| WUSS |
2026 |
Automating Excel Table of Contents Generation from SAS -Produced RTF Reports Without Predefined Metadata |
Joshua Lin |
source |
9 |
| WUSS |
2026 |
Building Better Data Science Workflows: Best Practices with Git, GitHub, Data Version Control (DVC), and MLflow for Open-Source Collaboration |
Ryan Paul Lafler |
source |
15 |
| WUSS |
2026 |
From Raw to Compliant: Applying Domain-Specific SAS Macros for Data Cut-Off in Clinical Trials |
Ballari Sen |
source |
26 |
| WUSS |
2026 |
Smarter CRF Reviews: An Open-Source AI Tool for Automated Protocol-to-CRF Gap Analysis in Clinical Trials |
Raj Sharma |
source |
9 |
| PharmaSUG CN |
2026 |
A Dual-Engine Architecture for MedDRA Auto-Encoding: Integrating Rule-Based Logic with LLM Semantic Retrieval in R Shiny |
Qingqing Wang,
Yaxiong Suo |
source |
6 |
| PharmaSUG CN |
2026 |
A Standardized Programming Framework for Daily Dose Dataset Construction from Multi-Source Clinical Data |
Xianjun Li,
Chengye Lu |
source |
10 |
| PharmaSUG CN |
2026 |
ADICE: A Proposed ADaM Dataset Structure for Intercurrent Events in the Estimand Framework |
Lijie Zhu |
source |
11 |
| PharmaSUG CN |
2026 |
AI-Assisted Code Generation for Structured Table: A Structured Filtering Logic Extraction Approach |
Qing Ma |
source |
6 |
| PharmaSUG CN |
2026 |
AI-Assisted QC for Clinical Trial Tables: A Scalable Approach for Heterogeneous Templates and Distributed Data. |
Shuchun (Coral) Wu |
source |
7 |
| PharmaSUG CN |
2026 |
AI-Native Real-Time SDTM Mapping and Exploration Agent |
Hao Chen,
Xuejie Zhou,
Haomin Yang,
Qianwang Wang |
source |
13 |
| PharmaSUG CN |
2026 |
An Integrated, AI-Augmented R Shiny Platform for Oncology Clinical Trial Decision Intelligence: From CDISC Data to Go/No-Go in One Unified Hub |
Zhiping Yan |
source |
28 |
| PharmaSUG CN |
2026 |
An Interpretable Machine Learning Framework for Exploratory Survival and Safety Analysis Using Random Survival Forests and SHAP |
Kun Shao |
source |
17 |
| PharmaSUG CN |
2026 |
Applying AI LLM to Reduce Manual Translation Workload in E-Data Package Submission |
Megan Chen |
source |
7 |
| PharmaSUG CN |
2026 |
Automated Clinical Text Classification with Robust Machine Learning for Pharmaceutical Data Curation |
Weineng Zhou |
source |
11 |
| PharmaSUG CN |
2026 |
Breaking Silos via Recycled Metadata: TOC-Driven Automation for Standard Title and Footnote Generation |
Tracy Cui |
source |
7 |
| PharmaSUG CN |
2026 |
Data Collection, Structuring, Analysis, and Reporting Considerations for CRS, ICANS, and IEC-HS in CAR-T Clinical Trials |
Zhemin Pan,
Jimmy Yang,
Shasha Hu,
Bo Li |
source |
24 |
| PharmaSUG CN |
2026 |
Development of an Efficient Automated Tool for Extracting Variables from Annotated Case Report Forms (aCRFs) and Mapping to SDTM Specification Files |
Ziyu Li |
source |
8 |
| PharmaSUG CN |
2026 |
DupChecker: A Python Tool for Detecting Code Duplication in Double Programming in Clinical Trials |
Xianhua Zeng |
source |
4 |
| PharmaSUG CN |
2026 |
Efficient Strategies for Handling Data Issues in Clinical Trial Submissions |
Kate Sun |
source |
7 |
| PharmaSUG CN |
2026 |
Evaluating Missing Data Imputation Methods for Clinical Trial Analysis |
Jiajun Wen |
source |
12 |
| PharmaSUG CN |
2026 |
From SAP to TFL: An AI-Assisted Workflow Framework for Automated Shells and TFLs |
Xiaoyu Ding,
Guoqing Zhao,
Huafeng Gao,
Zhiyuan Guo |
source |
18 |
| PharmaSUG CN |
2026 |
Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation |
Jingbo Zhu,
Jiehan Zhang |
source |
17 |
| PharmaSUG CN |
2026 |
Health Technology Assessment (HTA) Under EMA Framework: From Emerging to Mandatory Submission |
Jun Zhai |
source |
7 |
| PharmaSUG CN |
2026 |
Interactive Clinical Plot Gallery with Cross-Plot Subject Linking in R Shiny |
You (Lea) Lyu |
source |
10 |
| PharmaSUG CN |
2026 |
Interactive Clinical Trial Data Review Using Non-Shiny R HTML Dashboards |
Peng Tan |
source |
7 |
| PharmaSUG CN |
2026 |
Modernizing the Vaccine TAUG: An End-to-End, Output-Driven Framework for Reactogenicity, Immunogenicity, Efficacy, and Reviewer-Ready Submissions |
Lin Chen,
Jialiang Liu |
source |
18 |
| PharmaSUG CN |
2026 |
R in study validation |
Liang Han |
source |
7 |
| PharmaSUG CN |
2026 |
Safety Estimands and Analysis Dataset Design: Advancing Safety Evaluation in Clinical Trials |
Kun Ren,
Zeyu Guang |
source |
11 |
| PharmaSUG CN |
2026 |
The reporter package: A Powerful Reporting Package to Replicate SAS Output |
Bill Huang |
source |
24 |
| PharmaSUG CN |
2026 |
Word2PDF: A Python Tool to Convert and/or Combine RTF Files into a Single Bookmarked PDF/RTF with Table of Contents in a User-defined Order |
Xianhua Zeng |
source |
7 |
| PharmaSUG |
2026 |
A Human-in-the-Loop AI-Assisted Framework for ADaM Standardization |
Chunqiu Xia,
Feiyang Du |
source |
12 |
| PharmaSUG |
2026 |
A Statistical Programmer-s Guide to Tipping Point Analysis in SAS |
Ang Xu |
source |
9 |
| PharmaSUG |
2026 |
ADaM Pet Peeves Part 2: More Things Programmers Do That Make Us Crazy |
Sandra Minjoe,
Nancy Brucken,
Alyssa Wittle,
Nate Freimark,
Richann J. Watson,
Paul K. Slagle,
Tatiana Sotingco |
source |
15 |
| PharmaSUG |
2026 |
Agentic R in Clinical Trials: Empowering Statistical Programmers with Open Source LLM Packages & Positron Tools |
Philip Bowsher |
source |
15 |
| PharmaSUG |
2026 |
AI-Augmented SDTM Review: A Practical Framework Enhanced by a Structured Prompt Library |
Vihar Patel |
source |
10 |
| PharmaSUG |
2026 |
AI-Enhanced R Shiny App for Real-Time Clinical TLF Coding and Preview |
Dickson Wanjau |
source |
15 |
| PharmaSUG |
2026 |
AI-Recommended Color Palettes with QC for R Shiny Figures |
Yi Guo |
source |
19 |
| PharmaSUG |
2026 |
An End-to-End R-Based Pharmacokinetics (PK) Workflow for Regulatory Submission: The INAVO120 Study |
Qi Liu,
Shweta Vadhavkar |
source |
5 |
| PharmaSUG |
2026 |
An Experience Using R, SASSY and Tidyverse For Clinical Trial Analysis, From A SAS Programmer Perspective |
David W. Franklin |
source |
27 |
| PharmaSUG |
2026 |
An Innovative solution for Interactive Dashboards Using Python Flask Framework for Clinical Data Analytics |
Manish Bhagchandani |
source |
6 |
| PharmaSUG |
2026 |
ARMed AutoTable Macro Agents: An ARM-Driven Framework for Automated Analysis Table Generation |
Chengxin Li |
source |
10 |
| PharmaSUG |
2026 |
Automated Quality Checks for SDTM and ADaM Datasets Using R Shiny |
Shih-Che (Danny) Hsu,
Wei Qian |
source |
4 |
| PharmaSUG |
2026 |
Beyond Imitation: Selecting Synthetic Data with Purpose and Precision |
Sundaresh Sankaran,
Pritesh Desai,
Sherrine Eid |
source |
9 |
| PharmaSUG |
2026 |
Beyond Today-s Evidence: How AI-Enabled RWE Will Transform Development Speed, Study Quality, and Real-World Impact |
Sherrine Eid |
source |
15 |
| PharmaSUG |
2026 |
Boston Breakthroughs: A Dashboard-Driven Approach to Metadata and Audit Trails with SAS Clinical Acceleration |
Frances Gillespie,
Laura Watson |
source |
9 |
| PharmaSUG |
2026 |
Bridging the Gap: Table-Driven SAS Programming as a Pathway to AI in Clinical Trials Statistical Programming |
James Sun,
Vijaya Nadella,
Daniel Qi |
source |
15 |
| PharmaSUG |
2026 |
Building ADaM Datasets from Scratch using R: A SAS programmer-s Perspective |
Patel Mukesh,
Nilesh Patel |
source |
15 |
| PharmaSUG |
2026 |
Building Better Data Science Workflows: Best Practices with Git, GitHub, and Data Version Control (DVC) for Effective Collaboration |
Ryan Paul Lafler |
source |
17 |
| PharmaSUG |
2026 |
Building for the Long Haul: Managing Scope, Refactoring, and CI/CD in Internal R Packages |
Huijun An,
Blazej Neradilek,
Chenchen Yu,
Shannon Grant |
source |
9 |
| PharmaSUG |
2026 |
Challenges for small-mid size organization to build a GxP Compliant R Environment (CRE) |
Peng Zhang,
Tai Xie,
Peilin Zhou,
Christine Matakovich |
source |
7 |
| PharmaSUG |
2026 |
Closing the Loop: Validating AI-Generated SDTM Mappings using CDISC CORE and Synthetic Data |
Pietro Belligoli,
Constantin Weberpals,
Yarhy Flores Lopez |
source |
7 |
| PharmaSUG |
2026 |
CTCAE v6.0: The Good, the Bad, and the Ugly |
Elizabeth Dennis,
Grace Fawcett |
source |
6 |
| PharmaSUG |
2026 |
DefinePageChecker: A Python Tool for Verifying Page Number Hyperlinks in Define.xml |
Xianhua Zeng |
source |
4 |
| PharmaSUG |
2026 |
DOSEON: Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (PROC SQL, SAS Macro, DATA Step, and PROC FCMP) |
Inka Leprince,
Troy Martin Hughes |
source |
39 |
| PharmaSUG |
2026 |
Dynamic table generation for ongoing studies with unstable or changing cohorts |
Haoran Li,
Junruo Xia,
Yixuan Zhang |
source |
6 |
| PharmaSUG |
2026 |
Enhancing ADaM Specification Validation and Generation of SAS Codes Using LLM through Amazon Bedrock: A Practical Framework |
Pavan Kumar Tatikonda,
Ryo Nakaya,
Sravan Kongara |
source |
10 |
| PharmaSUG |
2026 |
Enhancing CDISC Standards Implementation (SDTM and ADaM) with PROC FCMP, PROC IML and Macro Loop Integration in Oncology Clinical Trials. |
Ajay Gupta,
Misikir Tesfaye |
source |
7 |
| PharmaSUG |
2026 |
From Automation to Evidence: Governing LLMs and AI Agents in Real-World Outcomes Research |
Sherrine Eid |
source |
17 |
| PharmaSUG |
2026 |
From Data Flood to Insight: Efficient SDTM Validation for High-Frequency Sources |
Seiko Yamazaki |
source |
6 |
| PharmaSUG |
2026 |
From Learner to Innovator: A Journey in R Empowered by AI to Enhance Narrative Review in Clinical Studies |
Shih-Che (Danny) Hsu |
source |
4 |
| PharmaSUG |
2026 |
From Manual to Automated": An SAS and R-Based Toolkit for Scalable SDTM Generation |
Hardik Sheth,
Eldho Alias |
source |
8 |
| PharmaSUG |
2026 |
From Molecular Subtypes to Bedside Decisions: An AI Approach for Personalized Critical Care Recommendations |
Xi Jiang,
Scott McClain |
source |
8 |
| PharmaSUG |
2026 |
From SAP to CSR: A Metadata-Driven TFL Workflow |
Bhavin Busa |
source |
7 |
| PharmaSUG |
2026 |
From Static Outputs to Living the Data - A Visualization framework transforming Clinical Data into a Continuous Asset |
Neharika Sharma |
source |
13 |
| PharmaSUG |
2026 |
From Tables to Tolerances: The Evolving Role of Statistical Programmers in Risk-Based Quality Management (RBQM) |
Vihar Patel |
source |
14 |
| PharmaSUG |
2026 |
Global Macro for Master Tracker |
Zhuo Chen,
Ted Lystig,
Xiaofan Cao,
Tuan Nguyen |
source |
8 |
| PharmaSUG |
2026 |
Goodbye SAS, Hello R: Practical Workflows for CDISC Standards |
Madeleine Penniston,
Alyssa M. Wittle |
source |
12 |
| PharmaSUG |
2026 |
Handling multiple screenings and multiple enrollments in SDTM: CDISC and FDA Guidance |
Laura Williams,
Andrea Gardani |
source |
7 |
| PharmaSUG |
2026 |
Harmonizing History: A Framework for Deriving Line of Therapy in Complex Integrated Summaries. |
Bhargav Koduru,
Kavitha Guddam,
Santosh Reddy Lekkala |
source |
15 |
| PharmaSUG |
2026 |
Hero-in-the-Loop: A Super Squad Approach to SDTM Creation & Validation |
Julie Ann Hood |
source |
7 |
| PharmaSUG |
2026 |
Implementation of Quality Tolerance Limits in Statistical Programming |
Yang Gao |
source |
4 |
| PharmaSUG |
2026 |
Implementing AI Agent-Driven Tools to Accelerate Clinical Research Workflows |
Nathan Lee |
source |
13 |
| PharmaSUG |
2026 |
Implementing Laboratory Toxicity Grading for CTCAE Version 6 and Beyond |
Keith Shusterman,
Mario Widel |
source |
6 |
| PharmaSUG |
2026 |
Insights and Experience Sharing with Patient-Reported Outcome Data Analysis in FDA-s Submission |
Jingyuan Chen |
source |
8 |
| PharmaSUG |
2026 |
Interactive Safety Data Visualization Platform: Transforming Adverse Event Analysis Review Through Dynamic Dashboards in Clinical Trials |
Nishanth Chinthala,
Alexandr Hromcenco |
source |
5 |
| PharmaSUG |
2026 |
Investigator-Initiated Trials: Navigating Statistical Programming Challenges with Practical Solutions |
Vikas Patil,
Ramesh Sundaram |
source |
6 |
| PharmaSUG |
2026 |
Managing Unblinded Activities Internally: The Independent Statistical Analysis Team (iSAT) Model |
Hong Wang,
Shu Chen,
Chen Li |
source |
4 |
| PharmaSUG |
2026 |
mkheader: An R Package for Automated Generation and Management of Program Headers in Clinical Trial Programming |
Gabriela Piasecki,
Laura Frederick |
source |
8 |
| PharmaSUG |
2026 |
Navigating Early Career Challenges in PK/ADA Statistical Programming |
Diyu Yang,
Sandeep Meesala |
source |
11 |
| PharmaSUG |
2026 |
One Study, Many Regulators: Submission-Ready Data Package for Multi-Region Filings |
Himanshu Patel,
Chintan Pandya |
source |
10 |
| PharmaSUG |
2026 |
Optimizing Clinical TFL Review with Python and Power BI: A Reproducible Workflow to Reduce QC Time and Improve Traceability |
Vijaya Lakshmi Cherakam,
Latha Donapati |
source |
10 |
| PharmaSUG |
2026 |
Protocol Analysis, Optimisation and Generation: Artificial Intelligence Enables a Unified View |
Sundaresh Sankaran,
Sherrine Eid |
source |
10 |
| PharmaSUG |
2026 |
PSMATCH: Propensity Score Matching of Clinical Trial Data with External Control Arms |
Ginger Barlow |
source |
8 |
| PharmaSUG |
2026 |
Python for Survival Analysis: Kaplan-Meier and Reverse KM Plots Made Easy |
Girish Kankipati,
Bala Rajesh Jakka |
source |
20 |
| PharmaSUG |
2026 |
R-Based Translation of Japanese Characters in Clinical Datasets for Regulatory Reporting |
Hardik Sheth,
Roshan Stanly |
source |
7 |
| PharmaSUG |
2026 |
Ready for Next Level SDTMs and ADaMs Compliance with End-to-End Processing? |
Sunil Kumar Gupta,
Tomás Sabat Stofsel |
source |
6 |
| PharmaSUG |
2026 |
SAS viya dynamic visualization of data |
Jumin Geng |
source |
5 |
| PharmaSUG |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source |
12 |
| PharmaSUG |
2026 |
Structure-Preserving Preprocessing of Clinical Documents for Large Language Model Analysis |
Zun Wang,
Juntao Yan |
source |
12 |
| PharmaSUG |
2026 |
Swimmer Plots - Some Practical Advice |
Ilya Krivelevich |
source |
11 |
| PharmaSUG |
2026 |
The Evolution of Open-Source Technologies in the Pharmaceutical Industry: Python as a Cost-Effective Solution for Clinical Statistical Programming |
Ramesh Potluri |
source |
9 |
| PharmaSUG |
2026 |
The Next Frontier of Statistical Programming: Vibe Coding with AI Coding Agents into SAS, R & Python |
Kevin Lee,
Nathan Lee |
source |
7 |
| PharmaSUG |
2026 |
Tipping Point Analysis: An Illustration of Sensitivity Analysis on Non-Administrative Censoring for Progression-Free Survival (PFS) |
Lihui Deng,
Kylie Fan,
Xiaoting Qin |
source |
7 |
| PharmaSUG |
2026 |
Traceability in Real World trials - just an aERD away. |
Ashwini Yermal Shanbhogue |
source |
7 |
| PharmaSUG |
2026 |
Unleash the R-volution: A Blueprint for Building Package Validation Capabilities in our own organization |
Kevin Lee |
source |
5 |
| PharmaSUG |
2026 |
Virtual Data, Real Standards: Leveraging Data Simulation for Smarter Clinical Trials |
Sangeeta Shabadi,
Nitesh Patil,
Jonathan Henshaw |
source |
16 |
| PharmaSUG |
2026 |
Women Leadership in AI-Driven Clinical Programming: Navigating Intersectionality and Innovation |
Lida Gharibvand |
source |
31 |
| PHUSE US |
2026 |
A Proc Compare Enhancement Macro |
Chris Weiner |
source
presentation source |
12 |
| PHUSE US |
2026 |
Accelerating Study Insights: Agile Data Visualisation Using R-Shiny |
Lin Yuan,
Heather Howell |
source
presentation source |
6 |
| PHUSE US |
2026 |
Acquiring a Compound with Multiple Clinical Trials? Let's Get Ready for a Type C Meeting! Key Considerations for Preparing Its Regulatory Submission |
Mathura P. Ramanathan,
Kajal Tahiliani |
source
presentation source |
12 |
| PHUSE US |
2026 |
Adopting gtsummary at Scale: How Roche Built a Companion to gtsummary to Standardise and Simplify ARD-Based Reporting |
Daniel Sjoberg |
source
presentation source |
3 |
| PHUSE US |
2026 |
Advancing Precision Medicine and Regulatory Readiness: Data Harmonisation and Statistical Methods for Companion Diagnostics Bridging Studies |
Ummul Vara Qurratul Ain |
source
presentation source |
10 |
| PHUSE US |
2026 |
Advancing Transparency, Patient-centricity, and Trustworthiness in Pharma: Metrics and Trends from the Good Pharma Scorecard [presentation] |
Jennifer Miller |
source |
48 |
| PHUSE US |
2026 |
Advancing Transparency-by-Design in Clinical Trial Disclosure: Real-World Applications for Regulatory Submissions [presentation] |
Obaraboye Olude,
Chantal Din-Bell |
source |
60 |
| PHUSE US |
2026 |
AI + Metadata : An Agentic Approach to Standards-Based Automation |
Kevin Burges |
source
presentation source |
10 |
| PHUSE US |
2026 |
AI as Copilot: Empowering, Not Replacing, Clinical Statistical Programmers |
Bhavesh Patkar |
source
presentation source |
5 |
| PHUSE US |
2026 |
AI Code Generator: Automating TFL Programming with ARS Metadata |
Bhavin Busa,
Navin Dedhia |
source
presentation source |
5 |
| PHUSE US |
2026 |
AI-powered approach for faster, more efficient authoring of clinical and regulatory documents |
Abhijeet Arora |
source
presentation source |
4 |
| PHUSE US |
2026 |
AI-Supported Validation of Open-Source Software |
Sven Prasse |
source
presentation source |
5 |
| PHUSE US |
2026 |
An AI-Driven Framework for Automated Statistical Analysis Plan Generation in Clinical Trials |
Qingyuan Zhang |
source
presentation source |
8 |
| PHUSE US |
2026 |
An RShiny App for Real-Time Continuous Safety Monitoring in Post-POC Trials: A Bayesian Approach to Decision-Making |
Jinquan Wu |
source
presentation source |
11 |
| PHUSE US |
2026 |
Anonymisation Strategies for Policy 0070 and PRCI Submissions [presentation] |
Stuart Donald |
source |
16 |
| PHUSE US |
2026 |
Around the Data DOSE-y Doe: Using DOSExx Variables within ADaM Datasets |
Inka Leprince,
Richann J. Watson |
source |
10 |
| PHUSE US |
2026 |
Automated Programming Consistency Checks: Enhancing Clinical Programming Quality, Efficiency and Scalability |
Narendra Babu Kolisetty |
source
presentation source |
5 |
| PHUSE US |
2026 |
Automating SDTM Compliance: A Web-Based SDTM Quality Control Tool Enhancing Clinical Trial Data Integrity |
Indraneel Narisetty,
Gopal Reddy Palvatla |
source
poster source |
11 |
| PHUSE US |
2026 |
Beyond Administration: Leveraging AI for Strategic Clinical Project Management |
Hayley MacKenzie |
source
presentation source |
7 |
| PHUSE US |
2026 |
Breaking into Statistical Programming: How SAS, R, Python, AI and ML Are Shaping Career Paths |
Kishore Pothuri |
source
presentation source |
6 |
| PHUSE US |
2026 |
Bridging Analysis and Strategy: The Transformative Role of Statistical Analysts in Drug Development |
Lingsong Yun |
source
presentation source |
17 |
| PHUSE US |
2026 |
Bridging Patient- and Trial-Level Insights |
Catharina Dahlbo,
Eva Kelty |
source
poster source |
5 |
| PHUSE US |
2026 |
Building High-Quality SDTM from Real-World Data: Lessons and Solutions |
Peishan(Jenny) Han,
Lixiao Chen |
source
presentation source |
4 |
| PHUSE US |
2026 |
Building Sustainable RBQM Frameworks: Challenges, Metrics and Real-World Results |
Nicole Stansbury |
source
poster source |
7 |
| PHUSE US |
2026 |
Building the Information Infrastructure Required for AI with Human in the Loop [presentation] |
Tomás Sabat Stofsel |
source |
53 |
| PHUSE US |
2026 |
Business Event Triggers - The Next Level of Automation |
Marc Jantke |
source
presentation source |
6 |
| PHUSE US |
2026 |
CDISC 360i: From Vision to Implementation - Lessons Learned and the Road Ahead [presentation] |
Peter Van Reusel |
source |
23 |
| PHUSE US |
2026 |
Changing rules on Data Ownership and Data Access [presentation] |
Darshan Kulkarni |
source |
38 |
| PHUSE US |
2026 |
Check Yourself: Edit Checks and Queries Made Easy with Shiny |
Maya Gans |
source
presentation source |
8 |
| PHUSE US |
2026 |
CLIQ: An AI-Native Framework for Unified Clinical Trial Data Quality Assurance |
Gopinath Viswanathan |
source
presentation source |
5 |
| PHUSE US |
2026 |
Closing the Gap: Identifying Missing Tumour Assessments in Oncology Studies |
Ke Xiao |
source
presentation source |
8 |
| PHUSE US |
2026 |
Common Issues in BIMO Clinical Site Dataset Packages |
Michael Beers |
source
presentation source |
7 |
| PHUSE US |
2026 |
Complex Trials, Simple Disclosures: Streamlined Transparency of Innovative Study Designs [presentation] |
Ritama Gupta Dempsey |
source |
15 |
| PHUSE US |
2026 |
Consistency, Speed and Satisfaction: The Impact of TLF Mock Shell Centralisation |
Jie Yang |
source
presentation source |
6 |
| PHUSE US |
2026 |
Creating Synthetic Data that Mimics Real-World Data for Accurate Analysis Programming Development |
Linshan Yuan,
Weiwei Xu |
source
poster source |
5 |
| PHUSE US |
2026 |
Data Designer: Empowering Data Preparation, Transformation, ARD Creation and Summarization for Insights and Decision Making |
Mukul K Mittal,
Sanjeev Rathore |
source
presentation source |
8 |
| PHUSE US |
2026 |
Data Diaries Don't Lie: Stats That Spot ePRO Risks |
Steven A. Gilbert,
Nechama Katan |
source
presentation source |
12 |
| PHUSE US |
2026 |
Data Harmonisation for ISS and ISE: A Practical Checklist for Integration Success |
Qiong Wei,
Lily Cheng |
source
presentation source |
10 |
| PHUSE US |
2026 |
Deceptive Twins: An Interactive Python Tool for Automated RTF Document Comparison in Clinical Submissions |
Aravind Gajula |
source
presentation source |
8 |
| PHUSE US |
2026 |
Defining Time Zero: Evaluating Index Line Selection Methods in External Control Arms (ECAs) |
Peishan(Jenny) Han,
Lorraine Fang |
source
presentation source |
5 |
| PHUSE US |
2026 |
Demystifying TMLE: A Practical Approach for Clinical Data Scientists |
Joshua Enxing |
source
presentation source |
12 |
| PHUSE US |
2026 |
Detecting Trends Before They Appear: AI-Driven Visualisations in Clinical Trials |
Steven Tan |
source
presentation source |
6 |
| PHUSE US |
2026 |
Deterministic Foundations, AI Acceleration: Lessons from Developing Hybrid Clinical Review Tools |
Matthew Kumar,
Srinivas Veeragoni |
source
presentation source |
8 |
| PHUSE US |
2026 |
Development Process of the Bioresearch Monitoring (BIMO) Package and the Obstacles Successfully Addressed [presentation] |
Sarad Nepal,
Murali Neela |
source |
19 |
| PHUSE US |
2026 |
Digital Twins for Clinical Submissions: Simulating Regulatory Review Before Submission |
Heather Gorr,
Divya Kapoor |
source
presentation source |
9 |
| PHUSE US |
2026 |
Electronic Clinical Data Submissions Across Global Regulatory Authorities |
Sampath Madanu |
source
presentation source |
12 |
| PHUSE US |
2026 |
Electronic Submission of Population PK Analysis Files ... What's Your Modus Operandi? |
Luai R. Alzoubi |
source
presentation source |
13 |
| PHUSE US |
2026 |
Empowering Clinical Data Review with Interactive Patient-Level Visualisations in {teal} |
Dony Unardi |
source |
4 |
| PHUSE US |
2026 |
Enhancing Clinical Trial Dataset Mapping with AI/ML Techniques: An Approach for CDISC Variable Prediction |
Parvee Kumar |
source
presentation source |
7 |
| PHUSE US |
2026 |
Ensuring Reliability of Medical Devices Through Statistical Oversight in the Age of AI |
Parvee Kumar,
Shrutimita Pokhariyal |
source
presentation source |
11 |
| PHUSE US |
2026 |
Equity as a Dimension of Quality: Embedding Equity into Risk-Based Quality Management |
Lydia Matombo |
source
presentation source |
6 |
| PHUSE US |
2026 |
Framework for Incorporating Estimands within the Statistical Analysis Plan |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE US |
2026 |
From ATC to ACG: Implementing the Concomitant Medication Grouping (ACG) Dataset in Clinical Trial Analysis |
Michelle Starkell |
source
presentation source |
8 |
| PHUSE US |
2026 |
From Automation to Audit-Readiness-AI's Growing Role in Statistical Programming |
Manoj Kumar Maripally |
source
presentation source |
4 |
| PHUSE US |
2026 |
From Complexity to Consistency: Scalable Anonymization Across Clinical Trial Portfolios [presentation] |
Ahmed Eldafrawy,
Danielle DiBonaventura |
source |
22 |
| PHUSE US |
2026 |
From Data Cutoffs to Decision-Making: Programming Futility Analysis in Oncology Clinical Trials |
Mani Mudumba |
source
presentation source |
6 |
| PHUSE US |
2026 |
From Legacy to ISS/ISE: Real-World Lessons in Module 5 Submissions |
Ajay Gunda,
Kishore Pothuri |
source
presentation source |
5 |
| PHUSE US |
2026 |
From Oversight to Insight - Rethinking Risk-Based Quality Management |
Madhumita Ghosh,
Eva Kelty |
source
presentation source |
5 |
| PHUSE US |
2026 |
From SAS to R for TLGs: A Case Study on Implementing an 'R-First, SAS-QC' Workflow for Time-to-Event Analysis |
Adler Moisés Fallas Rodríguez |
source
presentation source |
8 |
| PHUSE US |
2026 |
From System Exports to Standards: Will Standardisation of External Vendor Data Redefine Clinical Data Management/Analysis? |
Sai Sri Sravya Deevi |
source
presentation source |
5 |
| PHUSE US |
2026 |
From Tables to Text: Revolutionizing CSR Development with Generative AI |
Eric Zloty |
source
presentation source |
10 |
| PHUSE US |
2026 |
Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (DATA Step, PROC SQL, SAS Macro, and PROC FCMP) |
Inka Leprince,
Troy Martin Hughes |
source
presentation source |
32 |
| PHUSE US |
2026 |
Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! |
Troy Martin Hughes |
source
presentation source |
15 |
| PHUSE US |
2026 |
Group, Collapse, Repeat: A Dynamic SAS Macro for Stratification Pooling in Oncology Efficacy Analysis |
Venkatesh Burla |
source
presentation source |
9 |
| PHUSE US |
2026 |
Handle with Care: Study-Specific Assessment of R Package Risk |
Shannon Grant |
source
presentation source |
9 |
| PHUSE US |
2026 |
Harmonising gsm and the pharmaverse: Orchestrating SDTM, ADaM, TFLs and ARS in a Unified R Workflow |
Zelos Zhu |
source
presentation source |
3 |
| PHUSE US |
2026 |
Harnessing AI to Streamline ClinicalTrials.gov PRS Submissions |
Anaya Rehman |
source
presentation source |
6 |
| PHUSE US |
2026 |
Harnessing AI: Enhancing Test Data Quality and Efficiency in Clinical Trial Set-Up |
Rita Pecuch,
Varun Jagadeesh |
source
poster source |
8 |
| PHUSE US |
2026 |
Harnessing LLM-Augmented Automation for ADaM Dataset Generation |
Anil Mogha,
Ghourav Garg |
source
presentation source |
9 |
| PHUSE US |
2026 |
Hybrid SAS-R-Python Pipelines: Coordinating Multi-Language Workflows |
Kala Shivali,
Ashwin Chaudhari |
source
presentation source |
12 |
| PHUSE US |
2026 |
Implementing AI in Authoring Plain Language Summaries: Insights from a Live Project Experience [presentation] |
Vidhi Vashisht |
source |
18 |
| PHUSE US |
2026 |
Industry Trends in EU CTIS Transparency Documentation: A Comprehensive Analysis [presentation] |
Kara Groom,
Sanjay Bagani |
source |
14 |
| PHUSE US |
2026 |
Integrated Summary of Safety (ISS) Demystified: Practical Considerations for a Successful ISS |
Ji Qi,
Lily Cheng |
source
presentation source |
8 |
| PHUSE US |
2026 |
Interactive and Instant: GenAI-Driven Creation of Clinical Trial Applications |
Marcin Dubel |
source
presentation source |
12 |
| PHUSE US |
2026 |
Is There Really Any Benefit to Stratified Randomisation in Practice? |
Pavankumar Bhagat |
source
presentation source |
9 |
| PHUSE US |
2026 |
Key Guidelines, Tricks and Experiences for the PMDA and a Comparison with FDA and NMPA CDE Submissions |
Ramesh Potluri |
source
presentation source |
5 |
| PHUSE US |
2026 |
Leveraging Python for Synthetic External Vendor Data Generation for eCOA and ePRO |
Hitesh Raval |
source
presentation source |
9 |
| PHUSE US |
2026 |
Machine Learning Model for Risk Qualification of R Libraries |
Felipe Jimenez,
Luis Diego Leal Chaves |
source
presentation source |
13 |
| PHUSE US |
2026 |
Manual vs AI-Assisted Workflows: Practical Strategies for Complex R Package Development [presentation] |
Vedha Viyash |
source |
41 |
| PHUSE US |
2026 |
Mapping Minimal Residual Disease (MRD) Biomarker Data in Hematologic Malignancies: Clinical Significance and Data Standards in SDTM and ADaM |
Jyothi Nelakurthi |
source
presentation source |
8 |
| PHUSE US |
2026 |
Metadata-Driven TFL Generation: End-to-End Automation from Protocol to Output |
Bill Qubeck |
source
presentation source |
12 |
| PHUSE US |
2026 |
mkheader: An R Package for Automated Generation and Management of Program Headers in Clinical Trial Programming |
Laura Frederick |
source
presentation source |
8 |
| PHUSE US |
2026 |
Multi-Dimension Comparison Using SAS in the Context of Counting Hemophilia Bleeding Episodes |
Chivia Qianyun Zou,
Wenruo Hu |
source
presentation source |
8 |
| PHUSE US |
2026 |
Multi-Standard Submission - Process, Learnings and Recommendations for Best Practice |
Mukesh Garg |
source
presentation source |
8 |
| PHUSE US |
2026 |
Multiple Sclerosis Trials Unpacked: Standards, Endpoints and Programming Experience |
Daryna Teteriuk |
source
presentation source |
12 |
| PHUSE US |
2026 |
Next Generation QC Workflow Optimisation: Current Practices and Future Directions from the Emerging Trends & Innovation Working Group |
Matthew Finnemeyer,
Caroline Phares |
source
presentation source |
13 |
| PHUSE US |
2026 |
One Workflow to Rule Them All: Uniting Anonymisation and Confidential Information [presentation] |
Nirpal Virdee,
Lee Berry |
source |
14 |
| PHUSE US |
2026 |
Opening Session - Global Data Sharing Platforms: Aligning Frameworks, Pressures and Opportunities [presentation] |
Cathal Gallagher |
source |
31 |
| PHUSE US |
2026 |
Operationalising ICH E6 R3: A Risk-Based Blueprint for Data Management |
Vera Pomerantseva |
source
presentation source |
5 |
| PHUSE US |
2026 |
Optimising Flexibility and Consistency in Statistical Programming for Platform Trials: Practical Approaches to Data Cut, SDTM, ADaM and TFL Setup |
Kelly Fang,
Zhen (Laura) Li |
source
poster source |
6 |
| PHUSE US |
2026 |
Optimising Trial Design Dataset Creation To Minimise P21 Compliance Issues |
Rama Kudaravalli |
source
presentation source |
6 |
| PHUSE US |
2026 |
Orchestrating Multi-Agent Workflows for Complex Trial Data Integration |
Rajesh Hagalwadi |
source |
8 |
| PHUSE US |
2026 |
Outcome Blinding in External Control Arm Construction Using RWD: Challenges and Best Practices |
Peishan(Jenny) Han,
Lixiao Chen |
source
presentation source |
7 |
| PHUSE US |
2026 |
Perspective on Enterprise AI and Posit Tooling |
Philip Bowsher |
source
presentation source |
22 |
| PHUSE US |
2026 |
Pharmula 1 - Driving Innovation in Reporting |
Ellis Hughes |
source
presentation source |
4 |
| PHUSE US |
2026 |
Practical Survival Analysis Techniques for Clinical Trials Using SAS |
Xue Ding,
Tianchen Xu |
source
presentation source |
10 |
| PHUSE US |
2026 |
Pre-Conf as a Data Review Layer: An AbbVie Case Study for Optimised Clinical Data Flow |
Gian Prakash,
Aman Thukral |
source
presentation source |
2 |
| PHUSE US |
2026 |
Problem-First Agentic AI: Transforming Statistical Computing with Purposeful Automation |
Rajesh Hagalwadi |
source
presentation source |
8 |
| PHUSE US |
2026 |
Prompt Engineering in Gen AI: A Game Changer for the professional development of Statistical Programmers and Data Scientists |
Kevin Lee |
source
presentation source |
8 |
| PHUSE US |
2026 |
Ready for Next-Level SDTM and ADaM Compliance with End-to-End Processing? |
Sunil Kumar Gupta |
source
presentation source |
4 |
| PHUSE US |
2026 |
Real-Time AI-Driven TLF Generation with GAutoTLF |
Hao Xu,
Tyler Rowsell |
source
presentation source |
14 |
| PHUSE US |
2026 |
Real-Time Integration of EDC and Third-Party Data and Query Actions within an R Shiny Data Review and Patient Profile Tool |
Pavel Burmenko,
Terek J. Peterson |
source
presentation source |
5 |
| PHUSE US |
2026 |
Reduce, Reuse, R Shiny: A Framework for Building Generalised and Extensible R Shiny Applications |
Nathan Kosiba |
source
presentation source |
7 |
| PHUSE US |
2026 |
Regul-ASIAN Uncovered Navigating Reporting Requirements in Asian Markets [presentation] |
Ben Evans |
source |
42 |
| PHUSE US |
2026 |
Reproducible RWE at Scale: From Fragmented Data to Regulatory-Ready Insights |
Agnes Youn |
source
presentation source |
4 |
| PHUSE US |
2026 |
Revolutionising Clinical Data Transformation: Harnessing GenAI and Open Source for Automated SDTM Conversion |
Hao (Harry) Chen,
Jian Hua Hang |
source
presentation source |
6 |
| PHUSE US |
2026 |
Scalable Anonymisation for Complex Clinical Trial Data: A Sponsor-Vendor Perspective [presentation] |
Abby McDonell |
source |
30 |
| PHUSE US |
2026 |
Scalable R Packages Qualification Using a CI/CD Approach |
Natalia Andriychuk,
Jon Harmon |
source
presentation source |
4 |
| PHUSE US |
2026 |
Scaling Biometric Teams in Emerging Regions: Lessons from Armenia |
Nairi Alikhanyan,
Arman Melkonyan |
source
presentation source |
7 |
| PHUSE US |
2026 |
Scaling Interactive Applications for Clinical & RWE Insights Best Practices for Adoption, Compliance, and Long-Term Impact |
Chris McSpiritt Domino |
source
presentation source |
8 |
| PHUSE US |
2026 |
SCE White Paper 2.0 - A Modernised Framework for the Next Generation of Data Analysis |
Mark Bynens |
source
presentation source |
7 |
| PHUSE US |
2026 |
SDTM Automation: Implementation, Rollout and Lessons Learnt |
Bruce Chambers,
Minda Quiroz |
source
presentation source |
6 |
| PHUSE US |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source
presentation source |
10 |
| PHUSE US |
2026 |
SpecToSAS: AI-Powered SAS Code Generation from Study Specs |
Gargee Vaidya,
Lluis Gimenez |
source
presentation source |
12 |
| PHUSE US |
2026 |
Straight to the Source: Interactive Visual Dashboards for Data Cleaning |
Daniel Smith |
source
presentation source |
8 |
| PHUSE US |
2026 |
Submitting RWD: Where We Are and Where We Are Going |
Ingeborg Holt,
Sarah Ferko,
Jeffrey M. Abolafia |
source
presentation source |
24 |
| PHUSE US |
2026 |
Supporting Clinical Trial Recruitment Using Real-World Data |
Yi-Chien Lee |
source
presentation source |
2 |
| PHUSE US |
2026 |
Teaching Small Models To Think Big: Enterprise-Ready AI Through Knowledge Distillation |
Ramanathan Srinivasan,
Angu Sundaresh Krishna Kumar |
source
presentation source |
7 |
| PHUSE US |
2026 |
The Journey Beyond Anonymisation: Exploring the Secondary Use of Clinical Trial Data |
Yuliia Cherednichenko,
Tetiana Skorokhod |
source
presentation source |
18 |
| PHUSE US |
2026 |
The Journey of Deriving the Best Overall Response (BOR) for Solid Tumours - A Programmer's Perspective |
Milan Adesara,
Vishal Gandhi |
source
poster source |
7 |
| PHUSE US |
2026 |
The Revolution of Digitised Study Designs: Standards, Use Cases and Tools |
Berber Snoeijer |
source
presentation source |
3 |
| PHUSE US |
2026 |
The Use of Git in Statistical Programming |
Rita Pecuch,
Jim Coates |
source
presentation source |
9 |
| PHUSE US |
2026 |
Thriving in Change: Building People, Process and Technology Capabilities in Statistical Programming |
Ajay Aiyer |
source
presentation source |
5 |
| PHUSE US |
2026 |
Transforming Clinical Trials: Present Innovations and Future Paths with AI and Agentic Tools |
Sandeep Purwar |
source
presentation source |
5 |
| PHUSE US |
2026 |
Transforming Legacy Data into CDISC Standards: Practical Approaches and Regulatory Insights |
Khalif Halani,
Veena Palle |
source
presentation source |
6 |
| PHUSE US |
2026 |
Trends in eSub Evaluation Findings: A Twenty-Year Perspective on Data Traceability |
Lisa Kaye Brooks |
source
presentation source |
9 |
| PHUSE US |
2026 |
Turning Trial Data into Patient-Centric Insights |
Catharina Dahlbo,
Eva Kelty |
source
presentation source |
5 |
| PHUSE US |
2026 |
Unseen, Unstoppable: The Art of Invisible Leadership |
Johnson Dsouza,
Syed Gayaz Basha |
source
presentation source |
4 |
| PHUSE US |
2026 |
Validating AI in GxP: Test Harnesses, Guardrails and Compliance Controls |
Bill Qubeck |
source
presentation source |
14 |
| PHUSE US |
2026 |
What Patients are Interested in when it comes to Data Sharing [presentation] |
Deborah Collyar |
source |
18 |
| PHUSE US |
2026 |
Your Brain on AI: What We Gain, What We Risk, and How To Harness AI Without Losing Trial Integrity |
Aditya Gadiko |
source
presentation source |
6 |
| PHUSE US |
2026 |
{gsm} Operations - Implementing an Open Central Monitoring Framework |
Jenn Krohn |
source
presentation source |
6 |
| PHUSE US |
2026 |
{tflmetaR}: An R Package to Manage Metadata of Statistical Outputs |
Gary Cao |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Accelerating Clinical Study Startup: Automated eCRF Generation from Clinical Protocol Document |
Saiteja Nalla,
Kedar Deshpande |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Accelerating Pharma Innovation: The Role of SAS Synthetic Data |
Soundarya Palanisamy,
Anand Phand |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Advancing Clinical Programming Through Centres of Excellence |
Surendra Yajamanam |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Advancing Clinical Trial Analysis with Trimmed Means: Estimands, Intercurrent Events, and Regulatory Alignment |
Prasanth Palanisamy |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
AI for Adverse Event Signal Detection: Moving Beyond |
Monika Monika |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
AI-Driven Protocol Review: Accelerating and Simplifying Review |
Aditya Moogi |
source
poster source |
14 |
| PHUSE APAC |
2026 |
AI-Driven RBQM: Bridging Operational Excellence and Global Regulatory Demands |
Hyoback Lee,
Sailesh Bajpai |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
An AI-Powered Digital Standards Library for Accelerated Regulatory Submissions |
Anshu Aman,
Varun Sethuraman |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
Annualized Relapse Rate and Clinical Profiles in South Korean Multiple Sclerosis Patients: A Sample Cohort Study Using Korean National Health Insurance Data |
Seongjun Byun,
Jisuk Jo |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Auto-mapping of CDISC standards using Agentic AI |
Nithyanandan Thangavelu,
Rohit Bailur |
source
poster source |
2 |
| PHUSE APAC |
2026 |
Automated Comparison of EDC Transfers: Identifying Data Changes Across Versions |
Malavika Biju,
Vignesh V. Gopal,
Rahulraj Raju |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Automating TFL Generation Using R and pharmaRTF: From Data to Submission-Ready TFLs |
Dhananjay Srivastava |
source |
4 |
| PHUSE APAC |
2026 |
Batch Execution of CDISC SDTM/ADaM Programs with R |
Batch Execution,
Denny Sebastian,
Mohin K Mohanan |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Beyond Code: Elevating NextGen Statistical Programmers through Cross-Functional Learnings |
Saumil Tripathi |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Beyond Log-Rank: Advanced Survival Analysis for Non-Proportional Hazards in Oncology Trials |
Jagdish Nikam |
source
poster source |
7 |
| PHUSE APAC |
2026 |
Beyond Toxicity : Accelerating Dose -Finding with Pharmacokinetic -Driven Bayesian Design PKBOIN-12 |
Anetta Mary Xavier |
source
presentation source |
13 |
| PHUSE APAC |
2026 |
Bridging Statistical Expertise Through Intuitive Design: A Modern Web Interface for Automated SAS Procedure Selection in Cardiovascular Clinical Trials |
Likith Gopikumar |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Bridging the Divide: Harmonizing HL7 FHIR, OMOP, and CDISC Standards for Regulatory-Grade Real-World Evidence |
Yasa Sreekanth Reddy |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Building a Trustworthy RWD Analytics Platform Key Considerations and Strategies |
William Yuanhao Kuan,
Ashwini Reddy |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
CDISC 360i – Lessons Learned and Road Ahead [presentation] |
Peter Van Reusel |
source |
26 |
| PHUSE APAC |
2026 |
Connecting Open-Source and Enterprise Software: Enhancing Phase III Clinical Trial Design Through R Integration in East Horizon |
Pradip Maske,
Anoop Rawat |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Creating a clinical trial data package for Regulatory submission |
Pradip Sivaramakrishnan,
Anbarasan Durairajan |
source
poster source |
11 |
| PHUSE APAC |
2026 |
Critical & Sensitive Information (CSI) Paper AS02 Revolutionizing Clinical Quality: A Frontier Approach with Quality by Design (QbD), Infrastructure Modernization and Data-Driven Analytics |
Priti Gupta,
Deepa Balaji |
source
presentation source |
12 |
| PHUSE APAC |
2026 |
Cross-Platform Programming for Clinical Development: Practical Use of SAS, R, and Python |
Sandeep Lakkol,
Vinay S |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Decoding NCI-CTCAE: Smarter Lab Grading Through Metadata and Automation |
Zulfat Kapadia |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Development of Statistical Scientists for Pharmaceutical Drug Development at India Global Capability Centres |
Suresh Chenji |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
E2E Clinical Metadata Journey: 'Single Source of Truth' to Accelerate Clinical Research - From Collection and Tabulation to Analysis and Reporting |
Indumathi Narasetty |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
e2e Metadata Driven Model for Efficient Reporting Unveiling a Revolutionary Method for Defining Metadata and Reporting |
Priyanka Sarode |
source
presentation source |
2 |
| PHUSE APAC |
2026 |
Elastic Net Meets BART: A Hybrid Virtual Twins Approach for Reliable Subgroup Identification |
Alexis Bernard Dalam |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Elevating Clinical Data Presentation: Unlocking the Power of rtables in R |
Pooja Jasuja |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Elevating transparency in data standardization Applying XAI in SDTM, ADaM, and TLF Generation |
Shakila Jagadeesan |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Embracing the Semantic Shift: SDTMIG 4.0 and the Rise of Intelligent Clinical Data Standards |
Binitha Sathyabhama,
Venkateswarlu Layam |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Empowering Statistical Programmers: An Advanced Statistical Computing Environment [poster] |
Nikhil Khandelwal |
source |
1 |
| PHUSE APAC |
2026 |
End-to-End Continuous Integration and Deployment Pipeline for Multi Language Analytics Applications: A Clinical Data Management Case Study |
Avinash Patnaik,
Varun Sethuraman |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Enhancing Clinical Data Standardization Through Intelligent Mapping of eCRF Forms and Items to SDTM |
Saransh Khandelwal,
Kedar Deshpande |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Enhancing Stakeholder Accountability Involvement through Technological Advancement |
Muzzammil Ahmed |
source
poster source |
2 |
| PHUSE APAC |
2026 |
Ensuring Confidence in Trial Simulations: An Automated Testing Pipeline |
Hema Patil,
Anoop Rawat |
source
poster source |
3 |
| PHUSE APAC |
2026 |
Estimands Framework Through the Eye of a Statistical Programmer |
Shraddha Ganoo,
Kinjal Pandat |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Evolving with SDTM-IG v3.4: What Clinical Data Professionals Need to Know |
Prashanth Jatothu,
Nagaraju Salugu |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Faster Patient Recruitment in Clinical Trials through Simulations |
Keerthana Udupa |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
From Clicks to Compliance: How eCRF Design Decisions Echo Through to Submission |
Mary Shefoli |
source
poster source |
2 |
| PHUSE APAC |
2026 |
From Data to Digital Phenotypes: Modelling High-Dimensional PROs and Actigraphy Data in Decentralized Psychiatric Trials |
Sakshi Kaushik |
source
presentation source |
14 |
| PHUSE APAC |
2026 |
From Information to Insights: Harnessing Centralized Monitoring in RBQM to proactively identify and mitigate risks in Clinical Trials |
Bismita Borkakoty,
Priyangshu Chowdhury |
source
presentation source |
12 |
| PHUSE APAC |
2026 |
From Listings to Leadership: Navigating 18 Years of Statistical Programming Outsourcing and the Road Ahead |
Girish Havildar |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
From Static to Interactive: A Comparative Evaluation of ggplot2 and Plotly in Clinical Data Visualisation |
Mugdha Joshi |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
From XPT to JSON for submissions: Are we ready for the change? |
Poorna Suresh,
Bill Qubeck |
source
presentation source |
20 |
| PHUSE APAC |
2026 |
Harnessing Real-World Evidence and Data Visualisation to Improve Clinical Development and Accelerate Patient-Centric, Insight-Driven Decision-Making [presentation] |
Mujeebuddin Shaik |
source |
20 |
| PHUSE APAC |
2026 |
How Central Statistical Monitoring Drives a Risk-Based Approach to Clinical Trial Monitoring |
Charles Warne |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Innovating Clinical Signal Surveillance: Real-Time Dashboards for Protocol and PK Deviation Monitoring |
Rubina Pathan,
Jinu J. Nair |
source
poster source |
7 |
| PHUSE APAC |
2026 |
Integrating R Programming and Generative AI for Prompt-Driven Clinical Trial Data Analysis |
Vyom Bhatt |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
Integrating Real-World Evidence (RWE) and Digital Health Technologies (DHTs) with AI for Enhanced Patient Outcomes (RE) |
Varun Sethuraman |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Internal Paper AS19 Time-to-Event Analysis in Pain Management: A Case Study of the Double Stopwatch Method and ADaM Dataset Development in Relation to Rescue Medication |
Arnode Mukherjee,
Abhishek Paul |
source
presentation source |
12 |
| PHUSE APAC |
2026 |
Leading Through the Fog: Resilient Technical Leadership in a BANI Clinical World |
Satya Vyshnavi Thondapu |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Leveraging Data Visualization and R Shiny for Efficient Subgroup Analysis |
Srinidhi Ramachandran |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Leveraging Data Visualization from Clinical Trial Registries for Enhanced Insights |
Gowtham Manickaselvam,
Anand Boopalan |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Leveraging Real-World Evidence (RWE) in Clinical Trial Design: Statistical Challenges and Opportunities |
Muhammed Farzan K |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Mixed Models & Measured Outcomes: R Tips from the Clinical Trenches |
Keyur Shah |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
Next-Gen Statistical Programming in Clinical Trials: Driving Faster, Reliable, and Smarter Outcomes |
Shashikant Kumar,
Mrityunjay Kumar |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Optimising Few-Shot Prompting Strategies for Scalable and Reliable Enterprise AI Applications |
Varun Sethuraman,
Avinash Patnaik |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Optimizing Vendor Data Mapping: A DTS-Driven Approach to SDTM Readiness |
Chandan Patel Malyala,
Prasad Attini |
source
poster source |
4 |
| PHUSE APAC |
2026 |
Optimizing Workflow in Pharma: Innovative Dashboard Creation |
Dikshit A |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Precision Timing - Implementing Epoch Calculations with R for Clinical Data Integrity |
Sheik Ibrahim,
Ram Mohan Konda |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
RADAR: Rapid AGILE Development and Automated Reporting for Clinical Data Standards (Using R Shiny based Application) |
Neeraj Sharma,
Dhirendra Kumar |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
RbQM: An Intersection of Cross-Functional Collaboration of Clinical, Analytics, Statistics and Technology Domains for Better Clinical Trial Governance |
Abhishek Ghosh |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Reimagining Clinical Data Exploration: Animated Data Visualizations for Interactive Clinical Trial Storytelling |
Tony Mathew |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
RIP – Inconsistent Metadata Specifications with RAP (R And Python) Generate Specs Faster and Detect Early Errors to Speed Up Submissions |
Kairav Tarmaster |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Signal First: A Data-Driven Approach to Safety Prioritization Using SAS and Tableau |
Jinu J. Nair,
Rubina Pathan |
source
poster source |
9 |
| PHUSE APAC |
2026 |
Sparc AI: A Native Metadata-Driven Engine for End-to-End Clinical Trial Analysis |
Anil Mogha,
Ashwin Kumar Nyalakonda,
Gourav Garg |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Standardization of Auxiliary Medicinal Products (AxMPs) in Clinical Trials |
Divya Mekala,
Manoj Mishra |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Summary Outputs Made Simple: A Mirror View for SAS Programmers Exploring R |
Venkata Koteswara Rao Rayala |
source
poster source |
7 |
| PHUSE APAC |
2026 |
Targeted Maximum Likelihood Estimation: A Unified Approach for Confounding and Selection Bias |
Mahjoob O. Majeed,
Noel S. John |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
TFL Automation Through Design, Specify, Execute, and Report: A Seamless End-to-End Framework |
Malan Bosman,
Bhavin Busa |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
The AI-Powered Scribe: An Agentic Framework for Automated CSR Authoring |
Allwyn Dsouza |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
The Expanding Role of Real-World Evidence (RWE) in Supporting Regulatory Submissions |
Setu Sagar,
Nikhil A |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
The Intelligence Shift in AI Driven Clinical Trials [presentation] |
Sanjeev Sachdeva |
source |
11 |
| PHUSE APAC |
2026 |
The {teal} Adoption Playbook: Strategies, Tools and Learning Paths for Open Source [presentation] |
Vedha Viyash |
source |
39 |
| PHUSE APAC |
2026 |
TLF Treasure Hunt: Making Legacy Data Instantly Discoverable with RAD Finder |
Alexis Bernard Dalam,
Cielo Marie Castañeda |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Translational Biomarkers : Key Drivers of Clinical Outcomes in Oncology: Insights from Next-Generation Sequencing and Multi - Omic Profiling |
Mageshwaran Maran |
source
poster source |
6 |
| PHUSE APAC |
2026 |
Unified Meta-Study: Harmonizing Clinical Biomarker, Genomics and Clinical Trial Data for enhanced access, usability, and lifecycle management |
Namrata Padmashali |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Unlock Deeper Clinical Insights: A Unified Approach to Data Analysis with SAS, R, and Python |
Pavan Kallurkar |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Unlocking Biopharma Insights: A RAG-Enabled AI Framework for Rapid Access to Clinical and Nonclinical Study Data |
Lakshmi B K,
Sapna Chandran |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Unveiling Powerful Patient Data Insights Through Graph Database |
Sonal Dedhia |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
ValoRpacks - self-service R package validation |
Marc Jantke |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
Veristat TLF Packager (GUI): An Interactive Tool for Automated Creation of Combined PDFs with Bookmarks and Clickable Table of Contents |
Manivannan Mathialagan |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Vision to Decision: An Ocular case study on Estimand |
Deepak Kumar |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
Workforce 360°: Future-Proofing Leadership Models |
Sugumaran Muthuraj |
source
presentation source |
10 |
| PHUSE EU |
2025 |
A Code Assistant for Clinical Trial Tables |
Pietro Mascheroni,
Torben Brehme |
source
poster source |
6 |
| PHUSE EU |
2025 |
AI-Native Issue-Risk Intelligence: Connecting Issues to Known Risks and Identifying Emerging Risks |
Lawrence Dennison-Hall,
Alok Singh |
source
presentation source |
14 |
| PHUSE EU |
2025 |
An Evaluation of Data Formats for Clinical Reporting in a Multilingual Environment |
Craig Gower-Page |
source
presentation source |
12 |
| PHUSE EU |
2025 |
An Integrated J&J Platform To Enable Sustainable Clinical Trial Design |
Archana Nayak,
Jason LaRoche |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Automated Mock TFL Using an RAG LLM Setup |
Nicolaj Thostrup |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Bayesian Inference for Medical Device Reliability: Improving Safety and Effectiveness Assessments |
Shrutimita Pokhariyal |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Blinded & Coordinated: Aligning People and Processes To Prevent Unblinding |
Monika Bajek,
Dubravka Georgijevic |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Bridging Languages: Building Integrated Analytical Tools with SAS, R, and Python for Clinical Data |
Margarethe Povey |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Bridging the Gap: Translating Intercurrent Events into Analysis-Ready ADaM Datasets |
Meghna Diedrich |
source
poster source |
9 |
| PHUSE EU |
2025 |
Busy ? Productive: Breaking the Myth of Multitasking |
Goele Aerts |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Clinical Trials in the Quantum Era |
Michael Cooper,
Edyta Winciorek |
source
poster source |
11 |
| PHUSE EU |
2025 |
Close Encounters with Real-World Data |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
21 |
| PHUSE EU |
2025 |
Closing the Knowledge Gap with a Knowledge Management Strategy Empowered by Dashboards and AI |
Jannick Reymann Ravnborg,
Vicky Poulsen |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Code Compare A Machine Learning Based Framework for Code Plagiarism Analysis and Detection |
Saroj Kumar Jena |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Code, Collaborate, Conquer: The Future-Proof Programmer in an AI World |
James Shipley-Burgess |
source
presentation source |
4 |
| PHUSE EU |
2025 |
Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management |
Björn Koneswarakantha,
Frederik Collin |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Contributions to CAMIS PHUSE Project in 2025: Tobit Regression, Reference-based Multiple Imputation and Tipping Point Analysis |
Yannick Vandendijck |
source
presentation source |
12 |
| PHUSE EU |
2025 |
Cracking the Curve: Unlocking Clinical Insights with Ridgeline Plots |
Mariam Babayan,
Rafik Ghazaryan |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Decode Your Future: A Professional Development Growth Map for Programmers and Statisticians by Role Type |
Diana Stuart |
source
poster source |
8 |
| PHUSE EU |
2025 |
Detecting Logical Errors in Clinical Programming by Applying ChatGPT |
Illia Skliar |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Developing a Compliant and Scalable Statistical Computing Environment Based on PHUSE SCE Guidelines |
Casey Higgins,
Mark Sellors |
source |
5 |
| PHUSE EU |
2025 |
Disruption in Clinical Trials: How Conventional Roles Are Set to Change |
Amit Javkhedkar,
Kala Shivali |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Diversity, Inclusion and Equality Its Just Good Science! |
Roxanne McGuire,
Chris Ward |
source
presentation source |
19 |
| PHUSE EU |
2025 |
Embracing the Fear of Change in an Ever-Changing Industry |
Wilri Mackay |
source
presentation source |
4 |
| PHUSE EU |
2025 |
End-to-End R: Where To Start? |
Luke Thompson |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Enhancing Clinical Data Analysis: The PROC GREPLAY Advantage |
Vaisint Singh Muthudurai,
Kalyane Subramanian |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Enhancing Clinical Trial Management with Automated Data Integration and Real-Time Analytics |
Katrijn Op,
Sopra Steria |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Evaluating the Use of Real-World Data (RWD) as a Synthetic Control Group: A Statistical Approach |
Vasiliki Economou,
Dimitrios Kounelis |
source
poster source |
17 |
| PHUSE EU |
2025 |
Everyday AI for Statistical Programmers: Global Implementation of a Clinical Analysis Assistant |
Mathieu Cayssol,
Christoph Centner |
source
presentation source |
17 |
| PHUSE EU |
2025 |
FAIRchive Cloud-Based and GxP-Compliant Long-Term Archiving for Clinical Trial Data |
Frank Stoinski,
Alexander Lüders |
source
presentation source |
10 |
| PHUSE EU |
2025 |
FHIR for RWD Submissions: Why a US Regulation Signals a Global Shift And What You Need To Do Now |
Sanyogeeta Andhale,
Nachiket Thakkar |
source
presentation source |
11 |
| PHUSE EU |
2025 |
Fit-For-Purpose Approach of RBQM in Small Clinical Trials [presentation] |
Alicja Mark,
Agnes Verhoeven |
source |
15 |
| PHUSE EU |
2025 |
Framework for Integrating Omics Data with Other Clinical and NonClinical Data Sources |
Mehdi Harek,
Jonathon Keeney |
source
presentation source |
12 |
| PHUSE EU |
2025 |
From Breaking Bad to Breaking Data: Unlocking TFL PDFs |
Andrés Käsa,
Darius Tetsa |
source
presentation source |
13 |
| PHUSE EU |
2025 |
From Hassle to Harmony: Unifying Code Quality Experience in R and SAS |
Michael Thomsen |
source
presentation source |
9 |
| PHUSE EU |
2025 |
From Mock to Output: Using Generative AI to Write SAS Code for Standards-Based TFLs |
Kala Shivali,
Bhuvana Venkatappa |
source
presentation source |
16 |
| PHUSE EU |
2025 |
From Schedules of Activities (SoAs) to USDM: Automating Protocol Extraction Using Large Language Models |
Kerstin Forsberg,
Johannes Ulander |
source
presentation source |
10 |
| PHUSE EU |
2025 |
From Statistical Programming to AI Automation in Data Management: A Cross-Departmental Tech Journey |
Irene Luna,
Marcia Vaz |
source
presentation source |
5 |
| PHUSE EU |
2025 |
gridify: Enrich Figures and Tables with Custom Headers and Footers |
Maciej Nasinski,
Alexandra Wall |
source
poster source |
10 |
| PHUSE EU |
2025 |
Human in or Human out of the Loop: Impact and Things To Consider While Deploying AI |
Olivier Bouchard |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Interactive Exploration of Top Line Results: Integrating DaVinci with Teal |
Fabian Roethleithner,
Isabel Glauss |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Interactive Insights: Leveraging R Shiny for Enhanced Data Visualisation in Clinical Trial Readouts [presentation] |
Carolyn Fisher,
Elisabeth Deutschmann |
source |
20 |
| PHUSE EU |
2025 |
Is There Really Any Benefit to Stratified Randomisation Compared to Simple Randomisation with Covariate Adjustment? |
Pavankumar Bhagat |
source
presentation source |
9 |
| PHUSE EU |
2025 |
JazzAIR: Advancing Clinical Study Reporting Through Modern Development Practices and Testing Strategy [presentation] |
Jakub Sobolewski,
Chen Yang |
source |
34 |
| PHUSE EU |
2025 |
JSON for Submissions: Why You Should Care, What You Need To Know, and What To Do Now |
Bill Qubeck,
Sridhar Vijendra |
source
presentation source |
13 |
| PHUSE EU |
2025 |
Leading through talents |
Karolina Filar |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Lets Not Get Lost in Translation: Open-Source Adoption at Novartis |
Mark Baillie,
Orla Doyle |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Leveraging AI for Seamless SAS to R Migration: Challenges and Opportunities |
Milena Kraus,
Corrina Stoeckinger |
source
presentation source |
11 |
| PHUSE EU |
2025 |
Leveraging Open-Source Python Tools to Improve Efficiency and Transparency in Clinical Trials |
Sohan Lal,
Michael Olds |
source
presentation source |
8 |
| PHUSE EU |
2025 |
May the Code Be with You: Entering the pharmaverse Galaxy [presentation] |
Kirsty R. Lauderdale |
source |
17 |
| PHUSE EU |
2025 |
More Science, Less Bookkeeping: Our Path to Hyper-Efficient ADaM Program Generation via AI, Process Improvements, and Good Old-Fashioned Programming |
Matthew Phelps,
Nicolai Skov Johnse |
source
presentation source |
10 |
| PHUSE EU |
2025 |
Navigating Experimental Arms in Subtype Studies: Strategies for Precision and Clarity |
Narek Torosyan,
Edgar Sargsyan |
source
presentation source |
4 |
| PHUSE EU |
2025 |
New Multiple Imputation Approaches with SAS |
Andrea Parodi |
source
presentation source |
2 |
| PHUSE EU |
2025 |
On the Right Track: Managing Platform Modular Studies with a Central Metadata Switchboard |
Dubravka Georgijevic,
Carla Santillán |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Our Journey in Integrating External Control Arms (ECAs) and Real-World Data (RWD) for Rare Disease Trials |
Cyril Sombrin,
Gautham Selvaraj |
source
poster source |
4 |
| PHUSE EU |
2025 |
Oversight of Vendor Deliverables: A Layered Approach for Statistical Programming |
Pramod Chittam,
Camille Raets |
source
poster source |
3 |
| PHUSE EU |
2025 |
Pharmacokinetics Is Simple... Sometimes |
Vincent Buchheit |
source
presentation source |
12 |
| PHUSE EU |
2025 |
PHUSE Working Groups Highlights [poster] |
Chris Price |
source |
1 |
| PHUSE EU |
2025 |
Pooling Studies Through Code Traceability |
Hamdi Chouikha,
Kornelius Neufeld |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Redefining the role of the Statistical Programmer in an AI-Driven World |
James Shipley-Burgess |
source
poster source |
4 |
| PHUSE EU |
2025 |
Reproducibility, Lineage and Control: Building a Traceability Framework for the Modern Clinical Trial |
Bill Qubeck,
Shilpa Sood |
source
poster source |
6 |
| PHUSE EU |
2025 |
Rethinking Automation in the AI Era |
James Zee,
Liz Cole |
source
presentation source |
4 |
| PHUSE EU |
2025 |
Revolutionising Clinical Trial Monitoring and Data Analysis with AR- and VR-Driven Immersive Analytics |
Tej Narayan Yadav,
Saurabh Das |
source
presentation source |
7 |
| PHUSE EU |
2025 |
SAIL.R: Navigating Change Together in Clinical Analytics! |
Annemie Van Dijck |
source
presentation source |
11 |
| PHUSE EU |
2025 |
SAMBA: Bridging the Gap How GenAI Transforms Analysis Plans into ADaM Specs [presentation] |
Thiago Figueiredo,
Richard Becker |
source |
19 |
| PHUSE EU |
2025 |
Shots to Stats: AI's Take on Alcohol Units |
Liam Clothier |
source
poster source |
6 |
| PHUSE EU |
2025 |
Showcasing a Shiny Tool for Evaluating Biomarkers for Derisking Clinical Trials |
Stefan Thoma |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Small Application for Big Change: Data Integrity and Compliance Through Automated Decision Tracking with Shiny |
Olena Olishevska,
Mika Mäkinen |
source
poster source |
9 |
| PHUSE EU |
2025 |
Snakemake for Statistical Programmers: Automation and Reproducibility in Clinical Studies |
Nassim Sleiman,
Mathieu Cayssol |
source
poster source |
11 |
| PHUSE EU |
2025 |
Statistical Endpoints and Analysis in Diagnostic Imaging: The Matrix Has You and Your Data |
Srinivas Lanka,
James Sykes |
source
presentation source |
17 |
| PHUSE EU |
2025 |
Succeed with gridify: Enriching R Visualisations for Regulatory Submissions |
Alexandra Wall,
Jennifer Winick-Ng |
source
presentation source |
10 |
| PHUSE EU |
2025 |
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY)-estimation of adverse event risks |
Regina Stegherr,
Claudia Schmoor,
Jan Beyersmann,
Kaspar Rufibach,
Valentine Jehl,
Andreas Brückner,
Lewin Eisele,
Thomas Künzel,
Katrin Kupas,
Frank Langer,
Friedhelm Leverkus,
Anja Loos,
Christiane Norenberg,
Florian Voss,
Tim Friede |
source
poster source |
13 |
| PHUSE EU |
2025 |
Synthetic Data - the Game Changer in Drug Development |
Soundarya Palanisamy,
Anette Dalsgaard Jakobsen |
source
presentation source |
7 |
| PHUSE EU |
2025 |
The Show Must Go On: Best Practices for Submitting SDTM Data for Ongoing Studies |
Kristin Kelly |
source
presentation source |
8 |
| PHUSE EU |
2025 |
The Utilization of an Interface Based on a Graph Database |
Catharina Dahlbo,
Eva Kelty |
source
poster source |
8 |
| PHUSE EU |
2025 |
The Value of Clinical Trial Data: From Submission to Innovation |
Anne Katrine Alsing |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Think like a Quarterback - Deliver Projects, not fumbles |
Eoin Byrne |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Transforming Study-Specific Reporting (SSR Trends) Through an Innovative Data Pipeline Architecture Approach |
Archana Nayak,
Jill Ophoff |
source
presentation source |
3 |
| PHUSE EU |
2025 |
Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations |
Harinarayanan Gopichandran |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Turning Data into Deliverables: Automating Biometrics from Metadata to TFLs |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Twice as Much Aint Twice as Good: Is Double Programming Really the Gold Standard We Think it Is? |
Vitali Gering |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Unlocking Efficiency Through Digitisation: Plotting the Journey with Atlas for Clinical Trial Output Generation [presentation] |
Daphné Grasselly,
Eddy Foster |
source |
20 |
| PHUSE EU |
2025 |
USDM Synthetic Data |
Generation Stuart Malcolm |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Using CDISC USDM and BCs to select data from alternative data sources for regulatory purposes |
Berber Snoeijer |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Using Visual Dashboards to Improve Data Accuracy |
Daniel Smith |
source
poster source |
8 |
| PHUSE EU |
2025 |
Visualising the Invisible: Patient Journey with Waterfall, Spider and Swimmer Plots |
Varsha Mithun Patil,
Sunita Poojary |
source
presentation source |
14 |
| PHUSE EU |
2025 |
Why Wait for Real Data? The Power of Synthetic Data in Modern Clinical Trials |
Abhijeet Arora |
source
presentation source |
6 |
| PHUSE EU |
2025 |
{AdmiralMetabolic}: A Collaborative Journey To Develop an Admiral Extension Package for Metabolic Data |
Anders Askeland,
Olga Starostecka |
source
presentation source |
5 |
| MWSUG |
2025 |
Advancing Research in Rare Disease Using SAS Viya [presentation] |
Kelly Olano,
Pierce Kuhnell,
Laurie Smith |
source |
18 |
| MWSUG |
2025 |
Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into |
Troy Martin Hughes |
source |
14 |
| MWSUG |
2025 |
Mind the Gaps: Automating Multiple Imputation in Clinical Trial Workflows [presentation] |
Crisa Chen,
Jiangang Cai |
source |
30 |
| MWSUG |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker,
Pankaj Attri |
source |
7 |
| SESUG |
2025 |
Behind the Scenes with SAS Catalogs: Formats, Macros, and More |
Tejalkumari Tailor |
|
13 |
| SESUG |
2025 |
Craft Your Career as a Statistical Programmer: Opportunities and Challenges at CROs vs. Pharmas |
Xiao Xiao |
|
6 |
| SESUG |
2025 |
Creating DOCX Tables and Listings using Office Open XML from SAS |
Eric Qi,
Suhas R. Sanjee |
|
11 |
| SESUG |
2025 |
Efficacy + Safety in Phase 1/2 Immunotherapy Oncology Trials: OBD vs. MTD |
Ron Smith |
|
8 |
| SESUG |
2025 |
Enhanced Reporting Traceability: An R Shiny Application for Live Dependency Tracking and SAS Code Execution |
Tongda Che,
Laura Frederick,
Peng Wan |
|
11 |
| SESUG |
2025 |
Geocoding with the Google Maps API: Using PROC FCMP To Design User-Defined SAS Subroutines That Call User-Defined Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! |
Troy Martin Hughes |
|
14 |
| SESUG |
2025 |
Statistical Programmer's role in Bioresearch Monitoring (BIMO) package creation |
Sampath Madanu |
|
25 |
| SESUG |
2025 |
Versatile Graphic Presentation of Immunogenicity Analysis Results in Vaccine Studies with a Macro that Creates Multiple Forest Plots in One Output |
Hong Wang |
|
9 |
| WUSS |
2025 |
Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets |
Inka Leprince,
Richann J. Watson |
source |
13 |
| WUSS |
2025 |
Automating Clinical Study Reports: A Modular Framework for Continuous Data Reporting |
William Wei |
source |
7 |
| WUSS |
2025 |
PFS2, did you hear about it too? - Understanding the derivation of Progression Free Survival on next-line therapy (PFS2). |
Yeshashwini Chenna,
Lupetu Ntambwe |
source |
11 |
| WUSS |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker |
source |
7 |
| WUSS |
2025 |
Reach for R Low Hanging Fruit for Faster Results |
Sunil Kumar Gupta |
source |
4 |
| PharmaSUG |
2025 |
Addressing Challenges in Real-World Evidence Generation: The AI-SAS for Real-World Evidence Approach |
Takuji Komeda,
Yuki Yoshida,
Yohei Komatsu,
Yoshitake Kitanishi |
source |
7 |
| PharmaSUG |
2025 |
Addressing early challenges in RWD data standardization for analysis and reporting of RWE studies |
Xingshu Zhu,
Li Ma,
Bo Zheng |
source |
9 |
| PharmaSUG |
2025 |
Advanced Programming with R: Leveraging Tidyverse and Admiral for ADaM Dataset Creation with a Comparison to SAS |
Joshua J. Cook,
Richann J. Watson |
source |
20 |
| PharmaSUG |
2025 |
AI Empowered Metadata Governance |
Prasoon Sangwan |
source |
9 |
| PharmaSUG |
2025 |
AI is coming for you: New Biometric Leadership in the era of Gen AI |
Kevin Lee |
source |
7 |
| PharmaSUG |
2025 |
AI Performing Statistical Analysis: A Major Breakthrough in Clinical Trial Data Analysis |
Toshio Kimura,
Siqi Wang,
Weiming Du,
Songgu Xie |
source |
11 |
| PharmaSUG |
2025 |
An End-to-End Workflow for TFL Generation using R: MMRM Applications and Comparative Insights with SAS |
Kai Lei,
Jiaqiang Zhu,
Margaret Huang |
source |
14 |
| PharmaSUG |
2025 |
An Integrated R Shiny Solution for Dynamic Subgroup Adjustments and Customizations |
Yi Guo |
source |
20 |
| PharmaSUG |
2025 |
An Introduction to the Role of Statistical Programming in Medical Affairs |
Nagadip Rao |
source |
9 |
| PharmaSUG |
2025 |
Application of advanced GenAI tools in sample size estimation - questions and thoughts |
Igor Goldfarb,
Ella Zelichonok |
source |
12 |
| PharmaSUG |
2025 |
Automating Recurring Data Reconciliation for Serious Adverse Events Using SAS |
Patrick Dowe,
Gina Hird |
source |
25 |
| PharmaSUG |
2025 |
Automating Superscript Display for Upper and Lower Limit of Quantification Values in Pharmacodynamic Tables |
Anu Eldho |
source |
7 |
| PharmaSUG |
2025 |
Automation of Trial Design Domains generation using AI |
Prasoon Sangwan,
Mayank Bhatia,
Charusheela Thakur,
Shailesh Kumar |
source |
8 |
| PharmaSUG |
2025 |
Avoiding the Ouch: Mastering Time to Pain Progression Analysis |
Kavitha Boinapally,
Sai Krishna Pavan Nakirikanti,
Hank Dennis,
Yang Wang |
source |
9 |
| PharmaSUG |
2025 |
Bridging the Gap: Leadership of Statistical Programmers in Clinical Trials |
Allison Covucci,
Xiaohan Zou |
source |
6 |
| PharmaSUG |
2025 |
Build vs. Buy: Strategic Considerations for Implementing AI Solutions in Pharma and Biotech Companies |
Rajesh Hagalwadi |
source |
15 |
| PharmaSUG |
2025 |
Building a Scalable Training Platform for R: Empowering Analytics Excellence in Corporate Initiatives |
Michelle Page-Lopez,
Martyn Walker |
source |
7 |
| PharmaSUG |
2025 |
Building Resilient Teams |
Patrick Grimes,
Sajin Johnny |
source |
15 |
| PharmaSUG |
2025 |
Building Robust R Workflows: Renv for Version Control and Environment Reproducibility |
Junze Zhang,
Joshua J. Cook |
source |
17 |
| PharmaSUG |
2025 |
Calculating exact posterior probabilities and credible intervals from Bayesian borrowing robust mixture priors for binary, count and continuous outcomes in R and SAS |
Darren Scott,
Armando Turchetta |
source |
20 |
| PharmaSUG |
2025 |
Catch Page Overflow Issues Quick and Easy - A Simple Python Solution |
Junze Zhang,
Huei-Ling Chen |
source |
6 |
| PharmaSUG |
2025 |
Checking SDTM Datasets from Biostatistical Perspective |
Inka Leprince,
Elizabeth Li |
source |
14 |
| PharmaSUG |
2025 |
Clinical Data Explorer: Transforming Clinical Data into Actionable Insights |
Karma Tarap,
Oriana Esposito,
Maheshkumar Umbarkar,
Ramnath Dhadage,
Tamara Martin |
source |
6 |
| PharmaSUG |
2025 |
Clopper Pearson CI? get your data ready for it! |
Ruth Marisol Rivera Barragan,
Isaac Vazquez |
source |
7 |
| PharmaSUG |
2025 |
Common Issues in BIMO Clinical Site Dataset Packages |
Michael Beers |
source |
9 |
| PharmaSUG |
2025 |
Comparing SQL and Graph Database Query Methods for Answering Clinical Trial Questions with LLM-Powered Pipelines |
Jaime Yan |
source |
24 |
| PharmaSUG |
2025 |
Cytokine Release Syndrome (CRS) - Data Collection, Clinical Database Integration and Analyses in a Dose Escalation Cell Therapy Trial |
Cyrille Correia,
Venky Chakravarthy |
source |
13 |
| PharmaSUG |
2025 |
Data management and biostatistics synergy: how to achieve and what can be expected |
Diana Avetisian |
source |
11 |
| PharmaSUG |
2025 |
Debugging Options in R: Applications and Usage in Clinical Programming |
Madhusudhan Ginnaram,
Bingjun Wang,
Jeetender Chauhan,
Sarad Nepal |
source |
6 |
| PharmaSUG |
2025 |
Deciphering Exposure-Response Analysis Datasets: A Programmer-s Perspective for Oncology Studies |
Sabarinath Sundaram |
source |
6 |
| PharmaSUG |
2025 |
Decoding Laboratory Toxicity Grading: Unlocking the Potential and Overcoming Challenges of CTCAE |
Xiaoting Wu,
Lei Zhao |
source |
6 |
| PharmaSUG |
2025 |
Decoding the Role of Statistical Programming - A Decade of Keytruda Submissions and Approvals |
Mary N. Varughese,
Hong Qi |
source |
8 |
| PharmaSUG |
2025 |
Develop a SAS Macro for Dataset/Program Timestamp Version Control |
Chen Wang |
source |
4 |
| PharmaSUG |
2025 |
Does SDTM Validation Really Require Double Programming? |
Sunil Kumar Gupta,
Tomás Sabat Stofsel |
source |
5 |
| PharmaSUG |
2025 |
Efficacy Endpoints Related to CNS in Oncology Studies within ADaM |
Lihui Deng,
Kylie Fan |
source |
6 |
| PharmaSUG |
2025 |
Efficient Strategies for Handling Data Issues in Clinical Trial Submissions |
Kate Sun |
source |
7 |
| PharmaSUG |
2025 |
Enhance Safety Data Analysis Using SafetyGraphic R Package |
Vicky Yuan |
source |
17 |
| PharmaSUG |
2025 |
Enhancing Health Equity Outcomes through Comprehensive Data Collection of Marginalized Populations including Sexual Orientation, Gender Identity and Intersex Status (SOGI) |
Donna Sattler |
source |
5 |
| PharmaSUG |
2025 |
Exploring the Upcoming Integrated cSDRG! |
Srinivas Kovvuri,
Christine McNichol,
Randi McFarland,
Kiran Kumar Kundarapu,
Satheesh Avvaru |
source |
13 |
| PharmaSUG |
2025 |
Gen AI Assisted Code Conversion: From SAS to R Standard ADaM Templates |
Jeff Cheng,
Srinivas Malipeddi,
Gurubaran Veeravel,
Jaime Yan,
Suhas R. Sanjee |
source |
11 |
| PharmaSUG |
2025 |
Generating Synthetic Clinical Trial Data with AI: Methods, Challenges, and Insights |
Max Ma,
Weijie Yang,
Emily Ma |
source |
16 |
| PharmaSUG |
2025 |
Generative AI in Biometrics: Transforming Clinical Trials with Supercharged Efficiency an Innovation |
Kevin Lee |
source |
6 |
| PharmaSUG |
2025 |
Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! |
Troy Martin Hughes |
source |
14 |
| PharmaSUG |
2025 |
Guidance from the FDA authored "Submitting Patient-Reported Outcome Data in Cancer Clinical Trials" and recommendations for their implementation in study CDISC COA data. |
Charity Quick |
source |
14 |
| PharmaSUG |
2025 |
Handling Health Regulatory Information Requests: Best Practices and Strategies |
Himanshu Patel,
Chintan Pandya |
source |
11 |
| PharmaSUG |
2025 |
Handling Missing Data in External Control Arms: Best Practices, Recommendations, and SAS Code Examples |
Yutong Zhang |
source |
6 |
| PharmaSUG |
2025 |
Hands-on Training: eTFL Portal & TFL Designer Community |
Bhavin Busa |
source |
8 |
| PharmaSUG |
2025 |
Harnessing AI & CDISC ARS for Effortless Statistical Reporting & CSR Writing |
Bhavin Busa,
Navin Dedhia |
source |
10 |
| PharmaSUG |
2025 |
How to compute common clinical trials statistics in R |
Oleksandr Babych |
source |
15 |
| PharmaSUG |
2025 |
Identification of Domains Containing Screen Failure Participants in SDTMs and ADaMs for Reviewer-s Guides |
Sumanjali Mangalarapu |
source |
5 |
| PharmaSUG |
2025 |
Impact of Drug Accountability on Drug Compliance and Dose Intensity in Clinical Trials |
Vishal Gandhi,
Milan Adesara |
source |
7 |
| PharmaSUG |
2025 |
Implementation of the inverse probability of censoring weighting (IPCW) Model in Oncology Trials |
Mei Huang,
Shibani Harite,
Haijun Ma,
Linsong (Athena) Zhang |
source |
17 |
| PharmaSUG |
2025 |
Improve Your CRF Review Process: A Python-Based Approach to Capturing CRFs via Browser Automation |
Andrew Herndon |
source |
8 |
| PharmaSUG |
2025 |
In-house Data Monitoring Committee Report Programming |
Lingjiao Qi,
Amanda Plaisted,
Sreedhar Bodepudi |
source |
7 |
| PharmaSUG |
2025 |
Incorporating Frailty into Time-to-Event Analysis: A Practical Approach with R frailtypack |
Sunil Kumar Pusarla,
Avani Reddy Alla |
source |
9 |
| PharmaSUG |
2025 |
Integrated R scripts to Power BI |
Jun Yang |
source |
6 |
| PharmaSUG |
2025 |
Integrating Generative AI into Medical Writing: Building an Interactive Drafting and Search Framework |
Tadashi Matsuno |
source |
12 |
| PharmaSUG |
2025 |
Key guidelines, Tricks and Experiences for PMDA and comparison with FDA and CDE submission |
Ramesh Potluri |
source |
6 |
| PharmaSUG |
2025 |
Leveraging Health Technology Assessment (HTA) for Market Access: A Statistical Programming Perspective on German HTA Submission |
Rachana Agarwal,
Wendy Wang |
source |
5 |
| PharmaSUG |
2025 |
Leveraging previous study data for Extension studies: Structuring Subject and Participant Level Analysis datasets using CRF data |
Priyanka Thumuganti |
source |
7 |
| PharmaSUG |
2025 |
Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis |
Yuxin Wang,
Kelly Chao,
Wenqing Yu,
Hongbing Jin |
source |
11 |
| PharmaSUG |
2025 |
Methodology for AI-driven Outcome Prediction for Patients with Atrial Fibrillation After Transcatheter Aortic Valve Implantation (TAVI) |
Felix Just,
Krishna Padmanabhan,
Parth Jinger,
Amanda Borrow,
Rüdiger Smolnik,
Eva-Maria Fronk,
Neelam Yadav,
Sergei Krivtcov,
Stas Zakharkin,
Martin Unverdorben,
Asmir Vodencarevic |
source |
6 |
| PharmaSUG |
2025 |
Multiple Imputation Techniques in the Context of ADaM Datasets |
Shunbing Zhao,
Linping Li |
source |
11 |
| PharmaSUG |
2025 |
Navigating the transition of legacy processes for SDTM creation |
Jyothi Ketavarapu |
source |
5 |
| PharmaSUG |
2025 |
Our Second Brain: A Guide to Building Note System for SAS Programmer in Clinical Trial |
Zeyu Li |
source |
5 |
| PharmaSUG |
2025 |
Practical considerations for Intercurrent Events and Multiple Imputation |
David Bushnell |
source |
6 |
| PharmaSUG |
2025 |
Proc LIFE-REFLECT: Surviving the Leadership Journey |
Steve Nicholas |
source |
7 |
| PharmaSUG |
2025 |
Programming Challenges in Master Protocols |
Vijaya Jonnalagadda |
source |
6 |
| PharmaSUG |
2025 |
Programming Perspectives for Efficient and Accurate C-QTc Analysis |
Lingjie Zhang,
Lata Maganti,
Richard Moreton,
Runcheng Li |
source |
11 |
| PharmaSUG |
2025 |
Promising Zone Designs for Sample Size Re-estimation in Clinical Trials: Graphical Approaches Using SAS |
Zhao Yang,
Shivani Nanda |
source |
18 |
| PharmaSUG |
2025 |
Reach for R Low Hanging Fruit for Faster Results |
Sunil Kumar Gupta |
source |
4 |
| PharmaSUG |
2025 |
Risk Mitigation Solution for Kaplan-Meier Plot in Drug Labeling |
Bingjun Wang,
Jane X. Liao,
Suhas R. Sanjee,
Jeff Xia |
source |
13 |
| PharmaSUG |
2025 |
Sensitivity Analysis for Overall Survival |
Binal Mehta,
Patel Mukesh |
source |
13 |
| PharmaSUG |
2025 |
Slice, Dice, Analyze: Revolutionizing SDTM cuts with datacutr package |
Diego Madrigal Viquez |
source |
6 |
| PharmaSUG |
2025 |
Streamlining and Accelerating Clinical Research through AI and GenAI driven Insights and safety review of Medical and Scientific Literature |
Rohit Kadam,
Saurabh Das,
Rajasekhar Gadde,
Niketan Panchal,
Alejandra Guerchicoff |
source |
6 |
| PharmaSUG |
2025 |
Streamlining BIMO and Patient Profile Generation: A Python-Based Semi-Automated Approach Integrated with CSR Development |
Dmytro Skorba,
Mykyta Vysotskyi |
source |
15 |
| PharmaSUG |
2025 |
Streamlining Validation Review and SAS Program Management with R |
Huei-Ling Chen |
source |
11 |
| PharmaSUG |
2025 |
The Show Must Go On: Best Practices for Submitting SDTM Data for Ongoing Studies |
Kristin Kelly |
source |
9 |
| PharmaSUG |
2025 |
Time-to-Deterioration for Patients Reported Outcomes |
Christine S Teng |
source |
11 |
| PharmaSUG |
2025 |
Traceability and AI for Improved Understanding, Communication and QC of Clinical Trials |
Tomás Sabat Stofsel |
source |
5 |
| PharmaSUG |
2025 |
Transitioning External Clinical Studies to Internal: A Framework for Knowledge Transfer and Operational Excellence |
Chunqiu Xia,
Hong (Lily) Zhang,
Xiaohui Wang |
source |
6 |
| PharmaSUG |
2025 |
Understanding HIV: At-Risk Populations, Treatment, Prevention and Standardized Data Representation in HIV Studies |
Jyoti (Jo) Agarwal |
source |
12 |
| PharmaSUG |
2025 |
Unveiling Paradoxical Pathways: A Counterintuitive Compass for Strategic Decision-Making |
Anbu Damodaran |
source |
14 |
| PharmaSUG |
2025 |
Updating Define-XML packages: Tips and A Comprehensive Checklist |
Qiong Wei,
Ji Qi,
Lixin Gao |
source |
10 |
| PharmaSUG |
2025 |
Use Gen AI to program rules in R & Python to generate and validate metadata for data standards and study specifications. |
Priyanka Sawant,
Kairav Tarmaster |
source |
9 |
| PharmaSUG |
2025 |
Visualizing oncology data through 3D bar charts in R and Python |
Girish Kankipati,
Venkatesulu Salla |
source |
18 |
| PharmaSUG |
2025 |
You don-t have to handle the truth! Three Things to Know about Synthetic Data |
Catherine Briggs,
S. Robert Collins,
Sundaresh Sankaran |
source |
7 |
| PHUSE US |
2025 |
A Gen AI Agent for Statistical Output Review |
Peng Zhang,
Lizhong Liu |
source
presentation source |
6 |
| PHUSE US |
2025 |
A Guided User Experience for Automated Mapping |
Nathan Johnson |
source
presentation source |
9 |
| PHUSE US |
2025 |
A New Approach to Visualize Adverse Events |
Eva Kelty |
source
presentation source |
3 |
| PHUSE US |
2025 |
A Novel Pipeline for Generating Realistic Synthetic CDISC ADaM Datasets Using Large Language Models and Knowledge Graphs |
Chao Su,
Jaime Yan |
source
presentation source |
15 |
| PHUSE US |
2025 |
Accelerating Patient Safety with Knowledge Graphs: Lessons from a Successful Implementation |
Partha Bhattacharjee,
Kirti Aggarwal |
source
presentation source |
10 |
| PHUSE US |
2025 |
Actual Intelligence and Artificial Intelligence Joining Forces to Perform Statistical Analysis, Turning AI Hype into Reality |
Songgu Xie,
Toshio Kimura |
source
presentation source |
11 |
| PHUSE US |
2025 |
Advancing Safety Evaluation in Oncology Trials Using Estimands |
Reshma Radhakrishnan,
Lakshmi Mantha |
source
presentation source |
8 |
| PHUSE US |
2025 |
AI Ethical Considerations in Drug Development and Regulatory Review |
Tara Chavda,
Qingying Ally Lu |
source
presentation source |
5 |
| PHUSE US |
2025 |
An Integrated Approach to Protocol Deviation Management |
Jason Konn |
source
poster source |
3 |
| PHUSE US |
2025 |
An Intuitive Way to Derive the Last Known Alive Date in R |
Marckenley Mercie,
Diana Tai |
source
presentation source |
12 |
| PHUSE US |
2025 |
Big Data Analytics: Unlocking Insights from Vast Clinical Datasets |
Bill Qubeck,
Kala Shivalingaiah |
source
presentation source |
16 |
| PHUSE US |
2025 |
Biomedical Concepts: What Are They and Why Should I Care? |
Stuart Malcolm |
source
presentation source |
7 |
| PHUSE US |
2025 |
Building High-Performing Biometrics Teams: The SELF-REINFORCING LOOP and Leadership in Clinical Trials |
Arman Melkonyan |
source
presentation source |
6 |
| PHUSE US |
2025 |
Building Rome in a Few Months: How Open-Source Technologies Empower Small Pharma |
Chendi Liao,
Kasra Yousefi |
source
presentation source |
5 |
| PHUSE US |
2025 |
Can AI/ML Drive Data Analysis and Data Mapping in Clinical Trials? |
Philip Ross,
Revvity Signals |
source
presentation source |
11 |
| PHUSE US |
2025 |
Challenges of Genomic Data in Clinical Trials |
Hong Zheng,
Lingsong Yun |
source
presentation source |
8 |
| PHUSE US |
2025 |
Clinical Trial Reporting Automation Based on Knowledge Graph |
Jaya Simha Inampudi |
source
poster source |
5 |
| PHUSE US |
2025 |
Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP |
Ingeborg Holt,
Sarah Ferko,
Jeffrey M. Abolafia |
source
presentation source |
15 |
| PHUSE US |
2025 |
Data Transformation: Achieving Compliance with Irregular Data |
Reyes Eduardo Elizalde Duarte |
source
presentation source |
6 |
| PHUSE US |
2025 |
Demystifying the Handling and Mapping of External Data to CDISC Standards in Clinical Trials |
Murali Kanakenahalli,
Vamsi Kandimalla |
source
presentation source |
12 |
| PHUSE US |
2025 |
Differential Privacy (DP) Approach for Sharing Survival Analysis Data |
Elena Valkanova,
Bulat Fatykhov |
source
poster source |
11 |
| PHUSE US |
2025 |
Digital Health Technologies: Evolution, Insights and Future Directions [presentation] |
Vijay Pasapula |
source |
28 |
| PHUSE US |
2025 |
Dismantling the Black Box: Why We Need to Think Bigger About AI Integration |
Christina Dinger,
Joe Lebers |
source
presentation source |
7 |
| PHUSE US |
2025 |
E2E R Submission from a Roche Oncology Study |
Jingyuan Chen,
Hinal Patel |
source
presentation source |
6 |
| PHUSE US |
2025 |
Effective Adverse Event Management |
Eva Kelty,
Catharina Dahlbo |
source
poster source |
6 |
| PHUSE US |
2025 |
Efficient Positioning of QTL and Secondary Limit Thresholds in Clinical Trial Risk-Based Monitoring |
Vladimir Shnaydman |
source
presentation source |
12 |
| PHUSE US |
2025 |
Efficient TFL Review within Statistical Programming - Using R and SAS |
Siddharth Kumar |
source
presentation source |
8 |
| PHUSE US |
2025 |
Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers |
Julie Ann Hood |
source
poster source |
4 |
| PHUSE US |
2025 |
End-to-End Therapeutic Area Data Standards Development and Governance - A Case Study Involving CRS and ICANS |
Yaling Teng |
source
presentation source |
7 |
| PHUSE US |
2025 |
Enhancing Clinical Trial Data Queries with LLMs and Neo4j: A Flexible Framework for ADaM Dataset Management |
Jaime Yan |
source
presentation source |
28 |
| PHUSE US |
2025 |
Enhancing Data Accuracy and Collaboration Through Efficient Data Reconciliation Using SAS in Clinical Trials |
Piyush Makkapati,
Swathi Nattam |
source
presentation source |
8 |
| PHUSE US |
2025 |
eProtocol and the Promise of Automation |
Bill Qubeck,
Suhas Giriraj |
source
presentation source |
17 |
| PHUSE US |
2025 |
Evaluation of Open-Source Technologies in Clinical Trial Reporting |
Jaimin Patel |
source
poster source |
7 |
| PHUSE US |
2025 |
Evolution of Genomic Data Mapping from PF to GF in SDTM v3.4: Concepts, Challenges and Controlled Terminology with Genetic Variation Examples |
Rama Kudaravalli |
source
presentation source |
7 |
| PHUSE US |
2025 |
From Data Manager to Data Scientist: Navigating the Future of Data Management in Clinical Trials |
Debra Anderson |
source
presentation source |
6 |
| PHUSE US |
2025 |
From Manual to Machine: Leveraging Best-of-Breed Approaches in Clinical Data Management |
Joseph Lebers |
source
presentation source |
10 |
| PHUSE US |
2025 |
From RAGS to Riches: Creating a CDISC Standard Customer Service Agent Using R and Generative AI |
Daniel Woodie |
source
presentation source |
16 |
| PHUSE US |
2025 |
From Specification to CSR -- Toward a Unified Analysis and Review Platform |
Steve Ross |
source
presentation source |
7 |
| PHUSE US |
2025 |
From Topline to Triumph: Visualising the Pathways to Regulatory Approval |
Jasperlynn Kao |
source
poster source |
5 |
| PHUSE US |
2025 |
Future-Proofing Clinical Data Standards: Preparing for AI and Machine Learning |
Shivoy Pandita |
source
presentation source |
8 |
| PHUSE US |
2025 |
Gen AI-Powered Trial Performance Co-Pilot to Accelerate Clinical Trials |
Venkata Sureshbabu Bondu,
Mohit Sehgal |
source
presentation source |
4 |
| PHUSE US |
2025 |
Gen-AI for Statistical Reporting and Clinical Study Report (CSR) Writing |
Leveraging CDISC |
source
presentation source |
10 |
| PHUSE US |
2025 |
Generate Clinical Study Reports (CSRs) Using {quarto} and {shiny} |
Peng Zhang,
Jimmy Chen |
source
presentation source |
9 |
| PHUSE US |
2025 |
GPT-Powered Data Insights: Advancing Clinical Data Analytics with Large Language Models (LLMs) |
Melanie Hullings |
source
presentation source |
5 |
| PHUSE US |
2025 |
Harnessing Analysis Results Datasets (ARDs) for Clinical Reporting in R: Our First ARD-Based Filing Experience |
Daniel Sjoberg,
Nolan Steed |
source |
6 |
| PHUSE US |
2025 |
Harnessing the Power of R Shiny in a GxP-Compliant and Validated Manner for Clinical Trial Use |
Sanyogeeta Andhale,
Shilpa Sood |
source
presentation source |
13 |
| PHUSE US |
2025 |
How Unique is it for the Subject Identifier in a Study To Have Multiple Screenings and Enrolments? |
Anahita Vyas,
Rama Kudaravalli |
source
presentation source |
8 |
| PHUSE US |
2025 |
Innovative Data Cleaning to Prevent Unblinding Errors in Double-Blind Trials |
Ling Zhang,
Nan Zhou |
source
presentation source |
4 |
| PHUSE US |
2025 |
Innovative Storage of SDTM Mappings as JSON: Boosting Efficiency and Data Consistency |
Rohan Parmar,
Edgar Manukyan |
source
presentation source |
5 |
| PHUSE US |
2025 |
Intelligent Automation in Anonymisation for CTIS Submission |
Pinku Hooda,
Hiteshkumar Kanaiyalal Raval |
source
presentation source |
11 |
| PHUSE US |
2025 |
Interactive Dashboards - Empowering Clinicians to Generate Reports Instantly |
Inderjeet Arora |
source
presentation source |
8 |
| PHUSE US |
2025 |
Interactive Visualisation of Pooled Clinical Trial Safety Data |
Sara Bodach,
Ling Zhang |
source
presentation source |
7 |
| PHUSE US |
2025 |
Introducing TFL Viewer: A Centralised Platform for TFL Review, Collaboration and Approval |
Bhavin Busa |
source
presentation source |
5 |
| PHUSE US |
2025 |
Key Metrics for Success: Measuring Project Performance and Impact in the Face of Complex Clinical Trials |
Kavya Yachamaneni,
Hayley MacKenzie |
source
presentation source |
9 |
| PHUSE US |
2025 |
Kraken: A Shiny Application for Visualising SDTM Data in Early-Phase Clinical Trials |
Rutu Patel |
source
presentation source |
12 |
| PHUSE US |
2025 |
Leadership Presentations: Turning Disruption into Opportunity - Guiding Teams Through AI-Powered Transformation [presentation] |
Li Zheng |
source |
20 |
| PHUSE US |
2025 |
Let's Talk Future: Automated Solution for Standard-Compliant Data, Mock Shells and TFL Generation Using Open-Source Platforms with AI |
Inderjeet Arora,
Abhijeet Arora |
source
presentation source |
8 |
| PHUSE US |
2025 |
Leveraging HASH Technologies for Enhanced Clinical Trial Programming Efficiency |
Dmitrii Fedorychev,
Raviteja Nannapaneni |
source
presentation source |
5 |
| PHUSE US |
2025 |
Leveraging NLP for Clinical Trial Efficiency: Development of a Protocol-Aware AI Chatbot |
Seamus Gallivan,
Sairam Tangirala |
source
presentation source |
8 |
| PHUSE US |
2025 |
Leveraging Vector Databases to Enhance AI Applications in Pharmaceutical Research |
Angu Sundaresh Krishna Kumar,
Ramanathan Srinivasan |
source
presentation source |
11 |
| PHUSE US |
2025 |
LLMs in Clinical Trials: Overcoming Challenges Related to Patient Confidentiality and Intellectual Property |
Amit Javkhedkar,
Samip Shah |
source
presentation source |
7 |
| PHUSE US |
2025 |
LLMs in Drug Development - The Future is Closer Than We |
Think Chris McSpiritt |
source
presentation source |
9 |
| PHUSE US |
2025 |
Metaprogramming in R |
Sudhir Kedare,
Rajprakash Chennamaneni |
source
presentation source |
5 |
| PHUSE US |
2025 |
Natural Language to Code: AI-Powered Automation for CDISC-Compliant Datasets |
Vina Ro |
source
presentation source |
5 |
| PHUSE US |
2025 |
Next-Generation Deliverable Tracker |
Michael Byrne,
Stuart Malcolm |
source
presentation source |
5 |
| PHUSE US |
2025 |
OpenRBQM Extended: Endpoint Monitoring, Root Cause Analysis and Workflows |
Spencer Childress,
Jeremy Wildfire |
source
presentation source |
4 |
| PHUSE US |
2025 |
Optimising Collaboration and Quality Control in Outsourced Statistical Programming |
Mukesh Patel,
Nilesh Patel |
source
presentation source |
7 |
| PHUSE US |
2025 |
Optimising Leadership Strategies for Global Teams Through Time Zone-Based Task Assignment |
Tigran Alikhanyan,
Erik Torosyan |
source
presentation source |
7 |
| PHUSE US |
2025 |
Optimising SDTM and ADaM: Remediation Techniques for Data Accuracy |
Kishore Pothuri |
source
presentation source |
10 |
| PHUSE US |
2025 |
Optimizing Development and Regulatory Submission of eSUB Package for Exposure-Response and PK/PD Analysis |
Saumilkumar Tripathi,
Ephicacy Lifescience |
source
presentation source |
10 |
| PHUSE US |
2025 |
PHUSE in Japan: Past, Present and Future [poster] |
Koichi Yamaguchi |
source |
1 |
| PHUSE US |
2025 |
Planning Ahead: A Novel Approach to Creating Synthetic Immunogenicity Data |
Ruilan Wei |
source
presentation source |
5 |
| PHUSE US |
2025 |
Python's Future in Clinical Trials: Innovations and Collaborative Advancements |
Shweta Shukla,
Sohan Lal |
source
presentation source |
10 |
| PHUSE US |
2025 |
R Consortium's R-Based Test Submission Package for FDA Evaluation: A Milestone and a New Frontier in R-Based Regulatory Submissions |
Joel Laxamana |
source
poster source |
7 |
| PHUSE US |
2025 |
Real-World Data - Analysis-Ready Datasets: A Standardised, Specialised and Innovative Data Solution for Efficient Real-World Data Analysis |
Nayan Chaudhary,
Navdeep Pal |
source
presentation source |
12 |
| PHUSE US |
2025 |
Real-World Examples of eCOA Compliance and Audit Trail Review Using Advanced Statistical Methodology |
Jamie O'Neill |
source
presentation source |
5 |
| PHUSE US |
2025 |
Redefining FDA Submissions: The Future of Interactive R Shiny Dashboards |
André Veríssimo,
Vedha Viyash |
source
presentation source |
5 |
| PHUSE US |
2025 |
Revolutionising Cancer Trials with Adaptive Designs and Bayesian Analysis |
Navneet Jha |
source
presentation source |
11 |
| PHUSE US |
2025 |
Revolutionising Clinical Trials: Gen AI-Powered Biometrics Breakthroughs |
Kevin Lee |
source
presentation source |
6 |
| PHUSE US |
2025 |
Revolutionizing Clinical Trials with Intelligent Protocol Automation |
Zach Martin |
source
presentation source |
5 |
| PHUSE US |
2025 |
Risk Based Quality Management (RBQM) in Clinical Data Management |
Marcin Kot,
Anna Górecka |
source
presentation source |
9 |
| PHUSE US |
2025 |
Risk-Informed Data Strategies to Streamline Trial Complexity |
Tiina Erb |
source
presentation source |
3 |
| PHUSE US |
2025 |
Risk.assessr: A Tool for Assessing and Mitigating Risks with Open-Source R Packages in Clinical Trials |
Andre Couturier,
Edward Gillian |
source
presentation source |
10 |
| PHUSE US |
2025 |
Role of PK/PD, Biomarker Analysis in the Expansion of Phase 1 Trials |
Lavanya Peddibhotla |
source
presentation source |
7 |
| PHUSE US |
2025 |
Scaling up: accelerating self-hosted open-access LLMs to compete with the Big Three (ChatGPT, Claude, Gemini) |
Kostiantyn Drach |
source
presentation source |
12 |
| PHUSE US |
2025 |
SDTM Specification Automation Using an ML Approach to Provide Mappings |
Benzi Mathew,
Jaya Simha Inampudi |
source
presentation source |
5 |
| PHUSE US |
2025 |
SDTM UP - Versioning - Do's & Don'ts |
Utkarsh Pathak,
Ephicacy Lifescience |
source
presentation source |
9 |
| PHUSE US |
2025 |
Staying Out of the Ditch - How Governance Can Provide Your Team Guardrails |
Matt Tendler,
Chris McSpiritt |
source
presentation source |
5 |
| PHUSE US |
2025 |
Strategic Authoring of Clinical Study Reports to Leverage AI for Data Privacy and Public Disclosure |
Anaya Rehman |
source
presentation source |
6 |
| PHUSE US |
2025 |
Streamlining Machine Learning Modelling in Neuroscience Clinical Trials Through Cross-Functional Collaboration |
Jing Dai |
source
presentation source |
5 |
| PHUSE US |
2025 |
Synthetic Data Will Save the Day: Fact or Fiction |
Sherrine Eid |
source
presentation source |
7 |
| PHUSE US |
2025 |
The Best of Both Worlds: Machine Learning and Human-in-the-Loop Processing in TFl Design, Production and Validation |
Steve Ross,
Ilan Carmeli |
source
presentation source |
6 |
| PHUSE US |
2025 |
The Development of the CDISC eTFL Portal To Support the Adoption and Implementation of the Analysis Result Standard |
Bess LeRoy,
Bhavin Busa |
source
presentation source |
8 |
| PHUSE US |
2025 |
The Implementation of {teal} Shiny Apps for DMC Activities |
Zhen Wu,
Peng Zhang |
source
presentation source |
7 |
| PHUSE US |
2025 |
The Olympics of Data Ingestions |
Cathryn Herbst |
source
presentation source |
8 |
| PHUSE US |
2025 |
The Right Tool for the Job: Enhancing Risk-Based Monitoring and Data Cleaning |
Casey Higgins |
source
presentation source |
4 |
| PHUSE US |
2025 |
The Role of Quantitative Bias Analysis (QBA) in Ensuring the Reliability of Real-World Evidence (RWE) in Regulatory Submissions |
Brian Gillette,
Tasha Nagamine |
source
presentation source |
6 |
| PHUSE US |
2025 |
The Show Must Go On: Best Practices for Submitting SDTM Data for Ongoing Studies |
Kristin Kelly |
source
presentation source |
8 |
| PHUSE US |
2025 |
Topline Considerations for Double-Blind Trials |
Veena Palle,
Naresh Gopalkrishna |
source
poster source |
5 |
| PHUSE US |
2025 |
Transforming Clinical Trial Risk Assessments: From Checkbox to Quality-Driven Success [poster] |
Kristin Stallcup,
Rachael Geedey |
source |
1 |
| PHUSE US |
2025 |
Transforming Clinical Trials with AI-Driven Protocol Optimization and Next-Gen Statistical Programming |
Ravindra Shukla |
source
presentation source |
8 |
| PHUSE US |
2025 |
Transforming Clinical Trials: Leveraging Bayesian Statistics in Innovative Trial Design, Analysis, Applications and Navigating Challenges |
Jaskaran Singh Saini |
source
presentation source |
11 |
| PHUSE US |
2025 |
Transforming Pharma Master Data Management: Integrating Neo4j Knowledge Graphs with GraphRAG and Generative AI for Enhanced Data Querying and Analytics |
Sanjeev Kumar,
Sanjay Koshatwar |
source
presentation source |
7 |
| PHUSE US |
2025 |
Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations |
Harinarayanan Gopichandran |
source
presentation source |
8 |
| PHUSE US |
2025 |
Unleashing the Power of {teal}: New Features and Cross-Industry Collaboration |
Nina Qi,
Dony Unardi |
source
presentation source |
6 |
| PHUSE US |
2025 |
Unlocking the Secrets of Health: A Unified Approach to Biomarker and Clinical Data Integration |
Pavan Kumar Tatikonda |
source
presentation source |
8 |
| PHUSE US |
2025 |
Using Large Language Models for Consistency Checking of Tables, Listings and Graphs |
Yingying Wei |
source
presentation source |
7 |
| PHUSE US |
2025 |
Using the USDM and Ensuring Governance and Traceability to unlock the potential of Real-World Data sources for regulatory submissions |
Berber Snoeijer |
source
presentation source |
12 |
| PHUSE US |
2025 |
Utility Macro for Ensuring Consistent Updates of CRF Data in SDTM |
Naren Surampalli |
source
presentation source |
8 |
| PHUSE US |
2025 |
Validated by Verisian: The Future of Quality Control and Validation in Clinical Trial Analyses |
Henning Kuich |
source
presentation source |
12 |
| PHUSE US |
2025 |
Visualising Longitudinal Patients' Responses in a Clinical Study: A Unified Graphical Approach |
Avani Reddy Alla,
Sunil Kumar Pusarla |
source
poster source |
6 |
| PHUSE US |
2025 |
Wearable Technology: Enhancing Patient Monitoring and Real-World Evidence |
Bill Qubeck,
Sridhar Vijendra |
source
presentation source |
15 |
| PHUSE US |
2025 |
What R We Counting? The Quest to Quantify R Usage in Biostatistics Organizations |
Benjamin Arancibia |
source
presentation source |
3 |
| PHUSE US |
2025 |
Why Be Different? Shouldn't Everyone Be Using Agile to Deliver Their Clinical Trials? |
Michael S Rimler |
source
presentation source |
5 |
| MWSUG |
2024 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| PHUSE EU |
2024 |
A Guided User Experience for Automated Mapping |
Achilleas Zaras |
source
presentation source |
9 |
| PHUSE EU |
2024 |
A Tutorial for JFM Analysis in SAS for Modelling Recurrent Events and Death |
Edyta Winciorek |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Accelerating Trial Startup: Automated Central Monitoring Visualisations and Safety Package Management |
Carsten Rødseth Barsøe,
Charlotte Bergknut |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Agile? Wow! How Agile Ways of Working Can Drive Value for Conventional Clinical Trial Reporting |
Sheetal Patel,
Michael S Rimler |
source
presentation source |
6 |
| PHUSE EU |
2024 |
AI Got the Power: Streamlining Clinical Data Creation |
Emily Yates,
Matt Luppino,
Andrew Burd |
source
presentation source |
12 |
| PHUSE EU |
2024 |
Aligning Good Transparency Practice with the ISO/IEC 27559 De-Identification Framework [poster] |
Abby McDonell |
source |
1 |
| PHUSE EU |
2024 |
An Experiment on the Use of Altair SLC for Clinical Study Analytics |
Mark Holland,
Michael Byrne |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Analytical Risk-Based Monitoring (ARBM): From Targeted to Zero Source Data Verification (SDV) - Are Teams Ready for the Revolution? |
Plamena Kostadinova |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Artificial Intelligence Potential Use Cases in Clinical Data Engineering |
Deepak Pakalapati,
Mounika Pillamarapu |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Associated Patient Mapping in SDTM |
Sadiya Ait M'Bark |
source
poster source |
2 |
| PHUSE EU |
2024 |
Auto-Generating the List of Tables from a Statistical Analysis Plan - A Case Study [presentation] |
Jaya Simha Inampudi,
Krishna Gopal |
source |
14 |
| PHUSE EU |
2024 |
Automate Your Metadata: Reading and Modifying Information from PDF Files Using Python |
Salomo Benedikt Sparna,
Renate Scheiner-Sparna |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Behind the Blind: Enhancing Clinical Data Management with Python |
Niels Schrauwen |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Biomarkers Unleashed: A Programming Pipeline from Chaos to Clarity in Genomic Data |
Saskia Ständler,
Lea Zittlau |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Bridging Statistical Programming and Data Management: A Job Rotation Experience |
Frederikke Høyer |
source |
4 |
| PHUSE EU |
2024 |
Challenges and Wins of Pooling Internal and External Alzheimer's Data for Secondary Use |
Michaela Mertes,
Iska Gans |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Clinical Disease Endpoint Flag Implementation for Vaccine Studies |
Charumathy Sreeraman |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
13 |
| PHUSE EU |
2024 |
Data Curation Beyond Today's Standards |
Catharina Dahlbo,
Eva Kelty |
source
poster source |
5 |
| PHUSE EU |
2024 |
Data Pipelines in Clinical Trials Leveraging Apache Airflow for Automated Task Management |
Kostiantyn Zvieriev |
source
presentation source |
16 |
| PHUSE EU |
2024 |
DaVinci: A Modular Framework for Interactive Data Exploration and Visualisation in Clinical Research |
Isabel Glauß,
Stefan Döring |
source
presentation source |
5 |
| PHUSE EU |
2024 |
De-Identification of Participant Data for Public Disclosure |
Nicola Perry |
source
poster source |
7 |
| PHUSE EU |
2024 |
Developing Validated R Packages for Standardised and Efficient Statistical Report Generation at Roche Diagnostics |
Dorothee Childs,
Christoph Ehret |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Development of USDM through translation of human-readable protocols |
Jasmine Kestemont,
Stijn Rogiers |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Digital Data Flow: Achieving Protocol Digitalisation and Clinical Research Interoperability Through Multi-Stakeholder Collaboration [presentation] |
Mikkel Traun,
Lakshmi Sankar |
source |
21 |
| PHUSE EU |
2024 |
End-to-end Automation Using a Model-Driven Development (MDD) Workbench |
Stuart Malcolm |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Enhancing Quality of External Data |
Pascale Youinou |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Enhancing Standard Use by Creating a New Pivotal Role: The Standard Implementation Lead |
Marc-Antoine Prodhomme,
David Parkinson |
source
presentation source |
3 |
| PHUSE EU |
2024 |
Estimands: How to Make ADaM Implementation Your Friend |
Jaclyn Amberg |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Failed Clinical Trials: How to Benefit From Negative Experience |
Anna Amosova |
source
presentation source |
13 |
| PHUSE EU |
2024 |
FDA Business Rules and CDISC Open Rules: The Road to Adoption |
Nick De Donder |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Finding Out Subject Compliance Data in Clinical Trials |
Bhakti Gadekar,
Pravat Pradhan |
source
presentation source |
10 |
| PHUSE EU |
2024 |
From Senior Programmer to Head-of-Function: taking that 'leap-of faith' |
Roxanne McGuire |
source
presentation source |
5 |
| PHUSE EU |
2024 |
From Source to Submission: Getting the Best of Multiple Standards |
Jules Van der Zalm,
Berber Snoeijer |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Genomic Biomarkers: Development of a Pipeline for Distilling Patient Mutation Status |
Alexander Tchourbanov,
Karl Brand |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Guidance Beyond the SDTM Implementation Guide |
Kristin Kelly |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Harmonising FDA and PMDA Submission Requirements |
Luca Semeraro |
source
presentation source |
12 |
| PHUSE EU |
2024 |
How Agile Can you Be? Looking at Statistical Programming as a Software Development Process |
Oliver Wirtz,
Peter Bonata |
source
presentation source |
6 |
| PHUSE EU |
2024 |
How R Pharma? An Overview of How Our Industry Is Adopting the R Programming Language |
Ross Farrugia,
Ari Siggaard Knoph |
source
presentation source |
5 |
| PHUSE EU |
2024 |
How to Handle Huge Amounts of Output Tables - A Systematic Approach |
Nico Schreiber |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Incorporating Longitudinal Co-Medication Data into Population Pharmacokinetic (POPPK) Analysis Datasets: A Programmer's Perspective |
Aschwin van der Giesen,
Gerly van der Vleuten |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Innovation of Causal Inferential Frameworks for Biostatistics in Real-World Data and Evidence |
Anwesha Roy |
source
poster source |
8 |
| PHUSE EU |
2024 |
Insights of Using {admiralonco} at BMS: Facilitating Oncology Efficacy ADaM Datasets |
Yirong Cao,
Yi Yan |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Interactive Session - The State of Open Source Technology in Clinical Data Analysis, Reporting, and Submissions - A PHUSE Manuscript [presentation] |
Katja Glass,
Michael S Rimler |
source |
27 |
| PHUSE EU |
2024 |
Interpreting Data Cutoff Methods Using R |
Lusine Barseghyan,
Vahagn Barseghyan |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Introducing Graph Structure in Real-World Data Analyses |
Georgios Panagiotakis,
Maria Puri |
source
poster source |
10 |
| PHUSE EU |
2024 |
Keynote Speaker - Maneesh Juneja [presentation] |
Maneesh Juneja |
source |
104 |
| PHUSE EU |
2024 |
Leveraging 'Ensemble' Machine Learning Models to Drive Automation of Specification Generation and Data Mapping in Clinical Trial Data Submission |
Venu Mallarapu |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Leveraging Bayesian Posterior Probability for Analysing Treatment Effects in Clinical Trials: A Statistical Programmer's Guide |
Vismaya Kondassam Veedu |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Leveraging Data Science and Analytics to Optimise Clinical Trial Execution |
Melanie Hullings |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Leveraging Open Data and Machine Learning Enhanced Data Extraction for Clinical Trials Insight |
Hugo Bottois |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Leveraging Shiny Modules for Modular and Scalable Web Applications for Clinical Trials/Research |
Sohan Lal,
Pinku Hooda |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Making SDTM/ADaM CRT Packages Submission Ready |
Phillip Spowart |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Navigate Clinical Study Report Tables and Listings - The iTable & iListing Project |
Katja Glass |
source
presentation source |
13 |
| PHUSE EU |
2024 |
Navigating and Building Bridges: A Framework for Clinical Programming Using Open-Source Tools |
Yash Ankurbhai Shah,
Kavitha Allala |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Navigating First Data Submission: Pierre Fabre's Journey and Insights into Data Submission Challenges with the NMPA |
Romain Raymond,
Benoit Sansas |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Navigating the Clinical Research Landscape: The Role of Regulatory Intelligence and LLMs |
Federica Citterio,
Soundarya Palanisamy |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Navigating the Data Storm: Strategic Mastery for Sustaining Technical Excellence Amid Industry Shifts |
Mahdi About |
source
presentation source |
8 |
| PHUSE EU |
2024 |
OAK Productivity Experiment - How We Made SDTM Programming 5x Faster |
Amy Franklin,
Magdalena Krochmal |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Perl Regular Expressions in SDTM and ADaM Programming: Live Study Examples |
Pavol Valovic |
source
presentation source |
7 |
| PHUSE EU |
2024 |
R Shiny: From Code to Cloud |
Abu Sami |
source
presentation source |
12 |
| PHUSE EU |
2024 |
Revolutionising Statistical Programming Activities - StatProg CoPilot Consortium Leveraging on Open-Source World and Generative AI |
Sébastien Tourlet |
source
presentation source |
4 |
| PHUSE EU |
2024 |
SAIL.R: A Journey Towards R Software at Johnson & Johnson - A Training Perspective |
Yannick Vandendijck |
source
presentation source |
10 |
| PHUSE EU |
2024 |
SLURM + Open-Source Clinical Workflows: Current State |
Philip Bowsher,
Michael Mayer |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Stop Chatting, Start Scanning: AI's Visual Takeover in Pharma for Data Extraction with the Power of LLMs |
Ercan Suekuer |
source
presentation source |
3 |
| PHUSE EU |
2024 |
Strategies to Improve Understanding of Estimands and Analysis Section of Statistical Analysis Plan |
Inderjeet Arora |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Streamlining Complex Analysis: An SAS Macro for Marginal Structural Modelling |
Amine Khemiri |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Streamlining MHRA Inspection Preparation and Execution in CROs |
Nicolas Rouillé |
source
presentation source |
6 |
| PHUSE EU |
2024 |
The Development of the CDISC eTFL Portal to Support the Adoption and Implementation of the Analysis Results Standard |
Bess LeRoy,
Bhavin Busa |
source
presentation source |
8 |
| PHUSE EU |
2024 |
The Magical Trinity of TLF Automation: Digital Documents, Metadata, and GenAI |
Alastair Scarlett |
source
presentation source |
4 |
| PHUSE EU |
2024 |
The Open SCE: A Call to Action One Year Later |
Caroline Phares,
Pascal Bouquet |
source
presentation source |
6 |
| PHUSE EU |
2024 |
The Prentice-Wilcoxon Test to Study Time to Healing for Split Face, Double Blind, Dermatology Clinical Trials |
Shrutimita Pokhariyal,
Craig Wesselman |
source
presentation source |
10 |
| PHUSE EU |
2024 |
The R Journey to Submission |
Hinal Patel,
Welwyn Garden |
source
presentation source |
6 |
| PHUSE EU |
2024 |
The Significance of Generic Data Transfer Specification for Non-CRF Data in Clinical Trials |
Samaneh Sabiani,
Kristina Zweier |
source
presentation source |
9 |
| PHUSE EU |
2024 |
The TransCelerate/CDISC Digital Data Flow Project: Practical Electronic Study Designs [presentation] |
David Iberson-Hurst |
source |
8 |
| PHUSE EU |
2024 |
Transcriptomics - A Demanding Data Analysis that Expands the Limits of Regulated Clinical Data Handling |
Lea Yoshida Hildebrandt |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Trustworthy and responsible AI in health care and life sciences from a leadership perspective |
Mark Lambrecht |
source
presentation source |
3 |
| PHUSE EU |
2024 |
Unlocking the Enigma: Exploring SAS and R Strategies for Handling Non-Printable and Special Characters |
Eldho Alias,
Vishal V Nair,
Pooja Pradeep Pillai |
source
presentation source |
11 |
| PHUSE EU |
2024 |
Unveiling the Tipping Point: An In-depth Analysis |
Varsha Mithun Patil,
Ephicacy Lifescience |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Where Does Your SCE Fit in Your Data Strategy? |
Phil Loucks |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Why Are Old Wines Sometimes Tastier Than New Ones? |
Lars Andersson,
Henning Pontoppidan Föh |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Working with Omics data - A Statistical Programmers perspective |
Adrian Czaban |
source
presentation source |
10 |
| SESUG |
2024 |
A SAS MACRO to parse clinical conductor timesheets |
Kennedy Kamau Gachigi |
source |
6 |
| SESUG |
2024 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| SESUG |
2024 |
Applying Different Data Cutoff Dates for the Analysis of a Study Milestone |
Guowei Zhao,
Hong Qi |
source |
7 |
| SESUG |
2024 |
Efficient Way to Create Adverse Event (AE) Summary Tables by System Organ Class (SOC) and Preferred Term (PT) using PROC SQL in SAS |
Hardik Sheth |
source |
8 |
| SESUG |
2024 |
The Essentials Given - Becoming an Expert of Statistical Programming in Pharma & Health Care Industry |
Hongbo Li |
source |
5 |
| WUSS |
2024 |
iCSR: A Wormhole to Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade |
source |
7 |
| WUSS |
2024 |
Mastering Clinical Trial Reporting with SAS [presentation] |
Matthew J. Becker |
source |
4 |
| WUSS |
2024 |
Navigating Career Crossroads: From Statistical Manager to Entrepreneur |
Iuliana Constantin |
source |
8 |
| WUSS |
2024 |
SAS Viya in Action: Enhancing Life Sciences Data Analysis [presentation] |
Matthew J. Becker |
source |
13 |
| WUSS |
2024 |
Statistical Programmers Role for SPM Analysis |
Marckenley Mercie,
Ce (Colin) Zhou |
source |
11 |
| WUSS |
2024 |
Training Domain Specific AI for Clinical Data: Developing an AI Agent to Transform EDC Data to CDISC SDTM and then to ADaM Standards |
Sy J. Truong |
source |
12 |
| WUSS |
2024 |
Will statistical programmers be replaced by Artificial Intelligence? [presentation] |
Junying Zhang |
source |
20 |
| PharmaSUG CN |
2024 |
A quick way of the quality control in statistical programming process using SAS |
Donghai Liu |
source |
3 |
| PharmaSUG CN |
2024 |
Alluvial and Sankey Plots for Clinical Data Analysis - Implementation in SAS, R and Python |
Ke Yu |
source |
19 |
| PharmaSUG CN |
2024 |
Application of Natural Language Processing with R in clinical trials |
Feifeng Zhou,
Zhenchao Chen |
source |
11 |
| PharmaSUG CN |
2024 |
Auto-annotation CRF per SDTM-MSG 2.0 by R |
Qi Luo |
source |
9 |
| PharmaSUG CN |
2024 |
Automated PDF Data Extraction Tool - An Interactive Platform with Python Dash |
You (Lea) Lyu |
source |
4 |
| PharmaSUG CN |
2024 |
Automated Solution Drives Efficient Progress of DMC Analysis Projects |
Haoran Cui |
source |
5 |
| PharmaSUG CN |
2024 |
Best Overall Response (BOR) Confirmation in Oncology Clinical Trials: Insights from RECIST 1.1 |
Jihai Li |
source |
15 |
| PharmaSUG CN |
2024 |
Build PDF TFL Package with Table of Contents and Bookmarks - Taking Advantage of Unix Command Line |
Shimon Wang,
Abby Cai |
source |
10 |
| PharmaSUG CN |
2024 |
Deep Dive into IB and DSUR: A Compound Lead Programmer's Perspective |
Yang Song |
source |
7 |
| PharmaSUG CN |
2024 |
E9(R1) Program Practice and Its Application in Sensitivity Analysis |
Dawei Jiao |
source |
6 |
| PharmaSUG CN |
2024 |
Enhancing Patient Profile Visualization through Clustering Algorithms: An Exploration of Smart Data Presentation Techniques |
Zhengyuan Wen,
Kang Zhao |
source |
8 |
| PharmaSUG CN |
2024 |
Fighting with Special Characters in Data Management Programmer's Daily Work |
Fei Guo |
source |
20 |
| PharmaSUG CN |
2024 |
Implementation and tips on How to handle the ILD case in ADC trials |
Chen Lin Juan |
source |
8 |
| PharmaSUG CN |
2024 |
Implementation on concentration-QTc modeling |
Daoqing Li,
Deli Cao |
source |
20 |
| PharmaSUG CN |
2024 |
Implementing Statistical Methods in Companion Diagnostic: A Case Study in NSCLC |
Danxia Hu,
Mandy Gao,
Jianyong Tong |
source |
10 |
| PharmaSUG CN |
2024 |
Interactive analyses and displays for clinical data by utilizing a complete suite of analysis and reporting (A&R) tools via MedDRAH |
Zhiping Yan |
source |
13 |
| PharmaSUG CN |
2024 |
Introduction of Ophthalmic Examinations and the Preparation of SDTM OE Using SDTM IG 3.3 |
Shuang Qiu |
source |
15 |
| PharmaSUG CN |
2024 |
LiveTFL -- A Centralized Clinical Analysis Platform Based on the Teal Framework and Enhanced by AI |
Kaiping Yang,
Jie Liu,
Cheng Zhang,
Yuhang Liu |
source |
22 |
| PharmaSUG CN |
2024 |
Navigating Statistical Programming Challenges in Early Phase Oncology Trials |
Dandan Du |
source |
13 |
| PharmaSUG CN |
2024 |
Openstatsware: who we are and what we build together |
Liming Li |
source |
3 |
| PharmaSUG CN |
2024 |
Practice in Creating an R package for SDTM |
En Wang,
Longfei Li,
Xinyan Lai,
Qian Duan |
source |
5 |
| PharmaSUG CN |
2024 |
Programming Function Vendor Management in a Pharmaceutical Company |
David L. Wang,
Xingcan Yu |
source |
4 |
| PharmaSUG CN |
2024 |
Programming Perspective: Streamline Estimands, Strategies, and Design ADaM for Estimand |
Yuqin Wu |
source |
10 |
| PharmaSUG CN |
2024 |
R-based Solution for PK/ADA Simulated Data |
Kun Ren |
source |
7 |
| PharmaSUG CN |
2024 |
The Imperative Role of Data Cut-Off (DCO) in Clinical Trials: Ensuring Integrity and Precision in Oncology |
Nana Yang,
Chunpeng CZ Zhao |
source |
6 |
| PharmaSUG CN |
2024 |
Trial Agent: An Innovative and Intelligent LLM based Agent for Autonomous Clinical Trial Data Analysis |
Yu Peng,
Michael Wang |
source |
14 |
| PharmaSUG |
2024 |
A 'Shiny' New Perspective: Unveiling Next-Generation Patient Profiles for Medical and Safety Monitoring |
Helena Belloff,
William Lee,
Melanie Hullings |
source |
8 |
| PharmaSUG |
2024 |
A Change is Gonna Come: Maintaining Company Culture, Managing Time Zones, and Integrating Teams after a Global Acquisition |
Lydia King |
source |
3 |
| PharmaSUG |
2024 |
A Framework for Risk-Based Oversight for Fully Outsourced Clinical Studies |
Anbu Damodaran,
AstraZeneca Rare |
source |
7 |
| PharmaSUG |
2024 |
A Practical Approach to Automating SDTM Using a Metadata-Driven Method That Leverages CRF Specifications and SDTM Standards |
Xiangchen (Bob) Cui,
Min Chen,
Jessie Wang |
source |
23 |
| PharmaSUG |
2024 |
A Programmer-s Insight into an Alternative to TQT Study Data Submission |
Hiba Najeeb,
Raghavender Ranga |
source |
7 |
| PharmaSUG |
2024 |
A quick guide to SDTM and ADaM mapping of liquid Oncology Endpoints. |
Swaroop Kumar Koduri,
Shashikant Kumar,
Sathaiah Sanga |
source |
10 |
| PharmaSUG |
2024 |
aCRF Copilot: Pioneering AI/ML Assisted CRF Annotation for Enhanced Clinical Data Management Efficiency |
Chaitanya Pradeep Repaka,
Santhosh Karra |
source |
7 |
| PharmaSUG |
2024 |
Advancing Regulatory Intelligence with conversational and generative AI |
Saurabh Das,
Rohit Kadam,
Rajasekhar Gadde,
Niketan Panchal,
Saroj Sah |
source |
7 |
| PharmaSUG |
2024 |
Advancing the Maturation of Standardized CRF Design |
Sugumaran Muthuraj,
Rubha Raghu |
source |
9 |
| PharmaSUG |
2024 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman |
source |
7 |
| PharmaSUG |
2024 |
Agile Sponsor Oversight of Statistical Programming Activities |
Manuela Koska,
Veronika Csom |
source |
6 |
| PharmaSUG |
2024 |
Agile, Collaborative, Efficient (ACE): A New Perspective on Data Monitoring Committee Data Review Preparation |
Ke Xiao |
source |
6 |
| PharmaSUG |
2024 |
AI and the Clinical Trial Validation Process - Paving a Rocky Road |
Steve Ross,
Ilan Carmeli |
source |
7 |
| PharmaSUG |
2024 |
Amazing Graph Series: Swimmer Plot - Visualizing the Patient Journey: Adverse Event Severity, Medications, and Primary Endpoint |
Tracy Sherman,
Aakar Shah |
source |
16 |
| PharmaSUG |
2024 |
An approach to make Data Validation and Reporting tool using R Shiny for Clinica Data Validation |
Madhavi Gundu,
Vivek Jayesh Mandaliya |
source |
10 |
| PharmaSUG |
2024 |
Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets |
Inka Leprince,
Richann J. Watson |
source |
12 |
| PharmaSUG |
2024 |
Assurance in the Digital Age: Automating MD5 Verification for uploading data into a Cloud based Clinical Repository |
Laura Elliott,
Ben E. Bocchicchio |
source |
6 |
| PharmaSUG |
2024 |
Automating third party data transfer through digitized Electronic DTA Management |
Vandita Tripathi,
Manas Saha |
source |
6 |
| PharmaSUG |
2024 |
Automation of Report Generation Beyond Macro |
Hong Qi,
Mary N. Varughese |
source |
6 |
| PharmaSUG |
2024 |
AutoVis Oncology Presenter: Automated Python-Driven Statistical Analysis and Visualizations for Powerful Presentations |
Indraneel Narisetty |
source |
12 |
| PharmaSUG |
2024 |
Bayesian Methods in Survival Analysis: Enhancing Insights in Clinical Research |
Vadym Kalinichenko |
source |
11 |
| PharmaSUG |
2024 |
BIMO Brilliance: Your Path to Compliance Resilience |
Jai Deep Mittapalli,
Girish Kankipati |
source |
5 |
| PharmaSUG |
2024 |
Bridging AI and Clinical Research: A New Era of Data Management with ChatGPT |
Illia Skliar |
source |
12 |
| PharmaSUG |
2024 |
Challenges and Considerations When Building e-Submission SDTM Data Packages |
Wei Duan |
source |
8 |
| PharmaSUG |
2024 |
Converting FHIR to CDASH using SAS |
Pritesh Desai,
Mary Liang |
source |
5 |
| PharmaSUG |
2024 |
Data Harmony Revolution: Rocking Trials with Clinical Data Literacy |
Melanie Hullings,
Emily Murphy,
Andrew Burd,
Helena Belloff |
source |
5 |
| PharmaSUG |
2024 |
Dealing with Missing Data: Practical Implementation in SAS and R |
Isabella Y. Wang,
Lauren George,
Jin Xie |
source |
20 |
| PharmaSUG |
2024 |
Deep Dive into the BIMO (Bioresearch Monitoring) Package Submission |
Mathura P. Ramanathan,
Nancy Brucken |
source |
8 |
| PharmaSUG |
2024 |
Define-XML Conversion: A General Approach on Content Extraction Using Python |
Danfeng Fu,
Dickson Wanjau,
Ben Gao |
source |
15 |
| PharmaSUG |
2024 |
Demystifying Incidence Rates: A Step-by-Step Guide to Adverse Event Analysis for Novice Programmers |
Yuting Peng,
Ruohan Wang |
source |
10 |
| PharmaSUG |
2024 |
Design Considerations for ADaM Protocol Deviations Dataset in Vaccine Studies |
Rashmi Gundaralahalli Ramesh,
Jeffrey Lavenberg |
source |
12 |
| PharmaSUG |
2024 |
Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers |
Julie Ann Hood,
Jen Manzi |
source |
5 |
| PharmaSUG |
2024 |
Embracing Diversity in Statistical Computing Environments: A Multi-Language Approach |
Amit Javkhedkar,
Sridhar Vijendra |
source |
6 |
| PharmaSUG |
2024 |
Experimenting with Containers and webR for Submissions to FDA in the Pilot 4 |
André Veríssimo,
Ismael Rodriguez |
source |
8 |
| PharmaSUG |
2024 |
Exploring the Application of FDA Medical Query (FMQ) in Visualizing Adverse Event Data |
Tongda Che,
Danfeng Fu |
source |
12 |
| PharmaSUG |
2024 |
Game changer! The new CDISC ADaM domain ADNCA for PK/PD data analysis |
Santosh Ranjan |
source |
7 |
| PharmaSUG |
2024 |
Generation of Synthetic Data for Clinical Trials in Base SAS using a 2-Phase Discrete-Time Markov and Poison Rare Event Framework |
Adam Yates,
Misti Paudel,
Fengming Hu |
source |
14 |
| PharmaSUG |
2024 |
Generative Artificial Intelligence in sample size estimation - challenges, pitfalls, and conclusions |
Igor Goldfarb,
Vikas Sharma |
source |
26 |
| PharmaSUG |
2024 |
Guidance Beyond the SDTM Implementation Guide |
Kristin Kelly,
Michael Beers |
source |
11 |
| PharmaSUG |
2024 |
Guideline for Creating Unique Subject Identifier in Pooled studies for SDTM |
Vibhavari Honrao |
source |
5 |
| PharmaSUG |
2024 |
Handling of Humoral and Cellular Immunogenicity Data in SDTM |
Wei Duan |
source |
6 |
| PharmaSUG |
2024 |
iCSR: A Wormhole to Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade,
Chen Yang,
Matthew Travell,
Jagan Mohan Achi |
source |
7 |
| PharmaSUG |
2024 |
Implementation of composite estimands for responder analysis based on change from baseline in non-solid tumours |
Reshma Radhakrishnan |
source |
11 |
| PharmaSUG |
2024 |
Integrity, Please: Three Techniques for One-Step Solution in Pharmaceutical Programming |
Jason J. Su |
source |
15 |
| PharmaSUG |
2024 |
Interfacing with Large-scale Clinical Trials Data: The Database for Aggregate Analysis of ClinicalTrials.gov |
Joshua J. Cook,
Achraf Cohen |
source |
16 |
| PharmaSUG |
2024 |
LLM-Enhanced Training Agent for Statistical Programming |
Jason Zhang,
Jaime Yan |
source |
8 |
| PharmaSUG |
2024 |
Methodology for Automating TOC Extraction from Word Documents to Excel |
Jeetender Chauhan,
Madhusudhan Ginnaram,
Sarad Nepal,
Jaime Yan |
source |
5 |
| PharmaSUG |
2024 |
Navigating Success: Exploring AI-Assisted Approaches in Predicting and Evaluating Outcome of Clinical Trials and Submissions |
Ruohan Wang,
Chris Qin |
source |
9 |
| PharmaSUG |
2024 |
Oncology ADaM Datasets Creation Using R Programming: A Comprehensive Approach |
Ishwar Chouhan |
source |
29 |
| PharmaSUG |
2024 |
One size does not fit all: The need and art of customizing SCE and MDR for end users |
Shilpa Sood,
Sridhar Vijendra |
source |
6 |
| PharmaSUG |
2024 |
Ongoing Trends and Strategies to Fine-tune the CRO/Sponsor Partnership - Perspectives from Statistical Programming |
Mathura P. Ramanathan |
source |
10 |
| PharmaSUG |
2024 |
Opportunities and Challenges for R as an open-sourced solution for statistical analysis and reporting, from vendor's perspective |
Peng Zhang,
Lizhong Liu,
Tai Xie |
source |
8 |
| PharmaSUG |
2024 |
Optimizing Clinical Data Processes: Harnessing the Power of Metadata Repository (MDR) for Innovative Study Design (ISD) and Integrated Summary of Safety (ISS) / Efficacy (ISE) |
Lakshmi Mantha,
Purvi Kalra,
Arunateja Gottapu |
source |
9 |
| PharmaSUG |
2024 |
Periodic safety reports of clinical trials |
Murali Kanakenahalli,
Annette Bove,
Smita Sehgal |
source |
8 |
| PharmaSUG |
2024 |
PHUSE Safety Analytics Working Group - Overview and Deliverables Update |
Nancy Brucken,
Mary Nilsson,
Greg Ball |
source |
5 |
| PharmaSUG |
2024 |
Pictorial Representation of Adverse Events (AE) Summary - A new perspective to look at the AE data in Clinical Trials |
Pradeep Acharya,
Anurag Srivastav |
source |
11 |
| PharmaSUG |
2024 |
Piloting data visualization and reporting with Rshiny apps |
Yun Ma,
Yifan Han |
source |
7 |
| PharmaSUG |
2024 |
Piloting into the Future: Publicly available R-based Submissions to the FDA |
Benjamin Straub |
source |
9 |
| PharmaSUG |
2024 |
Programming with SAS PROC DS2: Experience with SDTM/ADaM |
Jianfeng Wang,
Li Cheng |
source |
6 |
| PharmaSUG |
2024 |
Protocol Amendments and EDC Updates: Downstream impact on Clinical Trial Data |
Anbu Damodaran,
Ram Gudavalli,
Kumar Bhimavarapu |
source |
11 |
| PharmaSUG |
2024 |
Quarto 1.4: Revolutionizing Open-source Dashboarding Capabilities |
Joshua J. Cook,
Kirk Paul Lafler |
source |
17 |
| PharmaSUG |
2024 |
Reimagining reporting and Visualization during clinical data management |
Vandita Tripathi,
Manas Saha |
source |
9 |
| PharmaSUG |
2024 |
Semi-Automated and Modularized Approach to Generate Tables for Clinical Study - Categorical Data Report |
William Wei,
Shunbing Zhao |
source |
8 |
| PharmaSUG |
2024 |
Simplifying Edit Check Configuration |
Vandita Tripathi,
Manas Saha |
source |
7 |
| PharmaSUG |
2024 |
Study Start Date - Let-s Get it Right! |
David C. Izard |
source |
6 |
| PharmaSUG |
2024 |
Submitting Patient-Reported Outcome Data in Cancer Clinical Trials - Guidance for Industry Technical Specifications Document [presentation] |
Flora Mulkey |
source |
48 |
| PharmaSUG |
2024 |
The Role of the Blinded Programmer in Preparation of Data Monitoring Committee Packages (for Clinical Trials) |
Binal Mehta,
Patel Mukesh |
source |
6 |
| PharmaSUG |
2024 |
The Survival Mode |
Varsha Ganagalla,
Natalie Johnson |
source |
12 |
| PharmaSUG |
2024 |
Translation from statistical to programming: effective communication between programmers and statisticians |
Diana Avetisian |
source |
10 |
| PharmaSUG |
2024 |
Unravelling the SDTM Automation Process through the Utilization of SDTM Transformation Template |
Lakshmi Mantha,
Inbasakaran Ramesh |
source |
11 |
| PharmaSUG |
2024 |
Updates on Preparing a BIMO Data Package |
Elizabeth Li,
Carl Chesbrough,
Inka Leprince |
source |
17 |
| PharmaSUG |
2024 |
Utilizing Data Visualization for Continuous Safety and Efficacy Monitoring within Early Development |
Margaret Wishart,
Tamara Martin |
source |
5 |
| PharmaSUG |
2024 |
Versatile and efficient graphical multiple comparison procedures with {graphicalMCP} |
Ethan Brockmann |
source |
3 |
| PharmaSUG |
2024 |
Visual discovery in Risk-Based Monitoring using topological models |
Kostiantyn Drach,
Iryna Kotenko |
source |
31 |
| PharmaSUG |
2024 |
What Being a Peer-to-Peer Mentor Offers - Perspective from an Individual Project Level Contributor |
LaNae Schaal |
source |
3 |
| PharmaSUG |
2024 |
Your Guide to Successfully Upversioning CDISC Standards |
David Neubauer,
Kapila Patel,
Toral Patel,
Soumya Rajesh |
source |
19 |
| PHUSE US |
2024 |
A Practical Approach to Automating SDTM Using a Metadata-Driven Method that Leverages eCRF Specifications and SDTM Programming Standards |
Xiangchen (Bob) Cui,
Min Chen |
source
presentation source |
12 |
| PHUSE US |
2024 |
A Privacy Methodology Toolkit to Improve Cross-Industry Clinical Data Reuse |
Patty Hegarty |
source
presentation source |
7 |
| PHUSE US |
2024 |
A standard data set format in regulatory submissions for clinical trials: automatic creation of headers, headers of headers, and footnotes |
Kevin R. Viel |
source
presentation source |
12 |
| PHUSE US |
2024 |
Agile, Collaborative, Efficient (ACE): A New Perspective on Data Monitoring Committee Data Review Preparation |
Ke Xiao,
Hong Wang |
source
poster source |
6 |
| PHUSE US |
2024 |
AI-Facilitated Monitoring Methods and Techniques to Enhance Participant Safety and Data Integrity |
Kris Wenzel,
Martin Bauwens |
source
presentation source |
6 |
| PHUSE US |
2024 |
Analysis of Same Objective - Different SAS Procedures: How to Choose a SAS Procedure Wisely for a Statistical Analysis? |
Pradeep Acharya,
Ephicacy Lifescience |
source
presentation source |
9 |
| PHUSE US |
2024 |
Approaching End-to-End Analysis Standardisation in Global and Therapeutic Areas Level |
Rudra Sheth,
Xiaohan Zou |
source
presentation source |
4 |
| PHUSE US |
2024 |
Are Platform Studies the Need of the Hour for Oncology Trials? |
Vidya Muthukumar |
source
presentation source |
2 |
| PHUSE US |
2024 |
Auditing an Open-Source Software Framework in a Regulatory Environment: Challenges, Gaps and Recommendations |
Uday Preetham Palukuru,
Shahrzad Talebian |
source
presentation source |
5 |
| PHUSE US |
2024 |
Automating ADaM Creation in Clinical Trials Part 2 |
Rie Ichihashi,
Lyubov Sushchenko |
source
presentation source |
7 |
| PHUSE US |
2024 |
Automating TLG Generation for Clinical Trials Leveraging R/R Shiny Technology and Cross-Therapeutic Area Expertise |
Vijay Sharma,
Margaret Wishart |
source
presentation source |
6 |
| PHUSE US |
2024 |
Beyond Outliers: Unsupervised Anomaly Detection in Clinical Trial Data |
Helena Yaben,
Kian Norouzi |
source
presentation source |
9 |
| PHUSE US |
2024 |
Beyond the Hype: A Pragmatic Approach to Leveraging AI/ML for Data Review |
Robert Musterer |
source
presentation source |
10 |
| PHUSE US |
2024 |
Build an Effective and High-Performance Team |
Helen Yang,
Richa Kala |
source
presentation source |
4 |
| PHUSE US |
2024 |
Case study of verification and validation methods for algorithmic predictive biomarkers |
Kartik Shetty |
source
presentation source |
4 |
| PHUSE US |
2024 |
CDISC Conformance Rules and the CORE Engine: Continuing the Road to Adoption |
Peter Van Reusel |
source
presentation source |
7 |
| PHUSE US |
2024 |
ChatGPT and AI/ML-Empowered Websites for All |
Jayapandian Nagamalaiyan |
source |
5 |
| PHUSE US |
2024 |
Clinical Project Management - Where Art, Science, and Craft Meet |
Hayley MacKenzie |
source
presentation source |
9 |
| PHUSE US |
2024 |
Codeless Queries: Harnessing AI to Translate Clinical Trial Questions into Custom Listings Through Intuitive UI Interactions |
Aditya Gadiko |
source
presentation source |
7 |
| PHUSE US |
2024 |
Collaborative Development of a Clinical Trial Data Anomaly Detection Tool within an Industry Consortium |
Pekka Tiikkainen |
source
presentation source |
6 |
| PHUSE US |
2024 |
Comparison of Standard Log-Rank Test with Selected Alternatives |
Elena Valkanova,
Bulat Fatykhov |
source
poster source |
18 |
| PHUSE US |
2024 |
Confirmation and Cancellation - Best Strategies for Data Collection and Handling within Solid Tumor Studies Using RECIST 1.1 and iRECIST Guidelines |
Sherry Ye,
Abraham Yeh |
source
presentation source |
10 |
| PHUSE US |
2024 |
Constructing Multilingual Visualisation Toolsets for Clinical Study Reports and Submission |
Jane X. Liao,
Bingjun Wang |
source
presentation source |
13 |
| PHUSE US |
2024 |
Data Designer: Empowering data mapping, manipulation and analysis for advanced insights and decision making |
Mukul K Mittal |
source
presentation source |
6 |
| PHUSE US |
2024 |
Data Pipeline - Improving Cycle Time and Shifting Data Closer to Analytics |
Jayasree Ivaturi |
source
presentation source |
6 |
| PHUSE US |
2024 |
Data Quality Evaluation of EHR FHIR API Real-World Data for FDA and Pharmaceutical Industry Use for Analysis and AI Implementation |
Sarah Ferko,
Abhishek Pandey,
Matthew Deady,
Brian Goodness |
source
presentation source |
10 |
| PHUSE US |
2024 |
Digital Protocol Vision ... How Digital Information Can Transform and Automate Our Processes [presentation] |
Bill Qubeck,
Chris Decker |
source |
27 |
| PHUSE US |
2024 |
Dynamic CDISC Analysis Results Data with the R Package {cards} |
Daniel Sjoberg |
source
poster source |
5 |
| PHUSE US |
2024 |
Dynamic document creation framework for streamlining cSDRG |
Umayal Annamalai |
source
presentation source |
7 |
| PHUSE US |
2024 |
Eliminating Duplicative Maintenance of Statistical Programs In Parallel Analyses Using a Single Control File |
Kavitha Boinapally |
source
poster source |
4 |
| PHUSE US |
2024 |
Eliminating SDTM Double Programming by Using a Validation Tool and Dummy Data |
Glenn Borgmans,
Tine Seeuws |
source
presentation source |
8 |
| PHUSE US |
2024 |
Embracing the Future of Digitisation: Uninterrupted Data Flows from Protocol Design to Electronic Data Capture [presentation] |
William Illis,
Diana Ye |
source |
18 |
| PHUSE US |
2024 |
Empowering Excellence: Strategies for Cultivating a Culture of Bold Decision-Making in Teams |
Mark Bynens |
source |
8 |
| PHUSE US |
2024 |
Empowering Healthcare Through Generative AI |
Ravindra Shukla,
Aman Bahl |
source
presentation source |
7 |
| PHUSE US |
2024 |
Enabling the Breakthroughs of Tomorrow: The Data Lakehouse for Clinical Trials |
Venu Mallarapu |
source
presentation source |
12 |
| PHUSE US |
2024 |
Enabling the Interoperable Data Ecosystem with the elluminate Clinical Data Cloud [presentation] |
Nathan Johnson |
source |
15 |
| PHUSE US |
2024 |
EOSS_MMRM V1.0: A Shiny Application for Estimand-Oriented Sample Size and Power Simulation Using MMRM Modelling |
Xiaoli Kong,
Jing Dai |
source
presentation source |
8 |
| PHUSE US |
2024 |
Evaluating Safety Compliance in Clinical Trials by Leveraging Patient Narratives and Deep Learning |
Sherrine Eid,
Sundaresh Sankaran |
source
presentation source |
9 |
| PHUSE US |
2024 |
Fidelity Assessment of Real-World Data (RWD) as an External Control Arm |
Mohamed Sameer,
Umayal Annamalai |
source
poster source |
5 |
| PHUSE US |
2024 |
Fight the Power - Supporting Study Teams with Niche R Packages for Delivering Statistical Packages |
Benjamin Arancibia,
Alice Ehmann |
source
presentation source |
4 |
| PHUSE US |
2024 |
From Data Iron to Data Gold |
Ashwini Yermal Shanbhogue |
source
poster source |
9 |
| PHUSE US |
2024 |
From Missing to Meaningful: Tackling Partial Dates in Clinical Trials |
Bhargav Koduru |
source
poster source |
4 |
| PHUSE US |
2024 |
Front-Loading Statistical Programming Using Automated Synthetic Data |
Faezeh Moshfeghifar,
Hemanth Padmakar |
source
presentation source |
5 |
| PHUSE US |
2024 |
Future Clinical Data Submission Standards: CDISC, FHIR, OMOP, or Hybrid Model |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
10 |
| PHUSE US |
2024 |
Future-Proofing Clinical Data Sciences: The Pivotal Role of Therapeutic Area Proficiency |
Sascha Ahrweiler |
source
presentation source |
12 |
| PHUSE US |
2024 |
Getting More Efficiency from your Instruments Using CDISC |
Franklin E. Menius |
source
presentation source |
5 |
| PHUSE US |
2024 |
Getting Started with Quarto |
Kevin Putschko |
source
poster source |
10 |
| PHUSE US |
2024 |
Good Statistical Monitoring {gsm}: An R Package for Risk-Based Monitoring and Clinical Trial Analytics |
Matt Roumaya,
Jeremy Wildfire |
source
presentation source |
5 |
| PHUSE US |
2024 |
Graphical overview for understanding, planning and execution of statistical programming activities using Neo4j |
Madhusudhan Reddy Mule Venkata |
source
presentation source |
13 |
| PHUSE US |
2024 |
Guidance Beyond the SDTM Implementation Guide |
Michael Beers,
Blue Bell |
source
presentation source |
10 |
| PHUSE US |
2024 |
Harness the Data's Potential in a Clinical Trial Process |
Eva Kelty,
Catharina Dahlbo |
source
poster source |
4 |
| PHUSE US |
2024 |
How No-Code Visualisation is Fast Becoming an Asset for Data Engineering and Data Science Teams |
Pritesh Desai |
source
presentation source |
6 |
| PHUSE US |
2024 |
ICH M11 Clinical Electronic Structured Harmonised Protocol (CeSHarP) and CDISC: Making the Electronic Protocol a Reality [presentation] |
Peter Van Reusel |
source |
33 |
| PHUSE US |
2024 |
iCSR: A Wormhole to the Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade |
source
presentation source |
7 |
| PHUSE US |
2024 |
Identifying Data Quality Issues in Clinical Trials Using OpenAI Embeddings |
Yash Shah,
Ashwin Rai |
source
presentation source |
5 |
| PHUSE US |
2024 |
Incorporating Real-World Data in a Low-Interventional Study: Challenges and Considerations |
Sandra VanPelt Nguyen |
source
presentation source |
8 |
| PHUSE US |
2024 |
It is Time to Get Answers: Handling Questionnaire Data in Respiratory Studies |
Valeriia Oreshko |
source
presentation source |
10 |
| PHUSE US |
2024 |
Journey of Reactogenicity Data from EDC to SDTM to Analysis Datasets |
Charumathy Sreeraman |
source
presentation source |
10 |
| PHUSE US |
2024 |
Key to EU-CTIS Success: Plan, Prepare, Participate |
Shawn Lantz,
Raina Agarwal |
source
poster source |
2 |
| PHUSE US |
2024 |
Large Language Models to Support RBM and Clinical Trial Development |
Sebastiaan Höppner,
Laura Trotta |
source
presentation source |
5 |
| PHUSE US |
2024 |
Leading Teams Through Clinical Data Transformation with Storytelling |
Alison Banda,
Katrina Rice |
source
presentation source |
3 |
| PHUSE US |
2024 |
Leveraging GitHub Actions and Continuous Integration in R Package Qualification |
Matt Roumaya,
Michael Stackhouse |
source
presentation source |
4 |
| PHUSE US |
2024 |
Mapping Real-World Data (RWD) to SDTM Samples for External Control Arm or Registry Studies |
Joe Xi,
Kevin Yang |
source
presentation source |
3 |
| PHUSE US |
2024 |
Mastering the Art of Adaptation: Innovative Strategies for Effective Change Management |
Mark Bynens |
source
presentation source |
13 |
| PHUSE US |
2024 |
My Data Are Too Good to Be True! Should I Worry About Fraud or Sloppiness? |
Johann Proeve |
source
presentation source |
9 |
| PHUSE US |
2024 |
Navigating RBQM Change Management: Real-World Strategies for Success |
Jamie O'Neill |
source
presentation source |
4 |
| PHUSE US |
2024 |
Navigating the Safe Integration of AI (ChatGPT) into Clinical Trials Programming Workflow |
Mykyta Vysotskyi |
source
presentation source |
10 |
| PHUSE US |
2024 |
NEST: How Could We Generate and Deliver Clinical Insights Even Faster? |
Vincent Shen |
source
presentation source |
4 |
| PHUSE US |
2024 |
Novel Ways to Leverage Your Real-World Data Investment in Integrated Evidence Package Submissions |
Sherrine Eid |
source
poster source |
6 |
| PHUSE US |
2024 |
Optimizing Clinical Research: Using AI for Automated Validation of Output Tables against ADaM |
Steve Ross |
source
presentation source |
5 |
| PHUSE US |
2024 |
Organisational Considerations When Replacing or Adding a New Software Language |
Brian K. Varney |
source
presentation source |
4 |
| PHUSE US |
2024 |
Post-Pandemic Trends in Study Designs |
Charumathy Sreeraman,
Jisha George |
source
presentation source |
7 |
| PHUSE US |
2024 |
Programming Approaches for Integrated Summary of Efficacy (ISE) Development in Oncology |
Narendra Babu Kolisetty,
Saigovind Chenna |
source
presentation source |
7 |
| PHUSE US |
2024 |
Real-Time Data Cleaning -- A Reality: When Automation Connects Digitised, Centralised, Standardised Data, it Transforms into Real-Time Data Cleaning |
Vidya Muthukumar |
source
poster source |
2 |
| PHUSE US |
2024 |
Redefining 'Interactive' Dashboards to Enhance Safety Data Review |
Andrew McGowan |
source
presentation source |
7 |
| PHUSE US |
2024 |
Revolutionising Informed Consent Form Analysis with Generative AI: Enhancing Efficiency in Drug Development and Data Re-Use |
Hangyu (Cedric) Liu |
source
presentation source |
11 |
| PHUSE US |
2024 |
Revolutionize Clinical Trial Data Exploration with teal |
Chendi Liao,
Dony Unardi |
source
presentation source |
6 |
| PHUSE US |
2024 |
Risk-Based Monitoring Using AI/ML Detection of Systematic Bias in Clinical Data |
Kostiantyn Drach,
Sergey Glushakov |
source
presentation source |
12 |
| PHUSE US |
2024 |
SDTM/ADaM Automation - Challenges and Issues from a Programmer's Perspective While Exploring an Automation Attempt to Address Them |
Alistair D-Souza |
source
presentation source |
6 |
| PHUSE US |
2024 |
Software Product Lines Framework: How to Manage End-to-End Metadata-Driven Automation at Sale |
Stuart Malcolm |
source
poster source |
5 |
| PHUSE US |
2024 |
Sowing Seeds of Inspiration: Letters to a Pre-Scientist |
Julie Ann Hood |
source
poster source |
3 |
| PHUSE US |
2024 |
SPACE - GSK Biostatistics continues its journey to a new frontier |
Eileen Ching |
source
presentation source |
9 |
| PHUSE US |
2024 |
Statistical Monitoring Report: A Path Forward to Interactive Data Analysis and Quantitative Decision-Making |
Debopriya Ghosh |
source
presentation source |
3 |
| PHUSE US |
2024 |
Synergising Large Language Models (LLMs) and Human-in-the-Loop (HITL) for Data Noise Reduction in the RBQM Approach |
Mukesh Babu,
Vineet Jain |
source
presentation source |
7 |
| PHUSE US |
2024 |
Teal as an Open-Source Tool Accelerates Clinical Trial Data Research at GSK |
Jeffrey Long |
source
presentation source |
7 |
| PHUSE US |
2024 |
Teal.builder: A Multifaceted Teal App Builder for Clinical Data Exploration and Reporting |
Freeman Wang,
Andre Couturier |
source
presentation source |
5 |
| PHUSE US |
2024 |
The Knowledge Graph - The Power of an Information Network driving Biometric workflows |
Nekzad Shroff,
Jaya Simha Inampudi |
source
presentation source |
3 |
| PHUSE US |
2024 |
The Potential Power of Data |
Eva Kelty,
Catharina Dahlbo |
source
presentation source |
5 |
| PHUSE US |
2024 |
The Role of FHIR Resources in Testing and Validating an EHR to a Sponsor Data Pipeline |
Patrick Genyn,
Andy Richardson |
source
presentation source |
6 |
| PHUSE US |
2024 |
The TransCelerate/CDISC Digital Data Flow Project: Practical Electronic Study Designs [presentation] |
David Iberson-Hurst |
source |
28 |
| PHUSE US |
2024 |
Transformative Strategies in People Leadership and Management for Organisational Success |
Bhanojinaidu Duppada,
Sumanth Goud Bheemagani |
source
presentation source |
8 |
| PHUSE US |
2024 |
Translating Data into Tableau Insights: Bridging the Gap Between Programmers and Medical Physicians |
Agnieszka Bel |
source
presentation source |
7 |
| PHUSE US |
2024 |
Unlocking the Future of Tables with the {tfrmt} R Package |
Becca Krouse |
source
presentation source |
8 |
| PHUSE US |
2024 |
Ups, Downs, and FDA Crowns - Lessons Learned from BIMO Submission Adventures! [presentation] |
Sushant Thakare |
source |
21 |
| PHUSE US |
2024 |
Usage of OMOP-CDM along with CDISC in Clinical Trials: Challenges and Opportunities |
Parag Shiralkar |
source
presentation source |
5 |
| PHUSE US |
2024 |
Validation Unveiled: Striking the Balance for Data Integrity and Compliance in R, Python, and SAS |
Sy J. Truong |
source
presentation source |
10 |
| PHUSE US |
2024 |
{admiral} - From Open Source Through to Company Implementation |
Ross Farrugia |
source
presentation source |
4 |
| PHUSE EU |
2023 |
A Beginner's Guide to Overcome the Attrition Bias in Clinical Research: The Method of Inverse Probability of Attrition Weighting (IPAW) |
Parichay Srivastava |
source
presentation source |
9 |
| PHUSE EU |
2023 |
A Data Lake is not a CDR and a CDR is not a Data Lake... Understanding the Differences and the Value of Each |
Chris Decker |
source
presentation source |
5 |
| PHUSE EU |
2023 |
A Dive Into the World of Biomedical Concepts |
Berber Snoeijer |
source
presentation source |
5 |
| PHUSE EU |
2023 |
A new standard of excellence; introducing the annotated Screen Report |
Franklin E. Menius |
source
presentation source |
8 |
| PHUSE EU |
2023 |
A Privacy Methodology Toolkit to Improve Cross-Industry Clinical Data Reuse |
Boris Grimm,
Diana Ye |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Advanced Analytics for Data Quality Assessment in Countries and Regions Affected by Crisis |
Archana Nayak,
Mohammad Umarfaruque |
source
presentation source |
13 |
| PHUSE EU |
2023 |
An Experience of Creating Questionnaire ADaMs Using the Admiral ADQS Package |
Luke Thompson,
David L. Ward |
source
presentation source |
4 |
| PHUSE EU |
2023 |
Analytical Risk-Based Monitoring (ARBM) - How Central Monitors Detect the Ripple in the Dataflow that Hides Danger On Site |
Juergen Zech |
source
presentation source |
4 |
| PHUSE EU |
2023 |
Applying Central Statistical Monitoring to Find Anomalies and Address Quality Issues in Clinical Trial Data |
Wiktor Majewski |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Automated Pipelines for Non-CRF Value Level Metadata, A Meta-programming Approach |
Selena Baset,
Philipp Ernst,
Didier Clément |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Avoid Major Pitfalls When Using Real-World Evidence (RWE) in Regulatory Submissions |
Alex Ide,
Mark Lambrecht |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Be Future-Minded While Designing Your Next Generation SCE |
Susanne M. Andersen,
Olivier Bouchard |
source
presentation source |
12 |
| PHUSE EU |
2023 |
Becoming an Integrated Part of the Open-Source Pharma Community |
Philip Bowsher |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Boosting SAS Programming Efficiency with ChatGPT: A Clinical Trials Perspective |
Illia Skliar |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Building a Large-Scale Clinical Trial's IT System with In-House Software and OpenClinica |
Sonja Grotjahn,
Allen Young |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Building an integrated pre-clinical and clinical data platform to enable rapid translational data review |
Brenda Finney,
Ali Dootson Instem |
source
presentation source |
12 |
| PHUSE EU |
2023 |
CDISC Conformance Rules and the CORE Engine: Continuing the Road to Adoption |
Nick De Donder |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Challenges in Oncology Modular studies: The Fortrea approach |
Francesca Dall'Acqua |
source
presentation source |
7 |
| PHUSE EU |
2023 |
CodeGeneration: Turning Metadata into SAS, R or Python |
Stuart Malcolm |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Comparing Analysis Method Implementations in Software (CAMIS): An Open Source Repository to Document Differences in Statistical Methodology Across Software |
Christina Fillmore |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Comparison of power between different recurrent events analysis methods using simulation |
Soumitra Kar |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Creating CORE Rules from Biomedical Concepts |
Johannes Ulander |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Data Managers and R Programming: The Unlikely Pair |
Anaelle Perretti (Bonetta) |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Detroit, Michigan: A Case Study for DEI Via Decentralised Clinical Trials (DCTs) |
Mark Rothe |
source
presentation source |
26 |
| PHUSE EU |
2023 |
Development Safety Update Report (DSUR)/Periodic Safety Update Report (PSUR) |
Phillip Spowart |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Drafting Your Plain Language Summaries: Hurdles to Overcome and How to Overcome Them |
Eliza Gray |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Driving Better Health for More People - SAS Life Science Analytics |
William Kuan,
Olivier Bouchard |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Efficacy Analyses with Imputations: Methods, Limitations and Lessons Learned |
Amine Khemiri |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Efficacy Endpoints in Adjuvant and Neo-Adjuvant Oncology Trials |
Yuliia (Piddubna) Cherednichenko,
Anna Amosova |
source
presentation source |
15 |
| PHUSE EU |
2023 |
Empowering Paediatric Drug Development: CDISC Standards and ICH Guidelines for Clinical Trials with Little Participants |
Ninan Luke |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Experiencing the FDA CBER |
Merve Akram,
Angelo Tinazzi |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Exploring Antidepressant Side Effects in the UK Through Topic Modelling and Social Media Analysis |
Khalid Ismail,
Amna Dridi |
source
presentation source |
13 |
| PHUSE EU |
2023 |
Figures are Basic(ally Overlooked) |
Kaleb Mead |
source
poster source |
17 |
| PHUSE EU |
2023 |
Gear Up SDTM with Digital Health Devices |
Vicky Poulsen |
source
presentation source |
5 |
| PHUSE EU |
2023 |
GPT (Generative Pretrained Transformers) and LLM (Large Language Models) have generated a lot of attention since their inception in early 2023 with the advent of OpenAI GPT3.5, then GPT4.0 |
Jerome Vetillard,
Mark Lambrecht |
source
presentation source |
16 |
| PHUSE EU |
2023 |
Guidance on SDTM for Liquid Oncology Endpoints [poster] |
Swaroop Koduri,
Tyagrajan Swaminathan |
source |
1 |
| PHUSE EU |
2023 |
H2H Portal - A Shiny Automation of Reproducible and Traceable Analysis and Reporting Using a Metadata Framework |
Julian Schmocker,
Qian Wang |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Harmonising Clinical Reporting Through the {falcon} Initiative: A Collaborative Leap Forward |
Jürgen Böhl,
Vincent Shen |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Human BioGeography: predicting clinical trials outcome using a 3D human body simulation with a GIS framework |
Diego Caso,
Rocio Matesanz Sanchez,
PhD Student |
source
presentation source |
6 |
| PHUSE EU |
2023 |
ICH M11 Clinical Electronic Structured Harmonized Protocol (CeSHarP) and CDISC: Making the Electronic Protocol a Reality [presentation] |
John Owen,
Peter Van Reusel |
source |
33 |
| PHUSE EU |
2023 |
Improving Clinical Operational Insights Delivery to different Levels of Leadership Seniority Using Shiny-Based Automation |
Peyman Eshghi,
Jose-Felipe Golib-Dzib |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Increasing Trend of Biomarker Analysis in Clinical Trials |
Anjali Ranga |
source
presentation source |
11 |
| PHUSE EU |
2023 |
InnerSource: A Stepping Stone Towards Open Source in Statistical Programming |
Jeppe Juul |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Integrating Isolated Clinical Trial Systems with RESTful APIs: Enhancing Data Accessibility and Collaboration |
Sumesh Kalappurakal,
Nicolas Dupuis |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Integrating Privacy By Design to Enable Innovative Clinical Trials and Post-Trial Data Sharing |
Muhammad Oneeb Rehman Mian |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Knowledge Graphs for Clinical Trials |
Eva Kelty,
Anders Högberg |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Leveraging Real-World Data to Provide Deeper Insight into Treatment Effects in Clinical Trials |
Soundarya Palanisamy,
Sherrine Eid |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Mastering the Art of Adaptation: Innovative Strategies for Effective Change Management |
Mark Bynens |
source
presentation source |
13 |
| PHUSE EU |
2023 |
MINT+ Automation and Digitization of SDTM specification |
Magdalena Krochmal |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Mr. ight - Why R Should Be Used for Validating TLFs in Clinical Trials? |
Monika Ludwinska |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Oak Garden - Metadata-Driven SDTM Automation in R |
Magdalena Krochmal,
Amy Franklin |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Optimizing Clinical Trial Design with Real-Time Sample Size Calculation and Enrollment Projection: A Shiny Dashboard Solution |
Dony Sabu |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Oversight and Insight within a Fast-Moving Biotech Company |
Stijn Rogiers,
Isabelle Vandriessche |
source
presentation source |
15 |
| PHUSE EU |
2023 |
Patient Profiles v2.0: Easy and Quick Clinical Trial Insights in Tableau |
Roman Radelicki,
Annelies Van Zeveren |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Quality Tolerance Limits - More Critical Aspects of Clinical Trials with Much Less Visibility |
Saritha Chamarthi,
Mahesh Balagonda |
source
presentation source |
2 |
| PHUSE EU |
2023 |
R Validation: Getting Started |
Christian S. Christensen |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Real world observational studies and the challenges in data collection |
Kavitha Devadiga |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Real-Time Safety and Medical Review by Integrating Data Visualisations with an SCE |
Shivoy Pandita,
Santhoshi Madeswaran |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Regulating the Future: Navigating the Complexities of 3D Printing in the Pharmaceutical Industry |
Burger Lubbe |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Revolutionising Data Exploration: An Interactive Journey Through R Shiny [presentation] |
Valentin Legras |
source |
30 |
| PHUSE EU |
2023 |
Risk-Based Monitoring in Clinical Trials with Machine-Learning-Powered Anomaly Detection |
Zaid Al-Jubouri,
Ece Kavalci |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Road to Rome or Roaming - A Reprise [presentation] |
Francis Kendall,
Christian Mueller |
source |
32 |
| PHUSE EU |
2023 |
Same Same but Different: Leveraging R for Comparing Clinical Study |
TLF Versions |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Size matters - sample size calculation with SAS and R |
Fenja Seither |
source
presentation source |
4 |
| PHUSE EU |
2023 |
Statistical Programming 101 for the Fourth Industrial Revolution |
Ritika Aggarwal |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Stay Ahead of the Curve: Learn About Leapfrogging as a Statistical Programmer |
Jitendra Singh,
Kavita Dargan |
source
presentation source |
4 |
| PHUSE EU |
2023 |
Streamlining Clinical Data Analysis and Reporting with R: Best Practices, Tips and Techniques for Efficient Workflow Management and Code Optimisation |
Vaibhavi Govind Bhide,
Perry Meeks |
source
presentation source |
12 |
| PHUSE EU |
2023 |
Submission Standards for Real-World Data: Gaps, Limitations and Recommendations |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
8 |
| PHUSE EU |
2023 |
TFL Designer: Automating Tables, Figures and Listings Design and Generation for Clinical Trial Analysis [presentation] |
Bhavin Busa |
source |
10 |
| PHUSE EU |
2023 |
The Curious Case of Observational Studies - A Programmer's Dilemma |
Vikas Shokeen |
source
presentation source |
11 |
| PHUSE EU |
2023 |
The Digital Protocol Is Just the Beginning. Or Is It? [presentation] |
Thierry Philippe,
Bill Qubeck |
source |
17 |
| PHUSE EU |
2023 |
The Evolving Role of Statistical Programmers in the Pharmaceutical Industry: The Impact of Artificial Intelligence |
Cindy Marabotti |
source
poster source |
8 |
| PHUSE EU |
2023 |
The role of FHIR Resources in ensuring Semantic Equivalence in EHR2EDC direct data capture |
Patrick Genyn |
source
presentation source |
4 |
| PHUSE EU |
2023 |
The TransCelerate/CDISC Digital Data Flow Project: Practical Electronic Study Designs [presentation] |
David Iberson-Hurst |
source |
28 |
| PHUSE EU |
2023 |
Unleashing the Role of a Statistical Programmer in Expediting a Submission, Novartis |
Sowmya Singuluri |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Visualising Your Protocol Objectives |
Varun Tripuraneni |
source
presentation source |
6 |
| WUSS |
2023 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| WUSS |
2023 |
Blinding Indexes - Generalized and Unified Framework - a SAS Macro |
Eduard Poltavskiy,
Rima Nandi,
Jeehyoung Kim,
Heejung Bang |
source |
10 |
| WUSS |
2023 |
Demystifying the define.xml: Overcoming the challenges of CRT Package. |
Yoganand Budumuru |
source |
10 |
| WUSS |
2023 |
Generation of AE (Adverse Events) summary tables by worst CTC Grade utilizing SAS |
Ballari Sen |
source |
14 |
| WUSS |
2023 |
How to Understand Therapeutic Area User Guide for Reactogenicity Events in Vaccine Studies |
Yanwei Han |
source |
9 |
| WUSS |
2023 |
Navigating SAS and CDISC Certification with Apprenticeship |
Sarvar Khamidov |
source |
7 |
| WUSS |
2023 |
Quality Control - Defining an Acceptable Quality Standard without Achieving Perfection |
Bill Coar |
source |
9 |
| WUSS |
2023 |
Visualizing Insights, Empowering Discoveries: SAS Viya Unleashed in Life Science Analytics |
Matthew J. Becker |
source |
13 |
| WUSS |
2023 |
Waterfall vis a vis Spider plots: Complex oncology efficacy endpoint made simpler. |
Yoganand Budumuru |
source |
21 |
| SESUG |
2023 |
An Innovative Approach to Generate a CONSORT Diagram in Clinical Trials |
Lydia Li,
Shunbing Zhao |
source |
6 |
| SESUG |
2023 |
For Clinical Trials: A Faster and Smoother Approach to Create your SDTM and ADAM Define Specifications for Define.xml with SAS |
Star Nze |
source |
29 |
| SESUG |
2023 |
Generate and Customize eDISH Plot to Identify Hy's Law Cases in Simple Steps |
Jeetender Chauhan,
Sarad Nepal,
Madhusudhan Ginnaram |
source |
10 |
| SESUG |
2023 |
SAS Macro for Randomization-Based Methods for Covariance and Stratified Adjustment of Win Ratios and Win Odds for Ordinal Outcomes |
Elaine Kowalewski,
Ann Marie K. Weideman,
Gary G. Koch |
source |
11 |
| PharmaSUG |
2023 |
'TUFF' LOVE: SDTM Pain Points Explained! |
Kristin Kelly,
Michael Beers |
source |
12 |
| PharmaSUG |
2023 |
A Macro Utility for CDISC Datasets Cross Checking |
Chao Su,
Jaime Yan,
Changhong Shi |
source |
9 |
| PharmaSUG |
2023 |
A model for sponsors to support independent operation of IDMCs in clinical trials. |
Bhanu Bayatapalli,
Yiyi Chen |
source |
8 |
| PharmaSUG |
2023 |
A utility to combine study outputs into all-in-one PDF for DSUR |
Wei Shao |
source |
8 |
| PharmaSUG |
2023 |
ADaM Design and Programming Standardization for Oncology Efficacy Endpoints Based on RECIST 1.1 |
Ellen (Zihui) Lin,
Matt Ness,
Yinghui Wang |
source |
9 |
| PharmaSUG |
2023 |
Adopting the New Integrated Analysis Data Reviewer-s Guide (iADRG) |
Randi Olsen McFarland,
Srinivas Kovvuri,
Kiran Kumar Kundarapu,
Satheesh Avvaru |
source |
11 |
| PharmaSUG |
2023 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| PharmaSUG |
2023 |
Application of Tipping Point Analysis in Clinical Trials using the Multiple Imputation Procedure in SAS |
Yunxia Sui,
Xianwei Bu,
Yuanyuan Duan,
Yihan Li,
Xin Wang |
source |
12 |
| PharmaSUG |
2023 |
Are you a great team player? |
Daryna Yaremchuk |
source |
8 |
| PharmaSUG |
2023 |
Automation of the SDSP CBER Appendix for Vaccine Studies |
Nicole Jones,
Pritesh Solanki |
source |
6 |
| PharmaSUG |
2023 |
Be a Lazy Validator - Let Your Code Do the Work |
Cara Lacson,
Ray de la Rosa,
Carol Matthews |
source |
17 |
| PharmaSUG |
2023 |
BIMO Package: Challenges and Perspectives while keeping up with the upgrades in the BIMO Technical Conformance Guide and the BDRG Guidelines |
Mathura P. Ramanathan,
Sowmya Gabbula |
source |
18 |
| PharmaSUG |
2023 |
Building an Internal R Package for Statistical Analysis and Reporting in Clinical Trials: A SAS User-s Perspective |
Huei-Ling Chen,
Heng Zhou,
Nan Xiao |
source |
11 |
| PharmaSUG |
2023 |
Can We Do It Better? Real-Time Validation Of Sdtm Mapping Is Superior To Double Programming |
Daniel Rolo,
Bremer Louw |
source |
9 |
| PharmaSUG |
2023 |
CDISC Conformance and Compliance: So Many Resources, So Little Time! |
Jennifer K. Fulton,
Stephen Black |
source |
11 |
| PharmaSUG |
2023 |
Data Doesn't Lie - Real Time Monitoring and Projecting on Clinical Trial Enrollment Progression |
Wenjun He |
source |
5 |
| PharmaSUG |
2023 |
Deep Learning to Classify Adverse Events from Patient Narratives |
Tom Sabo,
Sundaresh Sankaran,
Qais Hatim |
source |
11 |
| PharmaSUG |
2023 |
Digital Data Flow (DDF) and Technological Solution Providers |
Prasoon Sangwan,
Piyush K. Singh |
source |
8 |
| PharmaSUG |
2023 |
Do's and Don'ts of Being an Independent Consultant |
Raymond Lee |
source |
13 |
| PharmaSUG |
2023 |
FDA's Study Data Policy Framework and How CDISC Properties Are Evaluated for Inclusion |
Helena Sviglin |
source |
20 |
| PharmaSUG |
2023 |
Gear up the Metadata - Automating Patient Profile Generation, a Metadata Driven Programming Approach |
Tanmay Khole,
Aman Sharma,
Lili Li,
Durga Prasad Chinthapalli |
source |
20 |
| PharmaSUG |
2023 |
Guidelines for the Statistical Analysis in German Dossier Submissions |
Meiling Gao,
Xi Qian,
Hui Mao |
source |
8 |
| PharmaSUG |
2023 |
Handling CRS/NT Data in CAR-T Studies and Submission |
Joe Xi,
Yuanyuan Liu,
Lorraine Fang |
source |
7 |
| PharmaSUG |
2023 |
Hard Coding: What is it? Why Does It Matter? What Should You Do When Faced With Such A Request? |
Michael Nessly |
source |
4 |
| PharmaSUG |
2023 |
Have Meaningful Relationships: An Example of Implementing SDTM Special Purpose Data Set RELREC with a Many-to-Many Relationship |
Kaleigh Ragan,
Richann J. Watson |
source |
11 |
| PharmaSUG |
2023 |
How Can I Put This? - Using a pre-defined spreadsheet to explain your Pinnacle 21 Enterprise Issues |
Mike Lozano |
source |
12 |
| PharmaSUG |
2023 |
Integrating Practices: How Statistical Programmers Differ and Align Within User Groups |
Valeria Duran,
Radhika Etikala,
Haimavati Rammohan |
source |
15 |
| PharmaSUG |
2023 |
Let the Data Drive it and set your hands free - A Macro to create indicators for Special Interest AEs |
Yiwei Liu,
Jameson Cai |
source |
6 |
| PharmaSUG |
2023 |
Life Table Analysis for Time to First Event Onset |
Abhinav Srivastva |
source |
11 |
| PharmaSUG |
2023 |
Macro To Automate Crossover Review In Produced Outputs |
Igor Goldfarb,
Ella Zelichonok |
source |
25 |
| PharmaSUG |
2023 |
Making Multilingual Programmers - A Targeted Approach to R for Clinical Trials Training |
Jagan Mohan Achi,
Ashley Tarasiewicz |
source |
5 |
| PharmaSUG |
2023 |
Masters of the Table Universe: Creating Table Shells Consistently and Efficiently Across All Studies |
Michael Hagendoorn,
Ran Li,
Mimi Vigil,
Shan Yang |
source |
15 |
| PharmaSUG |
2023 |
Metaverse in the Healthcare - More Real than imagined! |
Aman Bahl |
source |
14 |
| PharmaSUG |
2023 |
Novel Applications of Real World Data in Clinical Trial Operations: Clinical Trial Feasibility |
Sherrine Eid,
Samiul Haque,
S. Robert Collins |
source |
13 |
| PharmaSUG |
2023 |
Novel Applications of Real World Data in Clinical Trials: External Control Arms |
Sherrine Eid,
Samiul Haque,
S. Robert Collins |
source |
6 |
| PharmaSUG |
2023 |
Patient's Journey using Real World Data and its Advanced Analytics |
Kevin Lee |
source |
4 |
| PharmaSUG |
2023 |
PHUSE Safety Analytics Working Group - Overview and Deliverables Update |
Nancy Brucken,
Clio Wu,
Mary Nilsson,
Greg Ball |
source |
5 |
| PharmaSUG |
2023 |
Programmer-s Perspective: Step into Awareness Regarding Clinical Trial Deliverables and Their Impact |
Lyma Faroz,
Jinit Mistry |
source |
10 |
| PharmaSUG |
2023 |
Pros and Cons of Freelancing |
Pradeep Bangalore |
source |
10 |
| PharmaSUG |
2023 |
R Package Qualification: Automation and Documentation in a Regulated Environment |
Paul Bernecki,
Nicole Jones,
Uday Preetham Palukuru,
Abhilash Chimbirithy |
source |
16 |
| PharmaSUG |
2023 |
R Package Quality & Validation: Current Landscape |
Philip Bowsher |
source |
9 |
| PharmaSUG |
2023 |
Real Time Analytical Reporting Using OpenFDA |
Shubhranshu Dutta |
source |
8 |
| PharmaSUG |
2023 |
Recent updates in BIMO Technical conformance guidance and use case scenario |
Vaibhav Garg,
Sreedhar Bodepudi |
source |
4 |
| PharmaSUG |
2023 |
Regulatory Data Submission and CDISC Compliance: Sponsor and Vendor Collaboration Best Practices |
Tabassum Ambia |
source |
5 |
| PharmaSUG |
2023 |
Revolutionizing Statistical Outputs Validation: a Product Demonstration of Verify, an ML-powered Automation Solution Streamlining the Validation Process |
Ilan Carmeli |
source |
11 |
| PharmaSUG |
2023 |
SAS Macro to Automate Programmer Status Sheet |
Jake Adler,
Denise Rossi,
Assir Abushouk |
source |
5 |
| PharmaSUG |
2023 |
SAS System Macros to Summarize the COMPARE Procedure Results and SAS Logs for a Directory or Single File. |
Kevin R. Viel |
source |
41 |
| PharmaSUG |
2023 |
SAS-based Method for PK Noncompartmental Analysis and Validation |
Hui Mao,
Lixin Gao |
source |
5 |
| PharmaSUG |
2023 |
SDTM Variables You Might Forget About |
Nadiia Pukhliar,
Dariia Tsyhanenko,
Iryna Kotenko |
source |
10 |
| PharmaSUG |
2023 |
Sensitivity Analysis for Missing Data Using Control-based Pattern Imputation |
Jun Feng,
Jingmin Liu |
source |
7 |
| PharmaSUG |
2023 |
Shifting the drug development paradigm with Adaptive Design and master protocol |
Aman Bahl |
source |
16 |
| PharmaSUG |
2023 |
Standardization of Reactogenicity Data into Findings |
Charumathy Sreeraman |
source |
9 |
| PharmaSUG |
2023 |
Standardized data handling framework for wearables |
Madhu Annamalai,
Umayal Annamalai |
source |
4 |
| PharmaSUG |
2023 |
Statistical Considerations and Methods for Handling Missing Outcome Data in Clinical Trials During the Era of COVID-19 |
Xi Qian,
Chengfei Lu |
source |
11 |
| PharmaSUG |
2023 |
Study Data Technical Rejection Criteria (TRC) Considerations for Multiple Data Packages in a Single Submission |
Christine S Teng,
Janet Low,
Si Ru Tang |
source |
10 |
| PharmaSUG |
2023 |
The Flexible Ways to Create Graphs for Clinical Trial |
Hong (Lily) Zhang,
Kaijun Zhang |
source |
11 |
| PharmaSUG |
2023 |
The Phantom of the ADaM: adding missing records to BDS datasets |
Anastasiia Drach |
source |
10 |
| PharmaSUG |
2023 |
Tips and traps on how to efficiently accelerate clinical trials to successful submission, approval, and launch |
Michael Nessly |
source |
5 |
| PharmaSUG |
2023 |
Traceability: Not just about Data |
Rohit Nagpal,
Kavitha Mullela |
source |
11 |
| PharmaSUG |
2023 |
Using R to Automate Clinical Trial Data Quality Review |
Melanie Hullings,
Emily Murphy,
Derek Lawrence,
Michelle Cohen,
Andrew Burd |
source |
6 |
| PharmaSUG |
2023 |
Validating novel maraca plots - R and SAS love story |
Nicole Major,
Srivathsa Ravikiran,
Monika Huhn,
Samvel Gasparyan,
Martin Karpefors |
source |
17 |
| PharmaSUG |
2023 |
What-s the F in specialized people? Let-s talk FSP - the models, variations, and what it takes to be successful |
Kathy Bradrick,
Ershlena McDaniel,
Lisa Stetler |
source |
5 |
| PharmaSUG |
2023 |
What-s the story in your subgroup analysis |
Lucy Dai |
source |
6 |
| PharmaSUG |
2023 |
Why FDA Medical Queries (FMQs) for Adverse Events of Special Interest? Implementation and Case Study |
Clio Wu |
source |
12 |
| PharmaSUG |
2023 |
You can REST easy validating Synthetic Data |
Ben Howell,
Ben E. Bocchicchio |
source |
9 |
| PHUSE US |
2023 |
A Beginner's Roadmap to Map Functions for Clinical Reporting in R |
Samuel Curlee,
Gabriela Piasecki |
source
presentation source |
6 |
| PHUSE US |
2023 |
A Pragmatic Approach to Data Cleaning - Decisions in Selecting When to Apply AI/ML [presentation] |
Robert Musterer,
Alison Banda |
source |
15 |
| PHUSE US |
2023 |
A Programmer's Point of View of Current and Future PD Detection T ools |
Meng Li |
source
presentation source |
6 |
| PHUSE US |
2023 |
A Road Map to Standardise Historical Clinical Trials for Synthetic Control Arm [presentation] |
Bhargav Koduru,
Corinne Ahlberg |
source
video |
16 |
| PHUSE US |
2023 |
A TransCelerate Initiative: Paving the Way for the Adoption of Modernized Statistical Analytics [presentation] |
Nicholas Masel |
source |
12 |
| PHUSE US |
2023 |
ADaM Planning Tool: A Web-Based Application to Collect, Create and Maintain ADaM Metadata in Clinical Trials [presentation] |
Lucky Singh,
Asavari Mehta |
source
video |
32 |
| PHUSE US |
2023 |
An Open-Sourced R Package for Streamlining Generation of Standard TLFs in Both Static and Interactive Formats [presentation] |
Lena Wang,
Heng Wang |
source
video |
25 |
| PHUSE US |
2023 |
Approachable and Scalable Web Application Solutions Using Shiny for Python and R Shiny in the Pharmaceutical Industry |
Vikash Jain,
Denny Sebastian |
source
presentation source |
9 |
| PHUSE US |
2023 |
Automating SDTM and ADaM Creation in Clinical Trials |
Lyubov Sushchenko,
Rie Ichihashi |
source
presentation source |
9 |
| PHUSE US |
2023 |
Automation of ADaM Dataset & TFL Visualization Through an R Package - GenAdam2 |
Mahesh Divakaran |
source
presentation source |
5 |
| PHUSE US |
2023 |
Balance Between Humans and Machines - How NLP Helps Translate Text Specification to Code, and Vice Versa |
Hao (Harry) Chen,
Jaimin Patel |
source
presentation source |
9 |
| PHUSE US |
2023 |
Best Practice for Successful Adoption and Implementation of CDISC Data Standards [presentation] |
Gilbert Hunter,
Martin Johnston |
source
video |
25 |
| PHUSE US |
2023 |
Beyond k-anonymity for Clinical Trial Data Anonymisation [presentation] |
Parvee Kumar,
Diwakar Angra |
source
video |
17 |
| PHUSE US |
2023 |
Big Pharma Acquires Biotech - Perceptions from The Clinical Data Scientists' Point of View |
Jonas Poulsson,
Henning Pontoppidan Föh |
source
presentation source |
10 |
| PHUSE US |
2023 |
Build vs Buy for SCE: Considerations for the Future of the Statistical Computing Environment (SCE) [presentation] |
Nathan Johnson,
Alison Banda |
source
video |
20 |
| PHUSE US |
2023 |
CDISC CORE - Milestones, Status and Roadmap |
Peter Van Reusel |
source
presentation source |
9 |
| PHUSE US |
2023 |
Challenges of Handling Vaccines Serology Data for Analysis and Reporting [presentation] |
Saritha Dhanasri,
Helen Yang |
source
video |
17 |
| PHUSE US |
2023 |
Cybernated Validation of Clinical Reports (TLs) |
Giri Balasubramanian,
Gopinath Viswanathan |
source |
9 |
| PHUSE US |
2023 |
Database Tools Needed for Personalised Study Participant Risk Surveillance |
Martin Bauwens |
source
presentation source |
5 |
| PHUSE US |
2023 |
Digging Deep into Digital Biomarkers: Empowering Clinical Trials |
Vijay Pasapula,
Gianna Huang |
source
presentation source |
12 |
| PHUSE US |
2023 |
DV-04 |
Unifying RECIST |
source
presentation source |
5 |
| PHUSE US |
2023 |
EDC Raw Data to SDTM Curation, Mapping and Automation with XBiom Tool |
Sunil Kumar Gupta,
Rahul Madhavan |
source
presentation source |
7 |
| PHUSE US |
2023 |
Enabling Comprehensive Interactive Data Analysis and Exploration in R with an Open-Sourced, Scalable Shiny Framework [presentation] |
Dony Unardi,
Chendi Liao |
source
video |
17 |
| PHUSE US |
2023 |
FORESTLY - An R Package to Generate Interactive Forest Plots |
Bingjun Wang,
Yilong Zhang |
source
presentation source |
14 |
| PHUSE US |
2023 |
Future Workforce: How to invest in your team through Innovative transformation |
Limna Salim |
source
presentation source |
8 |
| PHUSE US |
2023 |
Handling Multiple Adaptations in One Clinical Trial |
Parvee Kumar,
Shrutimita Pokhariyal |
source
presentation source |
6 |
| PHUSE US |
2023 |
Helping You Get in the Lightning Lane for a Wild Submissions Ride! [presentation] |
Ali Dootson |
source
video |
20 |
| PHUSE US |
2023 |
How to Customize Survival Curves in R and Add Interactivity |
Oleksandr Babych |
source
presentation source |
9 |
| PHUSE US |
2023 |
Innovate Clinical Trial Reporting with Open Source |
Soma Sekhar Sriadibhatla,
Francis Kendall |
source
presentation source |
4 |
| PHUSE US |
2023 |
Interactive Data Visualisation: A Tool for Common Clinical Study Figures and SAP Figure Shells |
Ji Qi,
Qisen Luan |
source
presentation source |
10 |
| PHUSE US |
2023 |
Introduction to Machine Learning Models, How to Train Them and What to Do if They Become Sassy [presentation] |
Thomas Kalfas |
source |
34 |
| PHUSE US |
2023 |
Learnings from an External Comparator Study Based on Real-World Data (RWD) / Real-World Evidence (RWE) in T-Cell Therapy for Solid Tumors |
Rabia Ahmad |
source
presentation source |
6 |
| PHUSE US |
2023 |
Leveraging Big Data in Real-World Evidence Generation: Data Engineering Challenges and Possibilities |
Samiul Haque,
S. Robert Collins |
source
presentation source |
6 |
| PHUSE US |
2023 |
Managing Deliverables in Oncology Basket Trials |
Hong Qi,
Mary N. Varughese |
source
presentation source |
6 |
| PHUSE US |
2023 |
Master Protocol Design: Advantages and Challenges in Vaccine Clinical Trials [presentation] |
Janaki Shankaran,
Meenal Gawas |
source
video |
19 |
| PHUSE US |
2023 |
More than Mandates: RBM Today and Why It Matters, Beyond the Guidance [presentation] |
Jason Konn,
Alison Banda |
source
video |
14 |
| PHUSE US |
2023 |
Parametric Event-prediction for Time-to-event Data in Clinical Trials [presentation] |
Jingyuan Chen,
Weijie Zhang |
source
video |
22 |
| PHUSE US |
2023 |
Patient Narratives (with R) [poster] |
Vahe Martirosyan,
Lilit Torosyan |
source |
1 |
| PHUSE US |
2023 |
Performing Propensity-score-integrated Comparative Analysis in External Control Arm Studies Using R [presentation] |
Lixiao Chen,
Lorraine Fang |
source
video |
20 |
| PHUSE US |
2023 |
PHUSE Safety Analytics Working Group - Overview and Summary of Ongoing Projects [poster] |
Clio Wu,
Mary Nilsson |
source |
1 |
| PHUSE US |
2023 |
Recasting Trial Designs with Digital Endpoints: A SWOT Analysis |
Kishore Shyamala |
source
presentation source |
7 |
| PHUSE US |
2023 |
Recommender System for Study Build: Using the Protocol to Select CRFs from Standard Libraries |
Komal Govil,
Karan Pande |
source
presentation source |
4 |
| PHUSE US |
2023 |
Reducing Rate of False Positives Risk Signals with Risk Management Strategy |
Vera Pomerantseva |
source
presentation source |
5 |
| PHUSE US |
2023 |
Reviewing External Vendor Data Transfer Specifications from a Programming Standpoint |
Mahesh Minnakanti |
source
presentation source |
5 |
| PHUSE US |
2023 |
SAS Macro for Converting Variable Attributes from XLSX Specifications to SDTM/ADAM SAS data sets |
Jinquan Wu |
source
presentation source |
8 |
| PHUSE US |
2023 |
Scrutinize Tables Listings Figures (TLFs) Prior to Customer Delivery |
Vijetha Kode |
source
presentation source |
6 |
| PHUSE US |
2023 |
SDTM Mapping Recommendation Engine - Acorn [presentation] |
Rohan Parmar,
Harshit Manektalia |
source
video |
32 |
| PHUSE US |
2023 |
Standardizing SDTM Laboratory (LB) Programming |
Murali Marneni,
Stephanie Olexovitch |
source
presentation source |
8 |
| PHUSE US |
2023 |
Staying Alert to Data Quality: A Shiny App to Visualise the Electronic Patient Reported Outcome (ePRO) Data |
Wenyi Liu |
source
presentation source |
6 |
| PHUSE US |
2023 |
Structured Protocol Authoring (SPA) - A Catalyst for Clinical Protocol Development |
Suhas Giriraj |
source
presentation source |
4 |
| PHUSE US |
2023 |
The Evolving Role of Project Programmer in The Next 3-5 Years |
Vinay Gupta,
Manas Rout |
source |
5 |
| PHUSE US |
2023 |
Tidytlg: An R Package for Clinical Reporting Using Tidyverse |
Sheng-Wei Wang |
source
presentation source |
9 |
| PHUSE US |
2023 |
Up-to-Date with Dates - Imputation Rules in R Compared to SAS |
Monika Ludwinska |
source
presentation source |
10 |
| PHUSE US |
2023 |
Use Python to make Clinical Trial Result Posting automatically |
Derek Li |
source
presentation source |
6 |
| PHUSE US |
2023 |
Using R for Automatically Managing Clinical Trial Data Issues [presentation] |
Jessica Riedy,
Jessica Higgins |
source
video |
9 |
| PHUSE US |
2023 |
Using Real-world Data and Synthetic Data to Predict Study Outcomes, Submission Performance and Market Effectiveness [presentation] |
Jose C. Lacal,
Stuart Malcom |
source
video |
15 |
| PHUSE US |
2023 |
Working Together: The Evolving Relationship of Biostatistics & Regulatory for Support of Study Data Standardization Plans and BIMO Reviewer's Guides |
David C. Izard |
source
presentation source |
3 |
| PHUSE EU |
2022 |
A Hitchhiker's Guide to the Corporate World for Newbies |
Ritika Aggarwal |
source
presentation source |
5 |
| PHUSE EU |
2022 |
Advanced SAS techniques to Generate Automated Topline RTF Reports - Used Daily by PMs |
Mizan Alam |
source
presentation source |
15 |
| PHUSE EU |
2022 |
Agile RnD - From Empiricism to Success |
Marc Jantke |
source
presentation source |
8 |
| PHUSE EU |
2022 |
An Approach to Effectively Reproduce TFLs When Performing ADaM Conversion [presentation] |
Amine Khemiri,
Caroline Pelckmans |
source
video |
19 |
| PHUSE EU |
2022 |
Automate to Accelerate: Saama's Smart Auto Mapper |
Mike Collinson |
source
presentation source |
5 |
| PHUSE EU |
2022 |
Automation of Standard ADaM Variables Through an R Package - GenAdam |
Mahesh Divakaran |
source
presentation source |
8 |
| PHUSE EU |
2022 |
Automation of the CDISC Pilot study - a step-by-step guide |
Stuart Malcolm |
source
presentation source |
9 |
| PHUSE EU |
2022 |
Bioresearch Monitoring Data Reviewer's Guide (BDRG) [presentation] |
Jack Field,
Steve Fitzpatrick |
source
video |
20 |
| PHUSE EU |
2022 |
Clinical Data Standards and Production of SDTMs. Are We Missing Important Points? [presentation] |
Eva Stigson,
Paulina Kuczkowska |
source |
15 |
| PHUSE EU |
2022 |
Collaboration Between Analytical Health Care Technology Leaders will Positively Impact Clinical Trial Research Innovation & Improve Health Care System [presentation] |
Mark Lambrecht,
Andrew Warrington |
source
video |
19 |
| PHUSE EU |
2022 |
Deep Learning to Classify Adverse Events from Patient Narratives [presentation] |
Qais Hatim,
Tom Sabo |
source
video |
12 |
| PHUSE EU |
2022 |
Devices and Decentralised Clinical Trials Using a Storage and Advanced Analytics Platform for the Clinical Data Environment (ALYCE) [presentation] |
Stephan Cichos,
Anja Thiede |
source
video |
23 |
| PHUSE EU |
2022 |
Effective NLP API Access to Unstructured Text for Downstream Analysis and Models in Pharma: Bench to Bedside [presentation] |
Jane Reed |
source
video |
26 |
| PHUSE EU |
2022 |
FACT - Fast Access to Clinical Trial Insights [presentation] |
Julia Gnatek,
Steffen Vangsgaard |
source
video |
27 |
| PHUSE EU |
2022 |
Finding Anomalies and Outliers in Clinical Trial Time Series Data |
Pekka Tiikkainen |
source
presentation source |
6 |
| PHUSE EU |
2022 |
From 'Being Alive' to 'Living': Why Does PRO Data Matter? [poster] |
Nimisha Joshi,
Rachel Thackray |
source |
1 |
| PHUSE EU |
2022 |
From Artifact to Metadata: A Divergent Approach to Automation Through Standardisation |
Nicolas Rouillé,
Camie Britton |
source
presentation source |
4 |
| PHUSE EU |
2022 |
Generating Schedule of Activities as FHIR Resources |
Andy Richardson,
Derek Hummerston |
source |
5 |
| PHUSE EU |
2022 |
GSK Diversity Paper: The Challenges We Faced with Real-world Data |
Harrison James,
Chris Leach |
source
presentation source |
43 |
| PHUSE EU |
2022 |
Harnessing AIML Technologies to Expedite Anonymisation of Unstructured Data: Implications for the EU CTR |
Niamh McGuinness,
Muhammad Oneeb Rehman Mian |
source
presentation source |
4 |
| PHUSE EU |
2022 |
Harnessing Routinely Generated git, github and Package-specific Metadata to Build a Portal into Open-source Projects [presentation] |
Mathieu Cayssol,
James Black |
source
video |
18 |
| PHUSE EU |
2022 |
Health Authorities Inspections: What to Expect? A Statistical Programmer Experience |
Alexander Carrington |
source
presentation source |
5 |
| PHUSE EU |
2022 |
How a Clinical Metadata Repository Facilitates Compliance with Industry Standards and Expedites Metadata Storage, Sharing, Analysis and Submission Times |
Gilbert Hunter |
source
presentation source |
2 |
| PHUSE EU |
2022 |
iCDM: Interactive Dashboards that Innovate Centralised Clinical Data Monitoring at Danone Nutricia Research |
Paul Vervuren,
Dennis Menkveld |
source
video
presentation source |
5 |
| PHUSE EU |
2022 |
Is Your Analytics Platform Ready for Handling Real-world Data for Regulatory-grade Real-world Evidence? |
William Kuan,
Olivier Bouchard |
source
presentation source |
7 |
| PHUSE EU |
2022 |
Leveraging Information from Healthy Volunteers' Placebo Data [presentation] |
Koen Ven |
source
video |
17 |
| PHUSE EU |
2022 |
Leveraging Manifest Files for Impact Analysis: Preparing Studies for Critical Deliverables (Interim/Final Run/Submissions) |
Indresh Kumar Singh |
source
poster source |
4 |
| PHUSE EU |
2022 |
Overcoming Challenges of Your Integrated Summary ISS/ISE Submissions |
Jenet Cp,
Akhil Vijayan |
source
presentation source |
7 |
| PHUSE EU |
2022 |
Patient Narratives - Speeding Up Narrative Generation Using ODS Document Stores |
Neville Cope |
source
presentation source |
14 |
| PHUSE EU |
2022 |
Predictive Analytics Framework for Diversity-focused Trial Enrolment: Synergistic role of Registry Data, Lived Experiences, and Programming Power |
Kapil Khambholja,
Vatsal Chhaya |
source
presentation source |
5 |
| PHUSE EU |
2022 |
Preparing for the "Q" in RBQM: The Framework for Risk-Based Quality Management [presentation] |
Jason Konn,
Alison Banda |
source |
9 |
| PHUSE EU |
2022 |
Processing Data and Documents with Natural Language Processing and Quantitative Anonymisation Strategies in Support of CTIS Disclosure Requirements [presentation] |
Elliot Zimmerman,
John Lyons |
source
video |
25 |
| PHUSE EU |
2022 |
Python to Automate an AR Project Identifying Discrepancies across Fields from a Government Open-source Dataset of COVID-19 Vaccine Registrations |
Aldir Medeiros Filho |
source
video
presentation source |
14 |
| PHUSE EU |
2022 |
Quality Tolerance Limits: Statistical and Programming Consideration |
Dhruba Sikdar,
Nathalie van Borrendam |
source
video
presentation source |
7 |
| PHUSE EU |
2022 |
RBM Beyond the Mandate: The Importance and Impacts of Risk-based Monitoring Today [presentation] |
Gina Wood,
Alison Banda |
source |
14 |
| PHUSE EU |
2022 |
Scaling within a Fast-moving Biotech Company. Key Learnings for Leaders and Innovators in Our Life Sciences Industry |
Stijn Rogiers,
Jasmine Kestemont |
source
presentation source |
11 |
| PHUSE EU |
2022 |
Seeing the Full Picture with the R Shiny Data Visualisation Toolbox |
Anastasiia Konvisarova |
source
presentation source |
20 |
| PHUSE EU |
2022 |
Set Up and Drive Your Routine Business Task with Power Automate [presentation] |
Satish Patil,
Bhavin Solanki |
source
video |
33 |
| PHUSE EU |
2022 |
Standards Subject to Change: Data Standards Flexibility in an Evolving Landscape [presentation] |
Gina Wood,
Alison Banda |
source |
28 |
| PHUSE EU |
2022 |
Streamlining the Usage of SAS, R and Python in our Process Workflow [presentation] |
Sayem Rahman,
Shafi Chowdhury |
source |
8 |
| PHUSE EU |
2022 |
Submission Readiness [presentation] |
Ali Dootson |
source |
16 |
| PHUSE EU |
2022 |
The Future-proof Data Fabric for Digital and Decentralised Trials [presentation] |
Venu Mallarapu |
source |
12 |
| PHUSE EU |
2022 |
The Integration Dilemma |
Angelo Tinazzi |
source
video
presentation source |
15 |
| PHUSE EU |
2022 |
The Real Benefit to Using Real-world Evidence Studies" Using RWE to Revamp Clinical Trials |
Artur Sargsyan |
source
presentation source |
5 |
| PHUSE EU |
2022 |
The Role of Data Analytics Functions in Studies Utilising RWD for Submissions [presentation] |
Mark Graham,
Ravi Bahia |
source
video |
15 |
| PHUSE EU |
2022 |
The Secret to Getting Your Dream Job Offer [presentation] |
Tom Oades |
source
video |
13 |
| PHUSE EU |
2022 |
Title:Pixel Plots: Identify Missing Data, See High-level Patterns and Break Axis Constraints |
Paul Grimsey |
source
presentation source |
16 |
| PHUSE EU |
2022 |
Tumour Assessment Evaluation Using MS Azure and Power BI [presentation] |
Robert Adams,
Clara Beck |
source
video |
22 |
| PHUSE EU |
2022 |
Using Individual-level Real-world Data to Inform Disease Area Data Models Employed for Clinical Trial Simulation and Design [presentation] |
Sheila McCartan |
source
video |
41 |
| PHUSE EU |
2022 |
Using Python to Compile CSR |
Loskutov Volodymyr |
source
video
presentation source |
4 |
| PHUSE EU |
2022 |
Using R to Write Patient Narratives |
Narek Torosyan |
source
presentation source |
3 |
| PHUSE EU |
2022 |
What History Teaches Us in Designing a Modern Statistical Computing Environment [presentation] |
Caroline Phares |
source
video |
11 |
| SESUG |
2022 |
A SAS Macro to Calculate Blinding Index in Clinical Trials: %blinding_index, an application of PROC IML |
Jingwei Wu,
Di Zhu |
source |
7 |
| SESUG |
2022 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| SESUG |
2022 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| SAS Explore |
2022 |
Using Simulation to Plan and Rescue Clinical Trial Enrollment [video] |
Jim Box |
source |
|
| WUSS |
2022 |
Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream |
Joshua M. Horstman,
Richann J. Watson |
source |
7 |
| WUSS |
2022 |
Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest |
Lindsey Xie,
Richann J. Watson,
Jinlin Wang,
Lauren Xiao |
source |
15 |
| WUSS |
2022 |
Complex heatmaps in Statistical analysis of Biomarkers and cancer genomics |
Yoganand Budumuru |
source |
18 |
| WUSS |
2022 |
Learn the Basics About the Pharmaceutical Industry in 20 Minutes |
Jim Box,
Matthew J. Becker |
source |
3 |
| WUSS |
2022 |
Quick Jumpstart into Pharmaceutical SAS Programming |
Jim Box,
Matthew J. Becker |
source |
7 |
| WUSS |
2022 |
So You Want to be a Successful Statistical Programmer?: The Importance of People Skills |
Carey G. Smoak |
source |
4 |
| WUSS |
2022 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| WUSS |
2022 |
TrackCHG: A SAS Macro to Colorize and Track Changes Between Data Transfers in Subject-Level Safety Listings |
Inka Leprince,
Elizabeth Li,
Carl Chesbrough |
source |
21 |
| PharmaSUG |
2022 |
A Practical Approach to Preparing Documentation for Clinical Registries |
Jennifer McGrogan,
Rex Tungala,
Mario Widel |
source |
16 |
| PharmaSUG |
2022 |
A Programmer's Perspective on Patient reported Outcomes in Oncology Trials |
Divya Vemulapalli |
source |
7 |
| PharmaSUG |
2022 |
A SAS Macro to Support the Supplemental Qualifier Section in cSDRG |
Jamuna Purma,
Bindya Bindya Vaswani |
source |
9 |
| PharmaSUG |
2022 |
A Tale of Two CDISC Support Groups - Supporting CDISC Standards is Anything but Standard |
Christine McNichol,
Mike Lozano |
source |
9 |
| PharmaSUG |
2022 |
ADaM Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest |
Lindsey Xie,
Richann J. Watson,
Jinlin Wang,
Lauren Xiao |
source |
15 |
| PharmaSUG |
2022 |
Agile innovation - an adaptive approach to transformation in Clinical Research Organizations |
Aman Bahl,
Hrideep Antony |
source |
10 |
| PharmaSUG |
2022 |
Analysis of sample size calculations in clinical trial - errors, pitfalls and conclusions |
Igor Goldfarb,
Ritu Karwal,
Xiaohua Shu |
source |
14 |
| PharmaSUG |
2022 |
Automation using SAS Makes it Easy to Monitor Dynamic Data in Clinical Trial |
Wenjun He |
source |
9 |
| PharmaSUG |
2022 |
Avoid Common Mistakes in Preparing the BIMO Deliverables |
Chintan Pandya,
Himanshu Patel |
source |
9 |
| PharmaSUG |
2022 |
Begin with the End in Mind: eCOA data from collection to analysis |
Franklin E. Menius,
Monali Khanna,
Vincent Allibone |
source |
7 |
| PharmaSUG |
2022 |
Building Dashboards for Data Review and Visualization using R Shiny |
John Saida Shaik,
Sreeram Kundoor |
source |
13 |
| PharmaSUG |
2022 |
Checking Compliance of CDISC SDTM Datasets Utilizing SAS Procedures. |
Ballari Sen |
source |
17 |
| PharmaSUG |
2022 |
Derivation of Efficacy Endpoints by iRECIST Criteria: A Practical Approach |
Ilya Krivelevich,
Lei Gao,
Richard Kennan |
source |
9 |
| PharmaSUG |
2022 |
Digital Health Technology in Clinical Trials: Opportunities, Challenges and Biometrics Future Re-imagined |
Kalyan Chakravarthy Buddavarapu,
Sherry Ye,
Vijay Vaidya |
source |
12 |
| PharmaSUG |
2022 |
Exploring R as a validation tool for statistical programming in clinical trials |
Uday Preetham Palukuru,
Runcheng Li,
Nilesh Patel,
Changhong Shi |
source |
11 |
| PharmaSUG |
2022 |
External R Package Qualification Process in Regulated Environment |
Jane X. Liao,
Fansen Kong,
Yilong Zhang |
source |
10 |
| PharmaSUG |
2022 |
From the Laboratory Toxicity Data Standardization to CTCAE Implementation |
Xiaoyin Zhong,
Jerry Xu |
source |
7 |
| PharmaSUG |
2022 |
Generating Forest and Kaplan Meier graphs for Regulatory Submission: Comparison of SAS and R |
Girija Javvaji,
Sivasankar Konda |
source |
6 |
| PharmaSUG |
2022 |
How to create BARDA Safety report for Periodic review |
Mrityunjay Kumar,
Dnyaneshwari Nighot,
Nitish Kumar,
Ganeshchandra Gupta |
source |
5 |
| PharmaSUG |
2022 |
How to utilize the EC domain to handle complex exposure data |
Varsha Korrapati,
Johnny Maruthavanan |
source |
8 |
| PharmaSUG |
2022 |
Including Population Information in ADaM define.xml for Better Understanding of Datasets |
Hong Qi,
Majdoub Haloui,
Guowei Wu |
source |
6 |
| PharmaSUG |
2022 |
Introduction to Annual Reporting for Beginners! |
Akshita Gurram,
Mamatha Mada |
source |
8 |
| PharmaSUG |
2022 |
Introduction to Synthetic Control Arm |
Venkat Rajagopal,
Abhinav Jain |
source |
4 |
| PharmaSUG |
2022 |
Just Say No to Data Listings! |
Mercidita Navarro,
Nancy Brucken,
Aiming Yang,
Greg Ball |
source |
4 |
| PharmaSUG |
2022 |
Leveraging AI to process unstructured Clinical data in real-time |
Madhusudhan Nagaram,
Syam Prasad Chandrala |
source |
10 |
| PharmaSUG |
2022 |
Merging Pharmacokinetic (PK) Sample Collection and Dosing Information for PK Analysis based on Study Design and lessons learned |
Durga Kalyani Paturi |
source |
11 |
| PharmaSUG |
2022 |
Metadata Driven Approach for Creation of Clinical Trial Figures |
Jeremy Gratt,
Qiuhong Jia,
Girish Kankipati |
source |
13 |
| PharmaSUG |
2022 |
New Digital Trends and Technologies in Clinical Trials and Clinical Data Management |
Srinivasa Rao Mandava |
source |
8 |
| PharmaSUG |
2022 |
Orchestrating Clinical Sequels with a Strategic Wand - Challenges of introducing Rolling CSRs in a Master Protocol |
Neharika Sharma |
source |
9 |
| PharmaSUG |
2022 |
PROC FUTURE PROOF 1.2 - Linked Data |
Danfeng Fu,
Ellie Norris,
Suhas R. Sanjee,
Susan Kramlik |
source |
13 |
| PharmaSUG |
2022 |
Quality Control With External Code |
Bill Coar |
source |
7 |
| PharmaSUG |
2022 |
Quality Gates: An Overview from Clinical SAS Programming Perspective |
Nagadip Rao,
Pavan Jupelli |
source |
10 |
| PharmaSUG |
2022 |
Real Time Oncology Review Readiness from Programming Perspective |
Binal Mehta,
Patel Mukesh |
source |
10 |
| PharmaSUG |
2022 |
Reconstruction of survival curves: An approach of comparing study drug curve with the standard of care digital survival curve |
Girish Kankipati,
Jai Deep Mittapalli |
source |
8 |
| PharmaSUG |
2022 |
RWD (OMOP) to SDTM (CDISC): A primer for your ETL journey |
Ashwini Yermal Shanbhogue |
source |
10 |
| PharmaSUG |
2022 |
SAS Macro to Colorize and Track Changes Between Data Transfers in Subject-Level Listings |
Inka Leprince,
Elizabeth Li,
Carl Chesbrough |
source |
19 |
| PharmaSUG |
2022 |
SAS ODS Application of Interactive and Informative Clinical Trial Reports |
Luwei Pang,
Aiming Yang |
source |
9 |
| PharmaSUG |
2022 |
Unravel the mystery around NONMEM data sets for statistical programmers |
Sabarinath Sundaram,
Lyma Faroz |
source |
9 |
| PharmaSUG |
2022 |
Vendor Audit: What it is and What to Expect from it |
Parag Shiralkar,
Nagadip Rao |
source |
6 |
| PharmaSUG |
2022 |
Win Ratio Simulation For Power Calculation Made Easy |
Lili Li,
Roger Chang,
Benjamin Fine,
Yu-Chen Su |
source |
13 |
| PHUSE US |
2022 |
(eDISH) Evaluation of Drug-induced Serious Hepatotoxicity Using SAS Graph [presentation] |
Jaimin Patel |
source |
13 |
| PHUSE US |
2022 |
A Duet of SAS and Python Generating XML File for Results Disclosure to ClinicalTrials.gov and EudraCT [presentation] |
Linghui Zhang |
source
video |
16 |
| PHUSE US |
2022 |
Applications of the R Package Validation Framework and {valtools} [presentation] |
Ellis Hughes |
source
video |
34 |
| PHUSE US |
2022 |
CDISC Analysis Results Standards - Approach and Development Update [presentation] |
Bess LeRoy,
Jeffrey M. Abolafia,
Bhavin Busa |
source |
18 |
| PHUSE US |
2022 |
Data Standardization at Scale with the elluminate Clinical Data Cloud [presentation] |
Nathan Johnson |
source |
19 |
| PHUSE US |
2022 |
Does My Skill Set Still Meet the Needs of the Market? [presentation] |
Dmytro Skorba |
source
video |
22 |
| PHUSE US |
2022 |
DPS Helper: A Web Application to Create the Data Presentation Specifications Word Document in Clinical Trials [presentation] |
Asavari Mehta,
Xiaoguang Yan |
source
video |
37 |
| PHUSE US |
2022 |
FDA Study Data Technical Rejection Criteria (TRC): What You Need to Know! [presentation] |
Jiang Xu,
Lina Cong |
source
video |
26 |
| PHUSE US |
2022 |
How Disclosure Teams Are Collaborating and Embracing the Changes Imposed by Global Transparency Regulations [presentation] |
Elliot Zimmerman |
source |
12 |
| PHUSE US |
2022 |
Incorporating Immunogenicity Data from Various Analyzing Labs [presentation] |
Elisabeth van Son-Palmen,
Gunasekaran Subramaniam |
source |
19 |
| PHUSE US |
2022 |
Introducing Reporting Packages in R for TFLs [presentation] |
Pavan Reddy,
Thomas Kalfas |
source
video |
12 |
| PHUSE US |
2022 |
Pan-pharma Industry Collaboration - New Horizon, Success Stories [presentation] |
Tadeusz Lewandowski |
source
video |
21 |
| PHUSE US |
2022 |
Practical Challenges in Handling Unstructured Data Using Artificial Intelligence [presentation] |
Farha Feroze |
source
video |
11 |
| PHUSE US |
2022 |
R and its Application in Clinical Trial Data Analysis [presentation] |
Santosh Kumar Davuluri |
source
video |
21 |
| PHUSE US |
2022 |
RBM - The New Normal Vigilante for CROs With AI and ML [presentation] |
Vidya Muthukumar |
source |
18 |
| PHUSE US |
2022 |
Reflections on Our Experience Moving to Open-source Pan-pharma Code Collaboration on Clinical Trial Reporting Tools [presentation] |
James Black |
source |
20 |
| PHUSE US |
2022 |
SPACE - Launching GSK Biostatistics towards new horizons |
Eileen Ching |
source
presentation source |
10 |
| PHUSE US |
2022 |
Statistical Programming Operational Review Dashboard [presentation] |
Kathleen J. Harkins,
Shuqi Zhao |
source
video |
16 |
| PHUSE US |
2022 |
Staying Ahead of the Curve: The Future Direction of Modernization of Statistical Analytics (MSA) [presentation] |
Peter Mesenbrink |
source |
19 |
| PHUSE US |
2022 |
The Bioresearch Monitoring Data Reviewer's Guide (BDRG) [presentation] |
Julie Maynard,
Sopan Dharma Kaith |
source |
25 |
| PHUSE US |
2022 |
The Decentralized Trials Data Problem: Foundations for the Future of Clinical Trials [presentation] |
Raj Indupuri |
source
video |
11 |
| PHUSE US |
2022 |
The RBM to RBQM Transformation: More Than the Method or the Tool [presentation] |
Alison Banda,
Jason Konn |
source |
12 |
| PHUSE US |
2022 |
Title: AI Application for Authoring Clinical Study Reports [presentation] |
Eric Weising,
Farha Feroze |
source
video |
9 |
| PHUSE US |
2022 |
Trial Summary SDTM Domain Made Easy for Regulatory Submissions [presentation] |
Kishore Pothuri |
source |
16 |
| PHUSE US |
2022 |
Using AI-based Technology to Accelerate Clinical Trial Data Sharing and Reuse [presentation] |
Ron Kaine,
Thomasin Element |
source
video |
33 |
| PHUSE US |
2022 |
We R in SPACE (Statistical Programming And Computing Environment). And We R Not Alone! [presentation] |
Alastair Scarlett,
Sumesh Kalappurakal |
source |
7 |
| PHUSE US |
2022 |
Working Smarter with Data to Optimize Onsite Monitoring [presentation] |
Jackie Gough |
source |
9 |
| PHUSE EU |
2021 |
A Beginner's Guide to Data Analysis |
Shuva Dey |
source
video |
15 |
| PHUSE EU |
2021 |
Advanced Excel Specification for Automatic SDTM Generation |
Aleksandra Gorbunova,
Ilya Mishchenko |
source
video
presentation source |
10 |
| PHUSE EU |
2021 |
AI-powered Drug Development: Accelerating Trials with AI & ML [presentation] |
Raj Indupuri |
source
video |
10 |
| PHUSE EU |
2021 |
Augmenting Therapeutic Effectiveness through Novel Analytics (ATHENA) - A Public-Private Partnership Project Funded by the Flemish Government (VLAIO) [presentation] |
Ploingarm Petsophonsakul,
Wouter Botermans |
source
video |
14 |
| PHUSE EU |
2021 |
Automated creation of a mapping specification for a pooled database |
Thomas Wollseifen |
source
video
presentation source |
12 |
| PHUSE EU |
2021 |
Building an SCE that Users Want to Use [presentation] |
Alastair Scarlett,
Chris Decker |
source
video |
9 |
| PHUSE EU |
2021 |
CDISC Analysis Results Standard Team: Enhancing Analysis Results and Traceability [presentation] |
Bess LeRoy,
Jeffrey M. Abolafia |
source
video |
41 |
| PHUSE EU |
2021 |
Clinical Design - Visualisation and Analysis Using the Interactive Application by R Shiny |
Athira Sudhakar,
Mahesh Divakaran |
source
video |
7 |
| PHUSE EU |
2021 |
Does No Errors Equal High Quality? [presentation] |
Julie Solbjerg Appel,
Sanna Herrgård |
source
video |
23 |
| PHUSE EU |
2021 |
EMA Panel Discussion: What Might the Future Landscape of Submitting Data Look Like in 2025 ? [presentation] |
Eftychia-Eirini Psarelli,
Jesper Kjær |
source |
11 |
| PHUSE EU |
2021 |
EMA Panel Discussion: What Might the Future Landscape of Submitting Data Look Like in 2025 ? [presentation] |
Eftychia-Eirini Psarelli,
Jesper Kjær |
source |
21 |
| PHUSE EU |
2021 |
HoW: New Era of Collaboration - Towards the Adoption of Digital Measures - DEEP Initiative |
Kai Langel,
Bert Hartog |
source |
13 |
| PHUSE EU |
2021 |
iListing - Get More Out of Listings [presentation] |
Katja Glass |
source
video |
37 |
| PHUSE EU |
2021 |
Implementation of a flat model for reactogenicity events in vaccine studies |
Charumathy Sreeraman,
Ephicacy Lifescience |
source
video
presentation source |
7 |
| PHUSE EU |
2021 |
Integrated Summary of Safety and Efficacy Production Strategies |
Navneet Agnihotri,
Sumit Pratap Pradhan |
source
video
presentation source |
9 |
| PHUSE EU |
2021 |
Methods and Challenges of R Validation for Regulatory Submission Analysis [presentation] |
Parvee Kumar |
source
video |
14 |
| PHUSE EU |
2021 |
Multiple Graphs with Common Horizontal Axis Using GTL |
Navneet Agnihotri,
Sumit Pratap Pradhan |
source
video
poster source |
4 |
| PHUSE EU |
2021 |
Navigating the Evolving Regulations for Health Canada [presentation] |
Gina Bennet |
source
video |
20 |
| PHUSE EU |
2021 |
New Insights Through Cross-portfolio Risk Analysis [presentation] |
Abdollahi Rouhollah,
Julian Ortiz |
source
video |
17 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
10 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
7 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
11 |
| PHUSE EU |
2021 |
Ongoing Safety Monitoring Using R-shiny [presentation] |
Pernille Højlund Nielsen,
Pernille Juul Jørgensen |
source
video |
12 |
| PHUSE EU |
2021 |
Preparing PK/PD ADaM Datasets and eCRT Data Package for FDA Submission |
Junying Zhang |
source
video
presentation source |
11 |
| PHUSE EU |
2021 |
Programming Infrastructure to Automate Process Flow for CSS [presentation] |
Archana Nayak,
Salvatore Saporito |
source
video |
22 |
| PHUSE EU |
2021 |
R and SAS Working Together - DNR's Experience Moving to LSAF 5.3 [presentation] |
Paul Vervuren |
source
video |
17 |
| PHUSE EU |
2021 |
Real-time Analysis of Clinical Trial Data [presentation] |
Jem Chang,
Prasanna Murugesan |
source
video |
9 |
| PHUSE EU |
2021 |
Real-world Data, CDISC SDTM, HL7 FHIR and the Future of Regulatory Submissions [presentation] |
Jozef Aerts |
source
video |
17 |
| PHUSE EU |
2021 |
Software Demonstration: Unlocking Value from Structured Clinical Trial Data - Sponsored by Privacy Analytics [presentation] |
Thomasin Element |
source |
18 |
| PHUSE EU |
2021 |
Software Evolutions are Inevitable: Phase Your Coding evolution to Modern Clinical Trial Analytics by Using both Old/New Techniques in a Modern SAS Platform [presentation] |
Olivier Bouchard,
Pritesh Desai |
source
video |
19 |
| PHUSE EU |
2021 |
Standard Implementation: Battling Through the Adversity of a Pandemic [presentation] |
Ana Arques,
Vicky Poulsen |
source
video |
18 |
| PHUSE EU |
2021 |
Standing Room Only: AR02: The Importance of Being Ernest - The Role of QTLs in QbD [presentation] |
Andrew Lawton |
source |
19 |
| PHUSE EU |
2021 |
Standing Room Only: DH01: ClinicalTrials.gov REST API - Tapping into the Clinical Studies Registry Database the Smart Way [presentation] |
Lukas Kniola |
source |
30 |
| PHUSE EU |
2021 |
Standing Room Only: SA04: Diversity, Equity and Inclusion of Your Submission Package [presentation] |
Anne-Sophie Bekx |
source |
19 |
| PHUSE EU |
2021 |
Statistical Training for Health Technology Assessment Statistical Programmers |
Anastasia Kokoreva,
William Malbecq |
source
video
presentation source |
7 |
| PHUSE EU |
2021 |
The AstraZeneca Data Automation Team: Future-proofing Programming Teams to Meet Tomorrow's Challenges [poster] |
Ruhul Amin,
Tony Allen |
source
video |
1 |
| PHUSE EU |
2021 |
The Library Approach Driving EDC Set-up Efficiencies: A Case Study [presentation] |
Jan De Cleir |
source
video |
23 |
| PHUSE EU |
2021 |
Use Python to Combine LST Files into a PDF file with Bookmarks |
Hengwei Liu |
source
video
presentation source |
10 |
| PHUSE EU |
2021 |
Using Jobs and API Macros to Create a Structured, Controlled and Personalised LSAF Environment [presentation] |
Stephan van Driel |
source
video |
30 |
| SESUG |
2021 |
Some Linux Shell Scripts for SAS Programmers |
Hengwei Liu |
source |
9 |
| PHUSE US |
2021 |
A Well Design QC Toolkit for Clinical Programming Compliance Checking [presentation] |
Huei-Ling Chen,
Sandeep Meesala |
source
video |
30 |
| PHUSE US |
2021 |
An R-based Tool to Build Questionnaires, Ratings and Scales (QRS) in EDC for Clinical Trials [presentation] |
Catherine Abogado,
Rammprasad Ganapathy |
source
video |
19 |
| PHUSE US |
2021 |
Automate Scientific Document such as CSR Generation using ML/NLP [presentation] |
Farha Feroze |
source
video |
13 |
| PHUSE US |
2021 |
Automated Validation of Clinical Trial Analysis and Reporting Deliverables Using 'testthat' [presentation] |
Amin Shirazi,
Jane X. Liao |
source
video |
35 |
| PHUSE US |
2021 |
Automation of a Web-based Metadata Repository for SAS Datasets with Selenium Technology [presentation] |
Eugene Tsykalov |
source
video |
14 |
| PHUSE US |
2021 |
Building an SCE that Users Want to Use [presentation] |
Alastair Scarlett,
Chris Decker |
source
video |
9 |
| PHUSE US |
2021 |
China Center for Drug Evaluation, NMPA Electronic Study Data Submission Requirements [presentation] |
Majdoub Haloui,
Yanhong Li |
source
video |
16 |
| PHUSE US |
2021 |
Commercially Confidential Information in clinical data publishing [presentation] |
Parvee Kumar |
source
video |
17 |
| PHUSE US |
2021 |
COVID-19 Presentation: CO01: Harnessing the Power of Shiny to Visualize Missing Data due to the COVID-19 Pandemic [presentation] |
Mark Rothe,
Sangeeta Bhattacharya |
source |
13 |
| PHUSE US |
2021 |
CSR Narratives Automation [presentation] |
Ritesh Dhimmar |
source
video |
23 |
| PHUSE US |
2021 |
Data Visualizations for Publication, Decision-making and Submission [presentation] |
Maria Dalton |
source
video |
18 |
| PHUSE US |
2021 |
Do EudraCT the Easy Way: Semi-automation of Inputting Study & Treatment Event Information in EudraCT [presentation] |
Kevin Miller,
Larry Sleeper |
source
video |
21 |
| PHUSE US |
2021 |
Exploring Categorical Data Using Unsupervised Graph-based Machine Learning [presentation] |
Irina Kotenko,
Kostiantyn Drach |
source
video |
34 |
| PHUSE US |
2021 |
FDA & PMDA Validator Rules - What, Why and How ... But Should You Care? [presentation] |
Charanjit Kahlon,
Kishore Pothuri |
source
video |
21 |
| PHUSE US |
2021 |
FDA Conformance Analysis and Upcoming Implementation of Technical Rejection Criteria for Study Data [presentation] |
Ethan Chen,
Heather Crandall |
source |
36 |
| PHUSE US |
2021 |
Good Cooperation Between SAS and R for Regulatory Submission [presentation] |
Jingyuan Chen |
source
video |
19 |
| PHUSE US |
2021 |
Hydrating a Data Lake to Power Innovation - Enabling Pharmaceutical Companies to Automate Data De-identification for Secondary Use [presentation] |
Cathal Gallagher,
Kristin McDougall |
source
video |
16 |
| PHUSE US |
2021 |
Keynote Presentation: Our Access to Real-world Data is Not Sustainable Without Transparency and Inclusion [presentation] |
Craig Lipset |
source |
33 |
| PHUSE US |
2021 |
Leadership Presentations: LE02: How to Build Knowledge Capacity for a High-performance Team [presentation] |
Xiaohui Wang |
source |
14 |
| PHUSE US |
2021 |
Leadership Presentations: LE06: One Sprint at a Time - Agile Transformation in Clinical Research [presentation] |
Aman Bahl,
Steve Benjamin |
source |
17 |
| PHUSE US |
2021 |
Patient Registries - New Gold Standard for Real World Data [presentation] |
Lavanya Peddibhotla,
Sivasankar Konda |
source
video |
14 |
| PHUSE US |
2021 |
Planning and Execution of Real-world Data Evidence Analysis |
Nicole Thorne,
Ramesh Sundaram |
source
video
presentation source |
6 |
| PHUSE US |
2021 |
Power BI in Clinical Data Exploration: Powerful Visuals that Answer Relevant Questions |
Lotte Jacobs,
Roxane Debrus |
source
video
presentation source |
10 |
| PHUSE US |
2021 |
Processes and Techniques for Creating Integrated Summary of Safety (ISS) |
Ghanshyam Jangid,
Jane E. Marrer |
source
video
presentation source |
9 |
| PHUSE US |
2021 |
Real-Time Clinical Trial Analytics Using Automation with IBM Clinical, Medidata Rave and Datacise [presentation] |
Aditya Gadiko,
Christopher C. Hurley |
source
video |
7 |
| PHUSE US |
2021 |
Reflect and Get More Information Out of Data than Ever Before [poster] |
Catharina Dahlbo,
Eva Kelty |
source |
1 |
| PHUSE US |
2021 |
Regulatory Update & Townhall [presentation] |
Ethan Chen |
source |
28 |
| PHUSE US |
2021 |
Rescreened Subjects, Data Collection and Standard Domain Mapping |
Savithri Jajam,
Vamshi Matta |
source
video
presentation source |
6 |
| PHUSE US |
2021 |
Self-sufficient Exploration of Clinical Trial Events in Different Ways and in Different Contexts [presentation] |
Eva Kelty |
source
video |
15 |
| PHUSE US |
2021 |
SimSCE: Building an SCE City to Support My Process [presentation] |
Andrew B. Ratcliffe,
Chris Decker |
source
video |
36 |
| PHUSE US |
2021 |
Software Demonstration: SD12: Reporting Application that Provides Instant Oversight to Management and Actively Helps Programmers to Save Time, Implement Standards and Raise Quality [presentation] |
Shafi Chowdhury |
source |
11 |
| PHUSE US |
2021 |
Standing Room Only Presentation: CM03: Quality Tolerance Limits: Leveraging Predictive Modeling [presentation] |
Christina Dinger,
Slade McKee |
source |
18 |
| PHUSE US |
2021 |
Standing Room Only Presentation: CT05: Programmatic Approach to Ensure Data Package Contents [presentation] |
Simon Xue,
Tanmay Khole |
source |
9 |
| PHUSE US |
2021 |
Standing Room Only Presentation: DH02: On the Other Side of the Fence: When Two Skill Areas Join Forces and Boundaries Dissolve [presentation] |
Mette Krogh Beyer,
Stine Ross |
source |
15 |
| PHUSE US |
2021 |
Standing Room Only Presentation: DV10: Topline Results Dashboards with Rmarkdown & Flexdashboard [presentation] |
Harsha Kalikivayi,
Robert Adams |
source |
26 |
| PHUSE US |
2021 |
Statistical Computing Environment White Paper |
Jorine Putter,
Mark Bynens |
source
pdf
video |
45 |
| PHUSE US |
2021 |
The Case for Pandemic-disrupted Studies and Challenges Implementing CDISC and FDA COVID-19 Guidelines for NDA Submissions [presentation] |
Vidya Muthukumar |
source |
44 |
| PHUSE US |
2021 |
Using Computer Vision to Identify and Extract Tables from Various File Formats [presentation] |
Kanishk Mair,
Shashank Pagidimarri |
source
video |
22 |
| PHUSE US |
2021 |
Using Natural Language Processing to Create Subject Safety Narratives [presentation] |
Frank Meloni,
Tim Willittes |
source
video |
8 |
| PHUSE US |
2021 |
Using Real-world Data in Supporting Health Authority Submission [presentation] |
Ruoying Fang,
Shuang Zhang |
source
video |
26 |
| PHUSE US |
2021 |
Visualization of Sparse PK Concentration Sampling Data, Step by Step (Improvement by Improvement) |
Ilya Krivelevich |
source
video
presentation source |
12 |
| PHUSE US |
2021 |
Visualizing Efficacy Data from Phase II or III Randomized, Double Blind Placebo Controlled Trials [presentation] |
Munish Mehra |
source
video |
18 |
| PharmaSUG |
2021 |
A Diagnostic Report for SAS Submission Programs |
Yang Gao,
Christine S Teng |
source |
6 |
| PharmaSUG |
2021 |
A Lead Programmer-s Guide to a Successful Submission |
Pranav Soanker,
Santosh Shivakavi |
source |
8 |
| PharmaSUG |
2021 |
A metadata driven approach to mock TFL generation |
Anne Petersen,
Cristina Boschini,
Tobias Kröpelin |
source |
5 |
| PharmaSUG |
2021 |
A Process to Validate Internal Developed R Package under Regulatory Environment |
Madhusudhan Ginnaram,
Amin Shirazi,
Simiao Ye,
Yalin Zhu,
Yilong Zhang |
source |
7 |
| PharmaSUG |
2021 |
A Strategy to Develop Specification for R Functions in Regulated Clinical Trial Environments |
Aiming Yang,
Yalin Zhu,
Yilong Zhang |
source |
11 |
| PharmaSUG |
2021 |
A TransCelerate Initiative - how can you modernize your statistical environment? |
Vincent J. Amoruccio,
Min Lee,
Daniel Woodie |
source |
16 |
| PharmaSUG |
2021 |
ADaM Implementation Guide for Medical Devices |
Julia Yang,
Silvia Faini,
Karin LaPann |
source |
11 |
| PharmaSUG |
2021 |
Agile Project Management in Analysis and Reporting of Late Stage Clinical Trial |
Sarad Nepal,
Uday Preetham Palukuru,
Peikun Wu,
Madhusudhan Ginnaram,
Ruchitbhai Patel,
Abhilash Chimbirithy |
source |
11 |
| PharmaSUG |
2021 |
An R Shiny Application: Validated Analysis Results Using R and SAS |
Abu Zafar Mohammad Sami |
source |
9 |
| PharmaSUG |
2021 |
Analysis and Reporting in Regulated Clinical Trial Environment using R |
Peikun Wu,
Uday Preetham Palukuru,
Yiwen Luo,
Sarad Nepal,
Yilong Zhang |
source |
11 |
| PharmaSUG |
2021 |
Application to Automate Clinical Study Report Generation using AI |
Farha Feroze |
source |
5 |
| PharmaSUG |
2021 |
Archival Tool: Automation using PowerShell |
Sumit Pratap Pradhan |
source |
9 |
| PharmaSUG |
2021 |
Automated CONSORT Flow Diagram Generation by SAS Programming |
Ryan Yu |
source |
10 |
| PharmaSUG |
2021 |
BAYESIAN Approach on COVID-19 test results |
Vidya Srinivas,
Ankita Sharma |
source |
4 |
| PharmaSUG |
2021 |
CDISC ADaM Phases, Periods, and Subperiods: A Case Study |
Jennifer K. Fulton |
source |
9 |
| PharmaSUG |
2021 |
Creating Patient Profiles Using SAS Software: Proc Report & SAS ODS |
Ballari Sen |
source |
13 |
| PharmaSUG |
2021 |
Customize and Beautify Your Kaplan-Meier Curves in Simple Steps |
John Henderson,
Lili Li |
source |
7 |
| PharmaSUG |
2021 |
Delight the Customer using agile transformation in Clinical Research |
Aman Bahl,
Steve Benjamin,
Hrideep Antony |
source |
9 |
| PharmaSUG |
2021 |
Effective Approach for ADaM Submission to FDA and PMDA |
Ranvir Singh |
source |
6 |
| PharmaSUG |
2021 |
Evaluating anthropometric growth endpoints with Z-Scores and Percentiles |
Snehal Sanas,
Pradeep Umapathi |
source |
11 |
| PharmaSUG |
2021 |
Fast, Efficient, and Automated Real-time Analytics for Clinical Trials |
Aditya Gadiko,
Christopher C. Hurley,
Anish Iyer |
source |
5 |
| PharmaSUG |
2021 |
FDA Study Data Technical Rejection Update [presentation] |
Ethan Chen |
source |
36 |
| PharmaSUG |
2021 |
Forward Planning: How to get the most of your eCOA data |
Monali Khanna,
Franklin E. Menius |
source |
7 |
| PharmaSUG |
2021 |
GCIG Criteria, Programming Makes It Easy |
Liming Xie,
Wei Wei |
source |
9 |
| PharmaSUG |
2021 |
Generating Synthetic CDISC Clinical Trial Data. |
Jose C. Lacal |
source |
14 |
| PharmaSUG |
2021 |
How simulation will impact the future of Healthcare & Life Sciences. |
Pritesh Desai,
Allison Sealy,
Shawn Tedman,
Lois Wright,
Bahar Biller |
source |
14 |
| PharmaSUG |
2021 |
How to handle decision making in the CRO / sponsor relationship in matters that require expertise |
Sarah McLaughlin |
source |
3 |
| PharmaSUG |
2021 |
How to Translate RTF Documents |
Jundong Ma,
Zhiping Yan |
source |
9 |
| PharmaSUG |
2021 |
IOT or IOMT? |
Lekitha JK |
source |
4 |
| PharmaSUG |
2021 |
Leadership and Programming |
Kriss Harris |
source |
6 |
| PharmaSUG |
2021 |
Life After Drug Approval... What Programmers Need to Know About REMS |
Cara Lacson,
Carol Matthews |
source |
11 |
| PharmaSUG |
2021 |
Macro to Compare Titles and Footnotes in Produced TLF and Corresponding Shells |
Igor Goldfarb,
Ella Zelichonok |
source |
26 |
| PharmaSUG |
2021 |
Multiple Successful Submissions of Medical Device Clinical Trial Data in the US and China using CDISC |
Phil Hall,
Tikiri B. Karunasundera,
Subendra Maharjan,
Vijaya Vegesna |
source |
10 |
| PharmaSUG |
2021 |
New Requirements of Clinical Trial Data Submission for China Filing: An Implementation |
Yuan Yuan Dong,
Wang Zhang,
Lily Ling |
source |
5 |
| PharmaSUG |
2021 |
No Black Boxes: An Utterly Transparent Batch Randomization System in R |
Dennis Sweitzer |
source |
12 |
| PharmaSUG |
2021 |
Preserving the Privacy of Participant's Data by Data Anonymization |
Chaithanya Velupam,
Kaushik Sundaram |
source |
10 |
| PharmaSUG |
2021 |
PROC FUTURE PROOF v1.1 - Linked Data |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee,
Jindřich Mynarz,
Danfeng Fu |
source |
12 |
| PharmaSUG |
2021 |
R Validation: Approaches and Considerations |
Philip Bowsher,
Sean Lopp |
source |
3 |
| PharmaSUG |
2021 |
SEND for CBER |
Lisa Lin |
source |
26 |
| PharmaSUG |
2021 |
Survival Statistics with PROC LIFETEST and PROC PHREG: Pitfall-Avoiding Survival Lessons for Programmers |
Yun (Julie) Zhuo |
source |
10 |
| PharmaSUG |
2021 |
Virtual human organs in clinical trails |
Sumeet Subhedar |
source |
3 |
| PharmaSUG |
2021 |
Visualization of Sparse PK Concentration Sampling Data, Step by Step (Improvement by Improvement) |
Ilya Krivelevich,
Simon Lin |
source |
14 |
| PharmaSUG |
2021 |
Why Data Scientists need leadership skills? Story of Cross-Value Chain Data Utilization Project |
Yura Suzuki,
Yuichi Koretaka,
Ryo Kiguchi,
Yoshitake Kitanishi |
source |
8 |
| SGF |
2021 |
Analyzing Data Missing Due to COVID-19: From Raw Data to ADaM and Beyond |
Yuliia Bahatska |
source
presentation |
12 |
| SGF |
2021 |
Deep Learning to Classify Adverse Events from Patient Narratives [presentation] |
Qais Hatim,
Tom Sabo |
source |
19 |
| SGF |
2021 |
Open Source SAS Macros - What? Where? How? |
Katja Glass |
source
presentation |
15 |
| PHUSE EU |
2020 |
A Collaborative Approach to Analysis Standards [presentation] |
Margie Merlino,
Marleen Nijs |
source
video |
22 |
| PHUSE EU |
2020 |
A Novel Way of Creating Tables in R [presentation] |
Adrian Waddell |
source
video |
42 |
| PHUSE EU |
2020 |
A Programmer's Journey Through an Early Oncology Adaptive Platform Trial [presentation] |
Rafi Rahi |
source
video |
20 |
| PHUSE EU |
2020 |
Achieving Balance - Approaching Anonymisation with Quantified Risk [presentation] |
Cathal Gallagher |
source
video |
27 |
| PHUSE EU |
2020 |
AI-assisted Medical Coding [presentation] |
Christian S. Christensen,
Thomas Ellebaek |
source
video |
20 |
| PHUSE EU |
2020 |
AI-supported and Demand-oriented Data Integration of Clinical Studies [presentation] |
David Hipp,
Kai Spielmann |
source
video |
18 |
| PHUSE EU |
2020 |
An Introduction to the Use of BigQuery for the Life Sciences [presentation] |
Claudio Garutti |
source
video |
14 |
| PHUSE EU |
2020 |
Application to Automate CSR Generation Using ML/NLP [presentation] |
Eric Weising,
Farha Feroze |
source
video |
10 |
| PHUSE EU |
2020 |
Approaches to Schedule of Activities (SOA) Specification for Automated Implementation [presentation] |
Andy Richardson |
source
video |
27 |
| PHUSE EU |
2020 |
Bilingual Execution - SAS and R in Clinical Trials - Initial Thoughts [presentation] |
Ari Siggaard Knoph,
Steffen Falgreen Larsen |
source
video |
16 |
| PHUSE EU |
2020 |
Brace Yourself for Smooth Unblinding [presentation] |
Vladyslav Khudov |
source
video |
26 |
| PHUSE EU |
2020 |
Breaking Boundaries: Working Across Different Workspaces in LSAF |
Kai Wanke |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
Data Integrity & Standards in the Clinical Data Pipeline [presentation] |
Mark Wheeldon,
Raj Indupuri |
source
video |
30 |
| PHUSE EU |
2020 |
Deploying Machine Learning in Data Management [presentation] |
Sheila Rocchio |
source
video |
11 |
| PHUSE EU |
2020 |
Digital Biomarkers Touch Down in Statistical Programming [presentation] |
Alexander Salzer,
Florian Wiese |
source
video |
23 |
| PHUSE EU |
2020 |
Don't UnderMine the Value of Your CRF - with Perl Regular Expressions [presentation] |
John McDade |
source
video |
22 |
| PHUSE EU |
2020 |
Enabling Novel Digital Endpoints in Clinical Trials for Regulatory Purposes: Bringing Efficiency to the Industry by Creating a Service-based Ecosystem [presentation] |
Bert Hartog,
Kai Langel |
source
video |
14 |
| PHUSE EU |
2020 |
Enhanced COVID-19 (SARS-COV-2) Detection - An Artificial Intelligence Approach [presentation] |
Muhammad Hamiz Ahmed,
Soundarya Palanisamy |
source
video |
37 |
| PHUSE EU |
2020 |
Goodbye, Excel, My Old Friend: A Collaboration Between Sanofi and S-cubed [presentation] |
David Iberson-Hurst,
Karen Fanouillere |
source
video |
19 |
| PHUSE EU |
2020 |
Graph Data Representation - The FAIRest of Them All [presentation] |
Eva Kelty,
Peter Tormay |
source
video |
25 |
| PHUSE EU |
2020 |
Improve Programming and Traceability with Datasets for Statistical Analysis Results |
Henning Pontoppidan Föh,
Jeppe Juul |
source
video
presentation source |
4 |
| PHUSE EU |
2020 |
Innovation in Exploratory/Regulatory Clinical Trial Analyses [presentation] |
Tadeusz Lewandowski |
source
video |
31 |
| PHUSE EU |
2020 |
Let CDISC Be |
Roxane Debrus,
Silvia Faini |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
Let food be thy medicine and medicine be thy food |
Fatima Kassim |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
Let's Include Every Data Point: Overview of Analytical Risk-based Monitoring with Spotfire Visualisations [presentation] |
Raju Tadala |
source
video |
17 |
| PHUSE EU |
2020 |
Make your data come alive |
Babych Oleksandr |
source
video
presentation source |
11 |
| PHUSE EU |
2020 |
Managing an International Statistical Programming Team in the Era of New Ways of Working |
Frédéric Coppin,
Harris Kampouris |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
MI FOR MI, OR HOW TO HANDLE MISSING INFORMATION WITH MULTIPLE IMPUTATION |
Daria Shamaida |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
One Boy's Dream: Hitting a Homerun in the Bottom of the Ninth Inning [presentation] |
Carey G. Smoak |
source
video |
23 |
| PHUSE EU |
2020 |
Patient Insights and Real-world Data from Social Media [presentation] |
Luisa Regenold,
Soundarya Palanisamy |
source
video |
28 |
| PHUSE EU |
2020 |
Pre-screening Process Flow [poster] |
Eva Joossens,
Jothi Suresh |
source
video |
1 |
| PHUSE EU |
2020 |
Preparing for FDA and PMDA Submission Simultaneously - What to Leverage, How to Deal with the Differences Efficiently [presentation] |
Jasmine Kestemont |
source
video |
22 |
| PHUSE EU |
2020 |
RBM: Pain or Pleasure? Tips for Effective Implementation [presentation] |
Steven Thys |
source
video |
33 |
| PHUSE EU |
2020 |
Rise and Shine: Using R Shiny to explore insomnia clinical trial data |
Matthew Brierley |
source
video
presentation source |
6 |
| PHUSE EU |
2020 |
Successful and Optimised Project Delivery by Embracing Agile in a Validated Environment [presentation] |
Andy Ratcliffe,
Chris Cowling |
source
video |
34 |
| PHUSE EU |
2020 |
The TransCelerate Hackathon: Accelerating Development [presentation] |
Johannes Ulander |
source
video |
26 |
| PHUSE EU |
2020 |
TidyCDISC: An Open-source Application to Interactively Create Tables, Figures and Patient Profiles from ADaM Data [presentation] |
Maya Gans,
Nate Mockler |
source
video |
21 |
| PHUSE EU |
2020 |
Understanding the Spread of COVID-19 in the United States Using Topology and Machine Learning for Time Series |
Iryna Kotenko,
Kostiantyn Drach |
source
video
presentation source |
32 |
| PHUSE EU |
2020 |
Unlocking the Potential of Big Data in Clinical Research [presentation] |
Vishal Kapoor |
source
video |
15 |
| PHUSE EU |
2020 |
Use Cases of Google Sheets in Programming Applications [presentation] |
Carina Hillenbach |
source
video |
16 |
| PHUSE EU |
2020 |
Using R from End to End: CDISC SDTM and ADaM into .xpt and Output Generation [presentation] |
Antonio Rodríguez Contestí |
source
video |
46 |
| PHUSE EU |
2020 |
Visualisation of Risk Indicators Using the Shiny App [presentation] |
Kadriye Kaplan |
source
video |
10 |
| SESUG |
2020 |
Analysis and Reporting of Reactogenicity Events in Vaccine Clinical Trials |
Amarnath Vijayarangan,
Sarah G. Anderson,
Santhiya Poongavanam |
source |
9 |
| SESUG |
2020 |
Some Korn Shell Scripts for SAS Programmers |
Hengwei Liu,
Daiichi Sankyo |
source |
7 |
| SESUG |
2020 |
Upgrading Clinical Trial Reports from ODS LISTING to ODS TAGSETS.RTF |
Christopher J. Smith |
source |
25 |
| SGF |
2020 |
Combination Weighted Log-rank Tests for Survival Analysis with Non-proportional Hazards |
Andrea Knezevic,
Sujata Patil |
source |
10 |
| SGF |
2020 |
Data Standardization Using SAS Health Data Mapper |
Eric Bolender |
source |
14 |
| SGF |
2020 |
Metrics and Medical Writing - We Don't Just Count Words |
Daniel Augusto Muriel Ramirez,
Dominic De Bellis |
source |
12 |
| SGF |
2020 |
Reaching Your Potential as a Statistician and Leader |
Gary R. Sullivan |
source |
17 |
| SGF |
2020 |
Sample Size Calculations Using SAS, R, and nQuery Software |
Jenna Cody |
source |
19 |
| SGF |
2020 |
Statistical Programming in the Pharmaceutical Industry: Advancing and Accelerating Drug Development |
Harper Forbes |
source |
10 |
| SGF |
2020 |
Upgrading Clinical Trial Reports from ODS LISTING to ODS TAGSETS.RTF |
Christopher J. Smith,
Joshua M. Horstman |
source |
25 |
| SGF |
2020 |
Using SAS Visual Analytics Reports for Operational Reporting in Clinical Trials |
Jun Wen,
Jack Shostak |
source |
17 |
| PharmaSUG |
2020 |
%MVMODELS: a Macro for Survival and Logistic Analysis |
Jeffrey P. Meyers |
source |
23 |
| PharmaSUG |
2020 |
10 things you need to know about PMDA eSubmission |
Yuichi Nakajima |
source |
6 |
| PharmaSUG |
2020 |
A SAS macro for tracking the Status of Table, Figure and Listing (TFL) Programming |
Yuping Wu,
Sayeed Nadim |
source |
4 |
| PharmaSUG |
2020 |
A Set of VBA Macros to Compare RTF Files in a Batch |
Jeff Xia,
Shunbing Zhao |
source |
6 |
| PharmaSUG |
2020 |
A Solution to Look-Ahead Observations |
Yongjiang (Jerry) Xu,
Yanhua (Katie) Yu |
source |
5 |
| PharmaSUG |
2020 |
A Tool to Organize SAS Programs, Output and More for a Clinical Study |
Yang Gao |
source |
10 |
| PharmaSUG |
2020 |
An Effective Management Approach for a First-Time Study Lead |
Himanshu Patel,
Jeff Xia |
source |
10 |
| PharmaSUG |
2020 |
An Overview of Medical Device Data Standards |
Shilpakala Vasudevan |
source |
5 |
| PharmaSUG |
2020 |
Analysis Package e-Submission - Planning and Execution |
Abhilash Chimbirithy,
Saigovind Chenna,
Majdoub Haloui |
source |
8 |
| PharmaSUG |
2020 |
Assessing Performance of Risk-based Testing |
Amber Randall,
Bill Coar |
source |
11 |
| PharmaSUG |
2020 |
Automation of Flowchart using SAS |
Xingshu Zhu,
Bo Zheng |
source |
9 |
| PharmaSUG |
2020 |
Calculation of Cochran-Mantel-Haenszel Statistics for Objective Response and Clinical Benefit Rates and the Effects of Stratification Factors |
Girish Kankipati,
Chia-Ling (Ally) Wu |
source |
8 |
| PharmaSUG |
2020 |
Challenges and solutions for e-data submission to PMDA even after submission to FDA |
Akari Kamitani,
HyeonJeong An,
Yura Suzuki,
Malla Reddy Boda,
Yoshitake Kitanishi |
source |
14 |
| PharmaSUG |
2020 |
Color Data Listings and Color Patient Profiles |
Charley Z. Wu |
source |
5 |
| PharmaSUG |
2020 |
Demographic Table and Subgroup Summary Macro %TABLEN |
Jeffrey P. Meyers |
source |
12 |
| PharmaSUG |
2020 |
Generating ADaM compliant ADSL Dataset by Using R |
Vipin Kumpawat,
Lalitkumar Bansal |
source |
9 |
| PharmaSUG |
2020 |
How to let Machine Learn Clinical Data Review as it can Support Reshaping the Future of Clinical Data Cleaning Process |
Mirai Kikawa,
Yuichi Nakajima |
source |
9 |
| PharmaSUG |
2020 |
Implementation of Immune Response Evaluation Criteria in Solid Tumors (iRECIST) in Efficacy Analysis of Oncology Studies |
Weiwei Guo |
source |
6 |
| PharmaSUG |
2020 |
Implementing Quality Tolerance Limits at a Large Pharmaceutical Company |
Steven A. Gilbert |
source |
13 |
| PharmaSUG |
2020 |
Macro To Produce Sas-Readable Table Of Content From Tlf Shells |
Igor Goldfarb,
Ella Zelichonok |
source |
18 |
| PharmaSUG |
2020 |
Metadata-driven Modular Macro Design for SDTM and ADaM |
Ellen (Zihui) Lin,
Aditya Tella,
Yeshashwini Chenna,
Michael Hagendoorn |
source |
9 |
| PharmaSUG |
2020 |
Moving A Hybrid Organization Towards CDISC Standardization |
Kobie O'Brian,
Sara Shoemaker,
Robert Kleemann,
Kate Ostbye |
source |
8 |
| PharmaSUG |
2020 |
One Boy's Dream: Hitting a Homerun in the Bottom of the Ninth Inning |
Carey G. Smoak |
source |
5 |
| PharmaSUG |
2020 |
Opening Doors for Automation with Python and REST: A SharePoint Example |
Michael Stackhouse |
source |
9 |
| PharmaSUG |
2020 |
Pattern Detection for Monitoring Adverse Events in Clinical Trials - Using Real Time, Real World Data |
Surabhi Dutta |
source |
20 |
| PharmaSUG |
2020 |
Preparing a Successful BIMO Data Package |
Elizabeth Li,
Carl Chesbrough,
Inka Leprince |
source |
20 |
| PharmaSUG |
2020 |
Principal Stratum strategy for handle intercurrent events: a causal estimand to avoid biased estimates |
Andrea Nizzardo,
Giovanni Marino Merlo,
Simona Scartoni |
source |
13 |
| PharmaSUG |
2020 |
PROC Future Proof; |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee |
source |
8 |
| PharmaSUG |
2020 |
R for Clinical Reporting, Yes - Let's Explore it! |
Hao Meng,
Yating Gu,
Yeshashwini Chenna |
source |
16 |
| PharmaSUG |
2020 |
Risk-based and Exposure-based Adjusted Safety Incidence Rates |
Qiuhong Jia,
Fang-Ting Kuo,
Chia-Ling (Ally) Wu,
Ping Xu |
source |
8 |
| PharmaSUG |
2020 |
SAS Migration from Unix to Windows and Back |
Valerie Williams |
source |
9 |
| PharmaSUG |
2020 |
SDSP: Sponsor and FDA Liaison |
Bhanu Bayatapalli,
Shefalica Chand |
source |
8 |
| PharmaSUG |
2020 |
Shell Script automation for SDTM/ADaM and TLGs |
Pradeep Acharya,
Aniket Patil |
source |
6 |
| PharmaSUG |
2020 |
Standard Analyses and Code Sharing Working Group Update |
Nancy Brucken,
Dante Di Tommaso,
Jane E. Marrer,
Mary Nilsson,
Jared Slain,
Hanming Tu |
source |
5 |
| PharmaSUG |
2020 |
Standardizing Patient Reported Outcomes (PROs) |
Charumathy Sreeraman |
source |
7 |
| PharmaSUG |
2020 |
Successful US Submission of Medical Device Clinical Trial using CDISC |
Phil Hall |
source |
6 |
| PharmaSUG |
2020 |
TDF - Overview and Status of the Test Data Factory Project, Standard Analyses & Code Sharing Working Group |
Nancy Brucken,
Peter Schaefer,
Jessica Dai,
Cynthia Stroupe,
Dante Di Tommaso |
source |
4 |
| PharmaSUG |
2020 |
Trial Sets in Human Clinical Trials |
Fred Wood |
source |
13 |
| PharmaSUG |
2020 |
Using SAS Simulations to determine appropriate Block Size for Subject Randomization Lists |
Kevin Venner,
Jennifer Ross,
Kyle Huber,
Noelle Sassany,
Graham Nicholls |
source |
10 |
| PHUSE US |
2020 |
A Case Study: Data Transparency of Clinical Trial Data |
Sherry Meeh |
source
presentation source |
8 |
| PHUSE US |
2020 |
A Collaborative Approach to Analysis Standards |
Margaret Merlino,
Marleen Nijs |
source
poster source |
5 |
| PHUSE US |
2020 |
A Journey Through End to End Data Flow |
Marcin Makowski,
Stayce Murray |
source
presentation source |
12 |
| PHUSE US |
2020 |
A Programmer's Journey through the BIMO Submission Process |
Raghavender Ranga |
source
presentation source |
12 |
| PHUSE US |
2020 |
A Visualization approach for Clinical Trials with Digital Data |
Siddharth Kumar Lokineni |
source
presentation source |
6 |
| PHUSE US |
2020 |
Accelerating Translational Research by Leveraging AI and Machine Learning |
Leveraging AI |
source
presentation source |
9 |
| PHUSE US |
2020 |
Adapting to Adaptive Clinical Trials [poster] |
Renu Shukla,
Wenmei Ge |
source |
1 |
| PHUSE US |
2020 |
An Interactive Visualization Application for Patient-reported Outcomes with Spotfire |
Matt Buckley |
source
presentation source |
5 |
| PHUSE US |
2020 |
Are we there yet? Evaluating new non-EDC data sources for clinical trial submission feasibility |
Vijay Pasapula |
source
presentation source |
6 |
| PHUSE US |
2020 |
Artificial Intelligence (AI)-enhanced Precision Medicine Drug Development |
Mohammad Afshar |
source |
9 |
| PHUSE US |
2020 |
Assessment of Machine Learning Methods in Coding of Concomitant Medications in Clinical Trials |
Sanna Herrgård,
Carla Gil,
Ingrid Holst,
John Holmer Nielsen |
source
presentation source |
8 |
| PHUSE US |
2020 |
Be the Master for a Master Protocol Study |
Ke Xiao |
source
poster source |
8 |
| PHUSE US |
2020 |
Big Lab Data at the Fingertips of the Statistical Reviewers Using R Shiny |
Mukul K Mittal,
Sarah Cannon |
source
presentation source |
8 |
| PHUSE US |
2020 |
CDISC's ADTTE Domain: Time-to-Event Analysis From a Programmer's Point of View |
Frieder Wolff,
Vitali Gering |
source
poster source |
8 |
| PHUSE US |
2020 |
Common Data Quality Issues Seen During FDA's JumpStart Service |
Aaron Belowich,
Andrea Arbelaez |
source
presentation source |
7 |
| PHUSE US |
2020 |
Common Sense Tips for Weaving Governance into an MDR |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE US |
2020 |
Connected Monitoring |
Mike Henderson |
source
presentation source |
6 |
| PHUSE US |
2020 |
Creating a Simplified TS Domain Using the R Shiny App |
Hanming Tu |
source
presentation source |
11 |
| PHUSE US |
2020 |
Data Exchange in Clinical Trial - Programming Perspective |
Chao Wang |
source
presentation source |
5 |
| PHUSE US |
2020 |
Data Load Automation |
Jennifer H. Desai |
source
presentation source |
4 |
| PHUSE US |
2020 |
Data Science Project (Educating for the Future Working Group) |
Aldir Medeiros Filho,
Sascha Ahrweiler |
source
presentation source |
10 |
| PHUSE US |
2020 |
Data Standards for eCOA in Clinical Trials |
Terek Peterson,
Franklin E. Menius |
source
presentation source |
6 |
| PHUSE US |
2020 |
Data Standards Used for Electronic Submission of Real-World Evidence in New Drug Application (NDA) |
Nicole Thorne,
Kathy Wu |
source
presentation source |
10 |
| PHUSE US |
2020 |
Data Wrangling - Combining and Restructuring QS-related ADaM Datasets for Pathway Predictive Modeling |
Stanley Brill |
source
poster source |
7 |
| PHUSE US |
2020 |
Data, Metadata and the notion of Holons* (* Information concepts) |
Peter Tormay |
source
presentation source |
7 |
| PHUSE US |
2020 |
Design and Conduct of Clinical Trials: Past Present and Future. New Innovative Technology Methods |
George Obsekov |
source
presentation source |
12 |
| PHUSE US |
2020 |
Digitalization of Clinical Study Report (CSR) Tables and Listings for Cross-report Verification |
Iraj Mohebalian,
Michael Badlani |
source
presentation source |
10 |
| PHUSE US |
2020 |
Disruption is Personal: RWE and AI Changing the Game for Personalized Medicine |
Arnab Goswami |
source
presentation source |
7 |
| PHUSE US |
2020 |
Dual Roles: I'm not just a programmer! |
Laura Williams,
Hunter Vega |
source
presentation source |
5 |
| PHUSE US |
2020 |
Efficacy ADaMs in Oncology - Step by Step (Dataset by Dataset) |
Ilya Krivelevich,
Ran Xie |
source
presentation source |
8 |
| PHUSE US |
2020 |
eSource Arising: Clinical Data Automation Possibilities Beyond Data Capture |
Sofie Stynen,
Annelies Van Zeveren |
source
presentation source |
8 |
| PHUSE US |
2020 |
Evolution of Clinical Data Disclosure and Transparency |
Sneha Paradkar |
source
presentation source |
8 |
| PHUSE US |
2020 |
Evolution of Data: From extraction to visualization |
Ashish Kumar |
source
presentation source |
11 |
| PHUSE US |
2020 |
FDA Study Data Guidance Update |
Ethan Chen |
source
presentation source |
6 |
| PHUSE US |
2020 |
FDA View: FDA Study Data |
Heather Crandall |
source |
6 |
| PHUSE US |
2020 |
Feedback to Feed Back |
Ankur Mathur,
Harper Forbes |
source
presentation source |
5 |
| PHUSE US |
2020 |
Get to the Bottom of Lab Toxicity Grading: Challenges and Implementation of CTCAE Version 5 |
Xiaoyin Zhong |
source
presentation source |
5 |
| PHUSE US |
2020 |
Getting e-Closer to Multi-Regional Clinical Trials |
Lily Ling,
Yuan Yuan Dong,
Yanhong Li |
source
presentation source |
5 |
| PHUSE US |
2020 |
Good Cooperation Between SAS and R for Regulatory Submission |
Jingyuan Chen |
source
presentation source |
8 |
| PHUSE US |
2020 |
Handling Missing Data in Clinical Trials: Techniques and Methods |
Pennidhi Karlakunta,
Naveen Kommuru |
source
presentation source |
9 |
| PHUSE US |
2020 |
How to Handle the Challenges for the Content of Specific Datasets in FDA Submission for HIV Drugs |
Fangfang Du |
source
presentation source |
6 |
| PHUSE US |
2020 |
How to reduce programming time for ADaM Creation? - Presenting STAG, a Tool Based Approach |
Diganta Bose |
source
presentation source |
16 |
| PHUSE US |
2020 |
Implementing New Technical Guidance: A Sponsor Experience with the April 2018 CBER Vaccine Guidance |
Liping Zhang,
Sandra VanPelt Ngyuen |
source
presentation source |
8 |
| PHUSE US |
2020 |
Incidence Rate - Incidence Proportion Prevalence Rate and Other Related Statistics |
Nadiia Pukhliar |
source
presentation source |
7 |
| PHUSE US |
2020 |
Industry Experiences Submitting Standardized Study Data to Regulatory Authorities |
Janet Low,
Vincent Guo |
source
presentation source |
12 |
| PHUSE US |
2020 |
Integration of Biomarkers Data in Clinical Trials |
Prakash Dev |
source
presentation source |
5 |
| PHUSE US |
2020 |
Is R language reliable and efficient tool for programming SAS datasets or just art for art's sake? |
Piotr Podlewski |
source
presentation source |
9 |
| PHUSE US |
2020 |
Lab Master List File Makes Easy |
Clio Wu |
source
presentation source |
7 |
| PHUSE US |
2020 |
Let Us Trace Back to the Beginning from the End |
Madhusudhan Reddy Papasani,
Swathi Kotla |
source
presentation source |
12 |
| PHUSE US |
2020 |
Life Science's Process and Artifact Generation Automation |
Lucky Singh |
source |
2 |
| PHUSE US |
2020 |
Machine Learning-AI is the Future - What Now? |
Priyanka Adusumilli,
Priyank Patel |
source
poster source |
8 |
| PHUSE US |
2020 |
Making the Invisible, Visible: People, Ideas and Conferences |
Gayathri Kolandaivelu |
source
poster source |
6 |
| PHUSE US |
2020 |
Managing Data Flow for Wearables, Apps and Sensors |
Mayur Tripathi,
Prashanth Jayadevamurthy |
source
presentation source |
4 |
| PHUSE US |
2020 |
Managing Simultaneous Drug Submissions with Breakthrough Designations - Lessons Learned from a Programming Perspective |
LiFeng Good |
source
presentation source |
6 |
| PHUSE US |
2020 |
Migrating to LSAF - The Danone Nutricia Research Journey |
Jean-Marc Ferran,
Paul Vervuren |
source
presentation source |
9 |
| PHUSE US |
2020 |
Natural Language Processing for Enhanced Treatment Decision |
Phani Ponnapalli,
Subrahmanyam Rayaprolu |
source
presentation source |
10 |
| PHUSE US |
2020 |
No more merging! (property graph database demystified) |
Alexey Kuznetsov |
source
presentation source |
11 |
| PHUSE US |
2020 |
Opening Doors for Automation with Python and REST: A SharePoint Example |
Michael Stackhouse |
source
presentation source |
9 |
| PHUSE US |
2020 |
Overcoming Hurdles in Clinical Programming Project Management Using Microsoft Teams |
Miten Tiwari |
source
presentation source |
11 |
| PHUSE US |
2020 |
Patient Privacy - The Topmost Priority! |
Shiva Gogu |
source
presentation source |
6 |
| PHUSE US |
2020 |
Population PK Dataset: Basic Concepts and Challenges from the Perspective of a SAS Programmer |
Namrata Pokhrel |
source
presentation source |
12 |
| PHUSE US |
2020 |
Programmer to SME - Career Game Changer |
Divya Cetlur,
Ephicacy Lifescience |
source
presentation source |
7 |
| PHUSE US |
2020 |
Quarterly Safety Reporting: Timely Analysis of Clinical Safety Data Using Qlik Sense Software |
Yvonne Denkins |
source
presentation source |
8 |
| PHUSE US |
2020 |
R Package Oriented Software Development Life Cycle in Regulated Clinical Trial Environments |
Rinki Jajoo,
Yalin Zhu |
source
presentation source |
12 |
| PHUSE US |
2020 |
SPA - A catalyst for clinical protocol development |
Suhas Giriraj,
Ephicacy Lifescience |
source
presentation source |
5 |
| PHUSE US |
2020 |
Spotfire Patient Profile Graphs: An Abridged Effective Approach Using Scripting Languages |
Anish Kuriachen |
source
presentation source |
12 |
| PHUSE US |
2020 |
Standards Compliance - An Automated Way to Measure the Interoperability of Clinical Studies |
Rammprasad Ganapathy |
source
presentation source |
6 |
| PHUSE US |
2020 |
Statistical Analysis in an Oncology Study for PCWG3 Patients [poster] |
Tony Tian |
source |
1 |
| PHUSE US |
2020 |
The Importance of General Linear Models (GLMs) in Clinical Research |
Ritesh Dhimmar,
Venkata Ikkurthy |
source |
12 |
| PHUSE US |
2020 |
Update on the PHUSE Standard Analyses & Code Sharing Working Group |
Jane E. Marrer |
source
poster source |
1 |
| PHUSE US |
2020 |
Using Graph Technology for Metadata-driven Clinical Development |
Frederik Malfait |
source |
6 |
| PHUSE US |
2020 |
Virtual Assistant for Conversational Experience with Clinical Data |
Amit Gulwadi,
Srinivasan Anandakumar |
source |
6 |
| PHUSE US |
2020 |
Visualizing Clinical Trial Design and Results in 20 Graphical Displays - Achieving 20-20 in 2020 |
Munish Mehra |
source
presentation source |
20 |
| PHUSE US |
2020 |
What You Need to Know About Submitting Data to the FDA |
Pritesh Solanki,
Janet Low |
source
presentation source |
7 |
| PHUSE EU |
2019 |
A Data-driven and cost-effective approach towards Risk Based Monitoring |
Vineet Jain |
source
presentation source |
7 |
| PHUSE EU |
2019 |
A Three-pronged Approach to Central Monitoring to Identify Potential Risks and Ensure Data Quality |
Jill Ophoff |
source
presentation source |
5 |
| PHUSE EU |
2019 |
ADaM-based Centralised Monitoring |
Christian S. Christensen |
source
presentation source |
3 |
| PHUSE EU |
2019 |
Addressing the Gap in Data Standards: Introducing the Aggregation Layer |
Claudio Garutti,
Marko Bomyer |
source
presentation source |
11 |
| PHUSE EU |
2019 |
ADSL - Friend or Foe? |
Jørgen Mangor Iversen |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Analysis of composite endpoints using the Win-Ratio method in SAS |
Murat Ipek |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Automated Review of Metadata Standards, Data Checks and Trend Visualisation |
Giuseppe Di Monaco |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Building a F.A.I.R. Foundation for Pharma: The PHUSE GoingTWLD Project |
Tim P. Williams,
Armando Oliva |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Challenges Involved with Using Legacy Clinical Trial Study Data During Integration |
Adebola Opasanya |
source
poster source |
8 |
| PHUSE EU |
2019 |
Considerations When Representing Multiple Subject Enrollments in SDTM |
Kristin Kelly,
Blue Bell |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Data Everywhere: What Does Risk-based Monitoring Mean for Data Management? |
Swapna Pothula |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Deconstructing SDTM - Starting Again |
Johannes Ulander |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Deep Sequencing |
Koen Ven,
Chantal Kersten |
source
presentation source |
10 |
| PHUSE EU |
2019 |
Design, Develop, Test and Document an R Package for Enrolment Modeling |
Stephen Gormley |
source
presentation source |
14 |
| PHUSE EU |
2019 |
Development of standard BIMO process to create clinsite dataset |
Hilde Delanghe |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Dose-finding Schemes in Clinical Trials |
Michael Brockmann |
source
presentation source |
15 |
| PHUSE EU |
2019 |
Early experiences using SDTM to organize clinical data collected using a physical activity tracker |
Martin Gram,
Gianluca Mortari |
source
presentation source |
13 |
| PHUSE EU |
2019 |
Educating for the Future: Data Engineering Techniques |
Guy R. Garrett |
source
presentation source |
10 |
| PHUSE EU |
2019 |
FAIR Data Standards in the GDSR |
Huw Mason |
source
poster source |
4 |
| PHUSE EU |
2019 |
Finding the Right Balance - Data Management Surveillance in a Fully Outsourced Partnership Model |
Konstanze Morgenroth |
source
presentation source |
11 |
| PHUSE EU |
2019 |
Holon - What, Why and How |
Catharina Dahlbo,
Eva Kelty |
source
poster source |
7 |
| PHUSE EU |
2019 |
How Will You Use CDISC Library? |
Sally Cassells |
source
presentation source |
6 |
| PHUSE EU |
2019 |
Integrated Data and Document Anonymisation for Efficient Data Sharing [presentation] |
Ali Dootson,
Cathal Gallagher |
source |
27 |
| PHUSE EU |
2019 |
Janssen Autism Knowledge Engine (JAKE) System in Autism Spectrum Disorder |
Sarah Bonneux |
source
poster source |
3 |
| PHUSE EU |
2019 |
Janssen's Journey Towards a Culture of Innovation |
Sumesh Kalappurakal,
Sangeeta Bhattacharya |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Laboratory Data: Issues with Myultiple Reference Ranges and Methods of Normalisation |
Jessica Hoegg,
Laura Marquis |
source
presentation source |
20 |
| PHUSE EU |
2019 |
Linked Data URIs [poster] |
Kerstin Forsberg,
Johannes Ulander |
source |
1 |
| PHUSE EU |
2019 |
Linked Data: Introduction and Deep Dive |
Nicolas Dupuis |
source
presentation source |
11 |
| PHUSE EU |
2019 |
Medical Device SDTM: A Real Case |
Roberto Teli |
source
poster source |
5 |
| PHUSE EU |
2019 |
Migrating to LSAF - Danone Nutricia Research's Journey |
Paul Vervuren,
Jean-Marc Ferran |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Mixed Model Repeated Measures (MMRMs) |
Mrudula Suryawanshi |
source
presentation source |
19 |
| PHUSE EU |
2019 |
MODERN ANALYTICS WITHIN AN OPEN SOURCE FRAMEWORK |
Sam Warden |
source
poster source |
4 |
| PHUSE EU |
2019 |
Navigating FDA Requirements: ISS/ISE Build Strategies |
Priyank Patel |
source |
9 |
| PHUSE EU |
2019 |
Oracle Analytics Cloud |
Mike Collinson |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Overcoming Hurdles in Clinical Programming Project Management Using Microsoft Teams |
Yan Wu,
Sofie Cambré |
source
presentation source |
11 |
| PHUSE EU |
2019 |
Pharmacokinetic and Statistical Considerations in First-in-Human Clinical Trials |
Joanna Magielse |
source
presentation source |
4 |
| PHUSE EU |
2019 |
Poster PP25 An Algorithm for Prioritizing Time Constrained Clinical Trial Activities |
Andy Richardson |
source
poster source |
7 |
| PHUSE EU |
2019 |
Processing big data from multiple sources |
Berber Snoeijer |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Quality Control and Validation - More Than Just PROC COMPARE |
Evgeny Starostin |
source
poster source |
7 |
| PHUSE EU |
2019 |
R you ready for Simulo: a user-friendly clinical trial simulator |
Quentin Leirens,
SGS Exprimo,
Nicolas Luyckx,
SGS Exprimo,
Bruno Speder,
SGS Exprimo |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Semi Auto-generated Narratives |
Bjarke Klein |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Speed Breaker, Traffic Signal and Toll Gates of a Highway Journey of a Sponsor-Vendor Relationship |
Anik Chatterjee,
Anusuiya Ghanghas |
source
poster source |
4 |
| PHUSE EU |
2019 |
Statistical Programming in the Future - Our Mindset, Data FAIRness and the Importance of Stakeholder Relationships |
Christoph Ziegler |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Structured Clinical Development - Using a Digitized Study Design and Planning to Drive Process Automation |
Djenan Ganic |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Sub-population Detection Using Graph-based Machine Learning |
Sergey Glushakov,
Kostiantyn Drach |
source |
28 |
| PHUSE EU |
2019 |
The Impact of AI, RWE, Precision Medicine and Mobile Health Technology on Streamlined Clinical Trials |
Stijn Rogiers,
Olivier Bouchard |
source
presentation source |
11 |
| PHUSE EU |
2019 |
The Importance of Sleep and How Best to Measure It [presentation] |
Neil Stanley |
source |
122 |
| PHUSE EU |
2019 |
The Promise of Wearable Technology in Clinical Trials: A Proof of Concept to Deliver it? |
Jennifer Bradford |
source
presentation source |
11 |
| PHUSE EU |
2019 |
TS does not mean T(o) S(uffer) - A hands-on guideline for a better understanding of the TS domain |
Kristina Zweier |
source
presentation source |
14 |
| PHUSE EU |
2019 |
Using Natural Language Processing to transform real world data |
Jane Reed,
Thierry Breyette |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Utilising RWD and RWE: An Introduction to Core Concepts and Requirements |
Christopher C. Hurley,
Aditya Gadiko |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Vaccines: Benefits for public health Statistical programming specificities in clinical trials |
Olfa Guaddoudi,
Emeline Burhin,
Julie Harriague,
Mohamed Oujaa |
source
poster source |
7 |
| PHUSE EU |
2019 |
Validate the validated: A python script for study leads to review clinical outputs |
Varaprasad Ilapogu |
source
presentation source |
6 |
| PHUSE EU |
2019 |
Validating R functions against SAS outputs: How RTest can build a bridge allowing to validate R |
Sebastian Wolf |
source
presentation source |
6 |
| PHUSE EU |
2019 |
Work Less - Do More: An Automated Approach to Define-XML Validation |
Kai Wanke |
source
presentation source |
8 |
| SESUG |
2019 |
ePRO: A View from Statistical Programmer |
Vijetha Kode,
Saigovind Chenna |
source |
18 |
| SESUG |
2019 |
Extending the Finkelstein-Schoenfeld test and Win Ratio to three composite Outcomes Using SAS |
Matheos Yosef,
Shokoufeh Khalatbari,
Scott Hummel |
source |
4 |
| SESUG |
2019 |
One Click to Analysis Results Metadata |
Srivathsa Ravikiran,
Priscilla Gathoni |
source |
18 |
| SESUG |
2019 |
Utilizing SAS Functions to Generate Accurate Adherence Notifications for Clinical Trials |
Lishu Zhang,
Jiu Zhao |
source |
7 |
| SESUG |
2019 |
Who, When, and Where - A Step-by-Step Approach to Creating a Color-Coded Tracker for Clinical Trial Subjects |
Venita DePuy |
source |
18 |
| MWSUG |
2019 |
Sample Size and Design Considerations in Studies Assessing Non-Inferiority using Continuous Outcomes |
Michael G. Wilson |
|
19 |
| MWSUG |
2019 |
Utilizing Macros to Create Patient Site Matching via Zip-Code Radiuses |
Kathryn Schurr |
|
15 |
| WUSS |
2019 |
A Fun (if Snarky) Look at SAS Certification Exams |
Aaron Brown |
source |
4 |
| WUSS |
2019 |
A Strategy for Dealing with Pinnacle 21 Errors and Warnings |
Carey G. Smoak |
source |
2 |
| WUSS |
2019 |
Bespoke outputs, just like everyone else's: using the SAS Macro Language to create template programs for standard presentations of your client's clinical trial data |
Sean-Paul A. Claypool |
source |
9 |
| WUSS |
2019 |
One Boy's Dream: Hitting a Homerun in the Bottom of the Ninth Inning |
Carey G. Smoak |
source |
5 |
| WUSS |
2019 |
Python applications in SAS programming for medical device clinical trial studies |
Jianlin Li |
source |
7 |
| WUSS |
2019 |
Spec to Code in Seconds: Use Microsoft Excel for Repetitive Code Writing |
Pinky Anandani Dutta |
source |
5 |
| WUSS |
2019 |
Validate the validated: A python script for study leads to review clinical outputs |
Varaprasad Ilapogu |
source |
6 |
| PharmaSUG |
2019 |
A Cloud-based Framework for Exploring Medical Study Data |
Peter Schaefer |
source |
10 |
| PharmaSUG |
2019 |
A Practical SAS Macro for Converting RTF to PDF Files |
Kaijun Zhang,
Xiao Xiao,
Brian Wu |
source |
7 |
| PharmaSUG |
2019 |
An Innovative Efficacy Table Programming to Automate Its Figure Generation to Ensure Both High Quality and Efficiency |
Xiangchen (Bob) Cui,
Letan (Cleo) Lin |
source |
23 |
| PharmaSUG |
2019 |
Application of Criterion I2 in Clinical Trials Using SAS |
Igor Goldfarb,
Mitchell Kotler |
source |
6 |
| PharmaSUG |
2019 |
Artificial Intelligence and Real World Evidence - it takes two to tango |
Charan Kumar Kuyyamudira Janardhana |
source |
9 |
| PharmaSUG |
2019 |
Automate the Mundane: Using Python for Text Mining |
Nathan Kosiba |
source |
5 |
| PharmaSUG |
2019 |
Automate the Process to Ensure the Compliance with FDA Business Rules in SDTM Programming for FDA Submission |
Xiangchen (Bob) Cui,
Hao Guan,
Min Chen,
Letan (Cleo) Lin |
source |
16 |
| PharmaSUG |
2019 |
Automating SAS Program Table of Contents for Your FDA Submission Package |
Lingjiao Qi,
Bharath Donthi |
source |
14 |
| PharmaSUG |
2019 |
Begin with the End of Validation: Adapting QbD Approach in Statistical Programming to Achieve Quality and Compliance Excellence |
Linghui Zhang |
source |
8 |
| PharmaSUG |
2019 |
Best Practices for ISS/ISE Dataset Development |
Bharath Donthi,
Lingjiao Qi |
source |
9 |
| PharmaSUG |
2019 |
Building Automations for Generating R and SAS Code Supporting Visualizations Across Multiple Therapeutic Areas |
Anastasia Alexeeva,
Mei Zhao,
William Martersteck |
source |
11 |
| PharmaSUG |
2019 |
Camouflage your Clinical Trial with Machine Learning and AI |
Ajith Baby Sadasivan,
Limna Salim,
Akhil Vijayan,
Anoop Ambika |
source |
10 |
| PharmaSUG |
2019 |
China NMPA (National Medical Products Administration) reform and new regulations/guidelines/requirements |
Yi Yang |
source |
11 |
| PharmaSUG |
2019 |
Clinical Development Standards for FDA Bioresearch Monitoring (BIMO) Submissions |
Denis Michel,
Julie Maynard |
source |
11 |
| PharmaSUG |
2019 |
Considerations When Representing Multiple Subject Enrollments in SDTM |
Kristin Kelly,
Mike Hamidi |
source |
8 |
| PharmaSUG |
2019 |
Define-XML with ARM |
Lei Jing,
Chao Wang |
source |
8 |
| PharmaSUG |
2019 |
Designing Flexible Data Standards Models |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2019 |
Developing Custom SAS Studio Tasks for Clinical Trial Graphs |
Olivia Wright,
Sanjay N. Matange |
source |
15 |
| PharmaSUG |
2019 |
Do-It-Yourself CDISC! A Case Study of Westat's Successful Implementation of CDISC Standards on a Fixed Budget |
Richard M. Mitchell,
Rachel Brown,
Jennifer K. Fulton,
Stephen Black,
Marie Byrd Alexander |
source |
6 |
| PharmaSUG |
2019 |
Don't Just Rely on Processes; Support Local Subject Matter Expertise |
Deidre Kreifels,
Steven R. Kirby,
Mario Widel |
source |
7 |
| PharmaSUG |
2019 |
Enhancing Randomization Methodology Decision-Making with SAS Simulations |
Kevin Venner,
Jennifer Ross,
Kyle Huber,
Graham Nicholls |
source |
15 |
| PharmaSUG |
2019 |
Equivalence, Superiority and Non-inferiority with Classical Statistical Tests: Implementation and Interpretation |
Marina Komaroff |
source |
7 |
| PharmaSUG |
2019 |
Experiences in Building CDISC Compliant ADaM Dataset to Support Multiple Imputation Analysis for Clinical Trials |
Xiangchen (Bob) Cui |
source |
20 |
| PharmaSUG |
2019 |
F2Plots: Visualizing relative treatment effects in cancer clinical trials |
Yellareddy Badduri |
source |
9 |
| PharmaSUG |
2019 |
Forewarned is forearmed or how to deal with ADSL issues |
Anastasiia Oparii |
source |
16 |
| PharmaSUG |
2019 |
Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies |
Mai Ngo,
Mary Grovesteen,
Vaughn Eason |
source |
8 |
| PharmaSUG |
2019 |
Innovative Technologies utilization in 21st Novel Clinical Research programs towards Generation of Real World Data. |
Srinivasa Rao Mandava |
source |
6 |
| PharmaSUG |
2019 |
Interactive TLFs - A Smarter Way to Review your Statistical Outputs |
Bhavin Busa |
source |
5 |
| PharmaSUG |
2019 |
Jump Start your Oncology knowledge |
Xiaoyin Zhong,
Feng Liu |
source |
9 |
| PharmaSUG |
2019 |
Large-scale TFL Automation for regulated Pharmaceutical trials using CDISC Analysis Results Metatadata (ARM) |
Stuart Malcolm |
source |
16 |
| PharmaSUG |
2019 |
Lessons Learned from Teaching 250+ Life Science Analytics (LSAF) Classes to Our Colleagues at Janssen Research and Development. |
Margie Merlino,
Jeanne Keagy |
source |
7 |
| PharmaSUG |
2019 |
Merging Sensor Data with Patient Records in Clinical Trials - Systems and Benefits |
Surabhi Dutta,
Shubhranshu Dutta |
source |
9 |
| PharmaSUG |
2019 |
Metadata Repository V1.0 - A Case Study in Standards Governance |
Aparna Venkataraman |
source |
7 |
| PharmaSUG |
2019 |
Minimally Invasive Surgery to Merge Data |
Paul D. Hamilton |
source |
4 |
| PharmaSUG |
2019 |
Multiple Studies BIMO Submission Package - A Programmer's Perspective |
Ramanjulu Valluru,
Harsha Dyavappa |
source |
17 |
| PharmaSUG |
2019 |
Next Innovation in Pharma - CDISC data and Machine Learning |
Kevin Lee |
source |
5 |
| PharmaSUG |
2019 |
Non-Clinical (SEND) Reference Guide for Clinical (SDTM) Programmers |
Dharmendra Tirumalasetti,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2019 |
Pacemaker Guy: De-Mystifying a Business Use Case for SDTM Standard and Medical Device Domains |
Carey G. Smoak,
Donna Sattler,
Fred Wood |
source |
10 |
| PharmaSUG |
2019 |
Patient Profile with Color-Coded Track Changes Since Last Review |
Himanshu Patel,
Jeff Xia |
source |
6 |
| PharmaSUG |
2019 |
Performing Analytics on Free-Text Data Fields: A Programer-s Wurst Nitemare |
Michael S Rimler,
Matt Pitlyk |
source |
18 |
| PharmaSUG |
2019 |
Pharmacokinetic Parameters for Sparse and Intensive Sampling - Nonclinical and Clinical Studies |
Shallabh Mehta |
source |
5 |
| PharmaSUG |
2019 |
Practical Perspective in Sample Size Determination |
Bill Coar |
source |
16 |
| PharmaSUG |
2019 |
Project Management Fundamentals for Programmers and Statisticians |
Jennifer Sniadecki |
source |
19 |
| PharmaSUG |
2019 |
Raw data sets tracker: Time and project management based on the volume of available clinical data using SAS software |
Girish Kankipati |
source |
10 |
| PharmaSUG |
2019 |
Sample Size Determination with SAS Studio |
Bill Coar |
source |
13 |
| PharmaSUG |
2019 |
SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials |
Lingling Li |
source |
11 |
| PharmaSUG |
2019 |
SHIONOGI Global SAS System Renewal Project - How to Improve Statistical Programming Platform |
Yura Suzuki,
Yoshimi Ishida,
Malla Reddy Boda,
Yoshitake Kitanishi |
source |
10 |
| PharmaSUG |
2019 |
SMQ SAS Dataset Macro |
Mi Young Kwon,
Ishan Shah |
source |
12 |
| PharmaSUG |
2019 |
Sponsor Considerations for Building a Reviewer's Guide to Facilitate BIMO (Bioresearch Monitoring) Review |
Kiran Kumar Kundarapu,
Janet Low,
Majdoub Haloui |
source |
5 |
| PharmaSUG |
2019 |
Sponsor oversight: Proof is in the documents |
Shailendra Phadke |
source |
4 |
| PharmaSUG |
2019 |
Statistical application in Image Processing by Integrating C and SAS |
Vidhyavathi Venkataraman,
Srinand Ponnathapura Nandakumar,
Anupama Datta |
source |
11 |
| PharmaSUG |
2019 |
Statistical Assurance in SAS: An Introduction and User-s Guide |
Jonathan L Moscovici,
Milena Kurtinecz |
source |
8 |
| PharmaSUG |
2019 |
Strategy to Evaluate the Quality of Clinical Data from CROs |
Charley Z. Wu |
source |
7 |
| PharmaSUG |
2019 |
The Anatomy of Clinical Trials Data: A Beginner's Guide |
Venky Chakravarthy |
source |
14 |
| PharmaSUG |
2019 |
The Application of SAS-Excel Handshake in DDT |
Maggie Ci Jiang |
source |
7 |
| PharmaSUG |
2019 |
The Need for Therapeutic Area User Guide Implementation |
Michael Beers |
source |
8 |
| PharmaSUG |
2019 |
This Paper focuses on CDISC Questionnaires, Ratings and Scales (QRS) supplements and types of FDA Clinical Outcome Assessments |
Shrishaila Patil |
source |
10 |
| PharmaSUG |
2019 |
Throw Away the Key: Blockchain-ed Healthcare Data |
Kathy Zhai |
source |
5 |
| PharmaSUG |
2019 |
What-s New in the SDTMIG v3.3 and the SDTM v1.7 |
Fred Wood |
source |
13 |
| PharmaSUG |
2019 |
Working Remotely - Home Office, Tools and Technology |
Gary E. Moore |
source |
25 |
| SGF |
2019 |
Interaction between SAS and Python for Data Handling and Visualization |
Yohei Takanami |
source |
22 |
| SGF |
2019 |
Make SAS Viya Realize Strategic Data Science - Data Governance, AI Platform and AI SAS Programmer |
Ryo Kiguchi,
Katsunari Hirano,
Yoshitake Kitanishi |
source |
8 |
| SGF |
2019 |
Real-World Evidence and Population Health Analytics: Intersection and Application |
David Olaleye |
source |
16 |
| SGF |
2019 |
Sample Size Determination with SAS Studio |
William Coar |
source |
13 |
| SGF |
2019 |
Time Travel into the Future of Clinical Trial Enrollment Design |
Bahar Biller,
Anup Mokashi,
Ivan Oliveira,
Sharmin Pathan,
Jinxin Yi,
Jim Box |
source |
17 |
| SGF |
2019 |
Utilization of Python in Clinical Study by SASPy |
Yuichi Nakajima |
source |
15 |
| PHUSE US |
2019 |
A Future 'View' of Digital Data from Wearable Devices |
Daniel Schramek |
source
presentation source |
11 |
| PHUSE US |
2019 |
A Paradigm Shift to Represent and Manage Clinical Data Standards for Creating Data-driven Specification |
Veena Nataraj |
source
presentation source |
9 |
| PHUSE US |
2019 |
Achieving Data Integrity in Clinical Trials Utilizing Blockchain Technology |
Premanand Kumaravel |
source
poster source |
5 |
| PHUSE US |
2019 |
Adverse Events of Special Interest (AESI) Tabulation |
Chuanfeng Shih |
source
presentation source |
5 |
| PHUSE US |
2019 |
An Antidote for Huge Clinical Trial Data Processing: Enclosing Hash in FCMP |
Premanand Kumaravel |
source
presentation source |
8 |
| PHUSE US |
2019 |
An Open Clinical Data Quality Framework |
Vineet Jain |
source
presentation source |
11 |
| PHUSE US |
2019 |
Applying Risk Based Approach to Portfolio Management |
Chandi Kodthiwada |
source
presentation source |
4 |
| PHUSE US |
2019 |
Brand Yourself - Don't Become a Blackberry [presentation] |
Sangeeta Bhattacharya |
source |
16 |
| PHUSE US |
2019 |
CDISC Doesn't Tell You What to Collect But Regulators Do! |
Diane Wold |
source
presentation source |
4 |
| PHUSE US |
2019 |
CDISC in Phase I/II Studies: Case Studies in Adopting Standards |
Emily Woolley,
Amber Randall Scharp |
source
presentation source |
7 |
| PHUSE US |
2019 |
CDISC Rules + FDA Requests + PMDA Requirements = Guaranteed Compliance? |
Deborah Goodfellow,
Mario Widel |
source |
9 |
| PHUSE US |
2019 |
Clinical Trials on Blockchain |
Rohit Banga,
Mohit Juneja |
source
presentation source |
8 |
| PHUSE US |
2019 |
Considerations for Using CDISC Standards in Observational Studies |
Jonathan Neville |
source
presentation source |
5 |
| PHUSE US |
2019 |
Considerations When Representing Multiple Subject Enrollments in SDTM |
Kristin Kelly |
source
presentation source |
6 |
| PHUSE US |
2019 |
Creating the Virologic Response ADaM Dataset |
Manjusha Alapati |
source
presentation source |
7 |
| PHUSE US |
2019 |
Dashboarding Analytics for Oncology Endpoint Data Using SAS |
Vidya Muthukumar |
source
presentation source |
7 |
| PHUSE US |
2019 |
Data Engineering Project (Educating for the Future PHUSE Working Group) |
Guy R. Garrett,
Bev Hayes |
source
presentation source |
5 |
| PHUSE US |
2019 |
Development of a Risk-based Monitoring (RBM) Visualization Application Interface Using JMP Scripting |
Dongsun Cao,
Bhargava Reddy |
source
presentation source |
13 |
| PHUSE US |
2019 |
Digital Analysis Results - #killTFLs |
Chris Decker |
source
presentation source |
6 |
| PHUSE US |
2019 |
Don't Let Your Data Handle You: A Novel Approach to Clinical Programming |
Jorine Putter |
source
presentation source |
10 |
| PHUSE US |
2019 |
Ensuring Consistent and Supported Standards Across Data and Metadata in a Large Regulatory Filing is Tricky Business |
Lisa Kaye Brooks |
source
presentation source |
10 |
| PHUSE US |
2019 |
High-quality Study Data Standards for Submission |
Majdoub Haloui,
Ellen L. Asam |
source
presentation source |
9 |
| PHUSE US |
2019 |
Impact of SEND Data on FDA Review of Nonclinical Studies |
Kevin Snyder,
Matthew Whittaker |
source
presentation source |
6 |
| PHUSE US |
2019 |
Interactive Exploratory Analysis and Visualization for Late-phase Clinical Data |
Sheng-Wei Wang,
Casey Yang |
source
presentation source |
9 |
| PHUSE US |
2019 |
Make the Most of Your Data - Explore Different Perspectives |
Catharina Dahlbo,
Michael Rubison |
source
poster source |
5 |
| PHUSE US |
2019 |
Making the Case for Metadata Development |
Mike Molter |
source
presentation source |
7 |
| PHUSE US |
2019 |
Managing Complexity Towards Submission |
Johannes Ulander |
source
presentation source |
26 |
| PHUSE US |
2019 |
Maximizing the Use of Patient Data Warehouse via Visual Analytics |
Sandy Lei,
Simon Alex |
source
presentation source |
7 |
| PHUSE US |
2019 |
Metadata-driven Automation in Drug Research |
Hanming Tu,
Zhongping Lin |
source
presentation source |
13 |
| PHUSE US |
2019 |
Misuse and Misapplication in Statistical Data Analysis - A Topic that Never Goes Out of Style |
Corinna Miede |
source
presentation source |
12 |
| PHUSE US |
2019 |
New Drug Development Paradigm [presentation] |
Francis Kendall,
Cytel |
source |
33 |
| PHUSE US |
2019 |
Next Generation Data Management: Case Studies for Ontology-driven Graph Databases |
Jim Lapointe |
source
presentation source |
8 |
| PHUSE US |
2019 |
Organize and Report Your Clinical Data Today! |
Michael Litzsinger |
source
presentation source |
7 |
| PHUSE US |
2019 |
Practical Implementation of Central Statistical Surveillance in Clinical Trials |
Giordano Lo Regio |
source
presentation source |
3 |
| PHUSE US |
2019 |
Proof of Concept (PoC) Development of Safety Visual Analytics (SVA) Using R Shiny and SAS |
Rinki Jajoo |
source
presentation source |
9 |
| PHUSE US |
2019 |
R Markdown for Reproducible Research |
Cole Arendt |
source
presentation source |
15 |
| PHUSE US |
2019 |
Removing Silos: Placing Data at the Center |
David Iberson-Hurst |
source
presentation source |
9 |
| PHUSE US |
2019 |
Simulo - A User-friendly Platform for Model-based Simulations |
Nicolas Luyckx,
Quentin Leirens |
source
presentation source |
7 |
| PHUSE US |
2019 |
Statistical Models of Risk Flux Reveal Dynamics of RBM-managed Clinical Trials |
Michael Farnum |
source
presentation source |
12 |
| PHUSE US |
2019 |
Streamline Process: To Generate SDTM Programs by Automation |
Hemalatha Elumalai |
source
poster source |
8 |
| PHUSE US |
2019 |
Streamlining the Results Reporting for ClinicalTrials.gov and EudraCT |
Naresh Tulluru,
Susruth Ganoothula |
source
presentation source |
7 |
| PHUSE US |
2019 |
Striking a Balance: Adoption of Analysis Results Metadata (ARM) in Early Development Studies |
Janet Low,
Pranab K. Mitra |
source
presentation source |
6 |
| PHUSE US |
2019 |
Submission of Software Programs to Regulatory Agencies |
Maria Dalton |
source
presentation source |
10 |
| PHUSE US |
2019 |
The EMA, Health Canada and the FDA: Three Agencies Tackle Data Sharing, Synergies and Differences |
Jean-Marc Ferran |
source
presentation source |
19 |
| PHUSE US |
2019 |
The Future of the Digitalized Data Flow |
Silas McKee,
Michel Rider |
source
presentation source |
3 |
| PHUSE US |
2019 |
The Implementation of Spotfire in Clinical Trials to Review Safety and Patient Reported Outcomes Data |
Jingyuan Chen,
Wenyi Liu |
source
presentation source |
6 |
| PHUSE US |
2019 |
The Last Time? Efficiently Scheduling the Pieces of Your Submission Deliverables |
Charity Quick,
Emily Canosa |
source
poster source |
5 |
| PHUSE US |
2019 |
The Need for Therapeutic Area User Guide Implementation |
Michael Beers |
source
presentation source |
7 |
| PHUSE US |
2019 |
The Power of Sharing Clinical Data: Real Projects with Real Impacts |
David Handelsman |
source
presentation source |
6 |
| PHUSE US |
2019 |
Today's Standards Governance: Getting a Boost from Leveraging an MDR |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE US |
2019 |
Using an MDR to Manage Your Lab Test Definitions |
Daniel Ringenbach,
Roopa Kandukuri |
source
presentation source |
7 |
| PHUSE US |
2019 |
Using Count-based Statistical Models for Key Performance Indicators, Risk Metrics, etc. [presentation] |
Aaron Mackey |
source |
15 |
| PHUSE US |
2019 |
Using R to Query Datasets from a SAS Server and Generate Different Kinds of Graphs in a Clinical Study |
Jei Li |
source
poster source |
4 |
| PHUSE US |
2019 |
Using Study Metrics to Monitor Several Aspects of Clinical Studies Virtually Real Time |
Julio Ruiz |
source
presentation source |
6 |
| PHUSE US |
2019 |
Utilizing Artificial Intelligence for Efficient CRF Design |
Komal Govil,
Sai Vundela |
source
presentation source |
5 |
| PHUSE US |
2019 |
ValueListDefs, MethodDefs and WhereClauses: How to Define Data Traceability in a Metadata Repository |
Judith Goud |
source
presentation source |
11 |
| PHUSE US |
2019 |
Visualizing Oncology Data Through Interactive Dashboards |
Vikram Chanduri,
Bhavin Busa |
source
presentation source |
5 |
| PHUSE US |
2019 |
Voice-based Clinical Monitoring Assistant |
Anoop Ambika |
source
presentation source |
7 |
| PHUSE EU |
2018 |
A Learned Approach to CDISC Specifications |
Stephen M. Noga,
Brandon L. Welch,
Jeffrey M. Abolafia |
source
presentation source |
9 |
| PHUSE EU |
2018 |
Adverse Event Data - gRaphically |
Lina Rajput,
Prajakta Chitale |
source
presentation source |
10 |
| PHUSE EU |
2018 |
APESS: A Unified Methodology for the Development and Review of Quantitative Analysis SOPs |
Andy Richardson,
Anthony Rossinin |
source
presentation source |
7 |
| PHUSE EU |
2018 |
AstraZeneca Early Clinical Biometrics Journey into Integrated Clinical Data Environment |
Ruhul Amin,
Per-Arne Stahl |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Automated Creation of Submission-Ready Artifacts [presentation] |
Silas McKee,
Lourdes Devenney |
source |
15 |
| PHUSE EU |
2018 |
Bridging the Visual Analytics-EDC Gap to Accelerate Centralised Data Monitoring |
Luis Torres |
source
presentation source |
4 |
| PHUSE EU |
2018 |
Central Statistical Surveillance in Clinical Trials |
Kris Lauwers,
Giordano Lo Regio |
source
presentation source |
2 |
| PHUSE EU |
2018 |
Clinical Trials on Blockchain |
Rohit Banga,
Mohit Juneja |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Data Engineering Project (Educating for the Future PHUSE Working Group) |
Guy R. Garrett,
Bev Hayes |
source
presentation source |
14 |
| PHUSE EU |
2018 |
Data Transparency - Breaking Down Data Silos for Improved Insight |
Peter Tormay,
Anna Berg |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Developing an End-to-End Standard and Automated Risk-based Monitoring Process |
Giuseppe Di Monaco,
Tim P. Williams |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Disruption Leads to Innovation: We Must Learn New Things! |
Chris Decker,
Ali Dootson |
source
presentation source |
8 |
| PHUSE EU |
2018 |
eSource to SDTM: Trade-offs and Pay-offs |
Donald Benoot,
Swapna Pothula |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Fancy Data Visualisations Without Additional Toolkits |
Kirsty Parker-Hodds |
source
presentation source |
5 |
| PHUSE EU |
2018 |
First Aid Kit for an Observational Study |
Yuliia Bahatska,
Vladlen Ivanushkin |
source
poster source |
4 |
| PHUSE EU |
2018 |
Forest Plots in Survival Subgroup Analyses |
Michael Brockmann,
Julia Benzing |
source
presentation source |
11 |
| PHUSE EU |
2018 |
From Machine-readable CDISC Standard Specifications to the e-Protocol |
Jozef Aerts |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Handling CRF Design Changes in a Live Environment |
Andre Snelting,
Nieke De Ruiter |
source
presentation source |
10 |
| PHUSE EU |
2018 |
Handling Missing Data in Clinical Trials Using Topological Data Analysis |
Sergey Glushakov,
Andrey Rekalo |
source
presentation source |
10 |
| PHUSE EU |
2018 |
How to Write ADaM Specifications Like a Ninja |
Caroline Francis |
source
poster source |
5 |
| PHUSE EU |
2018 |
iGET it! Downloading Data from a Centralised Repository Using PROC HTTP |
Neville Cope |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Implementation of a Metadata-based Approach to Statistical Planning, Analysis and Reporting |
Frank Freischlager,
Hanspeter Schnitzer |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Ann Croft |
source
presentation source |
13 |
| PHUSE EU |
2018 |
Implementing Advanced Analytics and Machine Learning in Risk-based Strategies |
Rajneesh Patil |
source
presentation source |
3 |
| PHUSE EU |
2018 |
Journey to the Centre of the Protocol: Explorations in Text Mining for Study eCRF Development |
Rodrick Bower |
source
poster source |
11 |
| PHUSE EU |
2018 |
Lessons Learned for Successful e-Study Data Submission to the PMDA towards the End of the Transitional Period |
Takashi Kitahara,
Ayako Noda |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Machine Learning with SAS |
Cathal Gallagher,
Jiangtang Hu |
source
presentation source |
3 |
| PHUSE EU |
2018 |
Managing the Impossible: CRO Oversight |
Detlef Nehrdich,
Waife |
source
presentation source |
5 |
| PHUSE EU |
2018 |
New Approach to Graph Databases |
Catharina Dahlbo,
Anna Berg |
source
poster source |
9 |
| PHUSE EU |
2018 |
Optimizing the Traceability Method in ADaM Parallel Conversions |
Roxane Debrus |
source
presentation source |
15 |
| PHUSE EU |
2018 |
Overall Survival Adjustment to Mitigate the Impact of Crossover from the Control Arm to the Experimental Arm. The Two-stage Method |
Antonio Nieto,
Javier Gómez |
source
poster source |
9 |
| PHUSE EU |
2018 |
Overcoming Resistance to Technology Change: A Linked Data Perspective |
Tim P. Williams |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Path of Change - From Market Research to Clinical Trials |
Eniko Bront |
source
presentation source |
3 |
| PHUSE EU |
2018 |
RWE: What We Have Observed |
Peter Grolimund |
source
presentation source |
4 |
| PHUSE EU |
2018 |
Sample Size: A Couple More Hints to Handle it Right Using SAS and R |
Andrii Artemchuk |
source
presentation source |
11 |
| PHUSE EU |
2018 |
SAS Life Science Analytical Framework (LSAF) in a Nutritional Clinical Research Setting |
Mickaël Hartweg,
Justine Morlet |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Simulating Enrolment Plans |
Jim Box |
source
presentation source |
6 |
| PHUSE EU |
2018 |
Step-by-step Guide to Efficacy Analysis in Solid Tumors Oncology Clinical Trials |
Anastasiia Tiurdo |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Streaming Tables and Listings by PROC STREAM |
Charumathy Sreeraman,
Samundeeswari Raja |
source
presentation source |
10 |
| PHUSE EU |
2018 |
Structured and Standardised Study Definition Drives Early Study Set-up for Added Business Benefits |
Djenan Ganic,
Tanja Petrowitsch |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Study URI |
Kerstin Forsberg,
Daniel Goude |
source
presentation source |
9 |
| PHUSE EU |
2018 |
Text as Data in the Context of Anonymising Clinical Study Reports |
Lukas Kniola,
Tim Perin |
source
presentation source |
12 |
| PHUSE EU |
2018 |
The 5 Rs of Innovative Digital Technologies |
Anna Hedman,
Charlotte Lomberg |
source
poster source |
4 |
| PHUSE EU |
2018 |
The EMA, Health Canada and the FDA: Three Agencies Tackle Data Sharing, Synergies and Differences |
Jean-Marc Ferran |
source
presentation source |
13 |
| PHUSE EU |
2018 |
The Importance of Being Ernest - Risk-based Approach (RBA) |
William Andrew Lawton |
source
presentation source |
4 |
| PHUSE EU |
2018 |
The interpretation and development of SDTM standards for non-submission purposes |
Paul Vervuren |
source
presentation source |
11 |
| PHUSE EU |
2018 |
The MetaDataHub - Integrating, Searching and Presenting Study Descriptive Information |
Elisabeth Nyman,
Michail Doulis |
source
presentation source |
8 |
| PHUSE EU |
2018 |
The Oncology-specific Domains TU, TS and RS: What to Know as a Statistical Analyst |
Frieder Wolff,
Vitali Gering |
source
presentation source |
8 |
| PHUSE EU |
2018 |
The Salford Lung Study: Challenges and Complexities with the Reporting of Electronic Medical Record Data in a Pioneering and Novel Approach to Clinical Trials |
Daniel Kwok,
Jennifer Colthart |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Top Five Challenges in Complying with CDISC Standards |
Trine Danø Klingberg,
Mikkel Traun |
source
presentation source |
4 |
| PHUSE EU |
2018 |
Turning Fantasy into Reality - Creating Custom Data Visualisations for Future Reporting |
James Diserens |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Use of HL7 FHIR as eSource to Pre-populate CDASH Case Report Forms Using a CDISC ODM API |
Samuel Hume,
Geoff Low |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Utilisation of Python in Clinical Studies by SASPy |
Yuichi Nakajima |
source
presentation source |
13 |
| PHUSE EU |
2018 |
ValueListDefs, MethodDefs and WhereClauses: How to Define Data Traceability in a Metadata Repository |
Judith Goud |
source
presentation source |
11 |
| SESUG |
2018 |
Dynamic Program Tracker |
Tanmay Khole,
Saigovind Chenna |
source |
5 |
| SESUG |
2018 |
Hardcoding In Clinical Trials: A (Sometimes) Necessary Evil |
Gregory Weller |
source |
5 |
| SESUG |
2018 |
SDTM - Just a Walk in the (Theme) Park, Exploring SDTM in the Most Magical Place on Earth |
Magical Place |
source |
10 |
| MWSUG |
2018 |
An Update on the CS Standard Analyses and Code Sharing Working Group |
Nancy Brucken,
Jared Slain |
|
4 |
| MWSUG |
2018 |
Toward Adoption of Agile Software Development in Clinical Trials |
Troy Martin Hughes |
|
7 |
| WUSS |
2018 |
CDISC in Phase I/II Studies: Approaches to adopting standards for CSR deliverables |
Emily Woolley,
Amber Randall |
source |
9 |
| WUSS |
2018 |
Defensive programming techniques for ongoing clinical studies |
Bharath Donthi,
Lingjiao Qi |
source |
8 |
| WUSS |
2018 |
Formatting outputs for clinical trial data to aid in readability |
Lingjiao Qi,
Bharath Donthi |
source |
11 |
| WUSS |
2018 |
How sensitive is your analysis? A case study on addressing it at ADaM level. |
Bhargav Koduru,
Balavenkata Pitchuka |
source |
7 |
| WUSS |
2018 |
Interactive Live Clinical Data Monitoring Dashboards with Drill-Down Using SAS & Microsoft Excel |
Parmodh Sharma,
Ankit Bansal,
Parvesh Boora |
source |
4 |
| PHUSE US |
2018 |
A Standardized Collaborative Approach for Statistical Programming Project Information |
Harper Forbes,
Christoph Ziegler |
source
presentation source |
4 |
| PHUSE US |
2018 |
A Statistics-based Tool to Inform Risk-based Monitoring Approaches |
Laura Williams,
Giulia Zardi |
source
presentation source |
8 |
| PHUSE US |
2018 |
A Successful Meta-Data Repository (MDR): It's About Managing Relationships |
Philip Giangiulio,
Melanie A. Paules |
source
presentation source |
7 |
| PHUSE US |
2018 |
Adverse Event Analysis - One step forward! |
Anuja Rasal |
source
presentation source |
11 |
| PHUSE US |
2018 |
Alexa for Clinical Research |
Chris Decker |
source
presentation source |
6 |
| PHUSE US |
2018 |
Assuring Data Integrity and Data Quality in Sponsor Submissions |
Paul Schuette |
source
presentation source |
5 |
| PHUSE US |
2018 |
Augmented Realtime Clinical DataMart |
Phani Shankar Srinivasan,
Subrahmanyam Rayaprolu |
source
presentation source |
7 |
| PHUSE US |
2018 |
Bili's Journey |
Chris Hurley,
Lisa Kaye Brooks |
source
poster source |
3 |
| PHUSE US |
2018 |
Building Dashboards for Real-time Insights into Clinical Data |
Bhavin Busa,
Siddartha Kondapally |
source |
6 |
| PHUSE US |
2018 |
Can Clinical Trial Datasets (CDSIC - SDTM/ADaM) be Generated Using R? |
Prasanna Murugesan |
source
presentation source |
3 |
| PHUSE US |
2018 |
CDER's Clinical Investigator Site Selection Tool |
Jean Mulinde,
Michael Johnson |
source
presentation source |
5 |
| PHUSE US |
2018 |
Challenges and Tactics of Managing Clinical Programming in Long Term Outcomes Trials |
David L. Wade,
Joanne C. Zhou,
Rakesh Kumar |
source
presentation source |
6 |
| PHUSE US |
2018 |
Clinical Timelines Visualized |
Spencer Childress,
Jeremy Wildfire |
source
presentation source |
6 |
| PHUSE US |
2018 |
Comparing and Contrasting Differences between the PHUSE SDSP and CBER Checklist |
Janet Low,
Pritesh Solanki |
source
presentation source |
5 |
| PHUSE US |
2018 |
CRF Design for Data Standards |
David A. Scocca |
source
presentation source |
4 |
| PHUSE US |
2018 |
Cross-study Analysis of SDTM Data Using R |
Greg Jones,
Todd Cornelius |
source
presentation source |
6 |
| PHUSE US |
2018 |
Cue the Word - QC - All You Need to Know! |
Subha Jamburajan,
Nancy Haeusser |
source
presentation source |
6 |
| PHUSE US |
2018 |
Data Science Applications and Scenarios |
Edwin Ponraj Thangarajan,
Giri Balasubramanian |
source
presentation source |
13 |
| PHUSE US |
2018 |
Evaluating how Blockchain can Transform the Pharmaceutical and Healthcare Industry |
Disa Lee Choun,
Jim Nasr |
source
presentation source |
9 |
| PHUSE US |
2018 |
Generating Table Listings and Figures Without Any Programs |
Shafi Chowdhury,
Md Zobair |
source
presentation source |
5 |
| PHUSE US |
2018 |
Harnessing Real-time Patient Data to Improve Clinical Outcomes and Research |
Himanshu Pandya,
Bob Engle |
source
presentation source |
4 |
| PHUSE US |
2018 |
How Automatic Visualization of Summary Results Can Speed up Review to Tables |
Shafi Chowdhury,
Rajwanur Rahman |
source
presentation source |
7 |
| PHUSE US |
2018 |
How do I have ONE Interpretation of CDISC for all my Studies? |
Mor Meyerovich |
source
presentation source |
5 |
| PHUSE US |
2018 |
Implementing an Metadata Repository Solution - A User Story |
Barrie Nelson,
Wade Fairbanks |
source
presentation source |
5 |
| PHUSE US |
2018 |
Increase Quality and Reduce SDTM Development Time with a Test Study Data Simulator |
Sasikumar Palanisamy,
Bhaskar Subramanian |
source |
4 |
| PHUSE US |
2018 |
Interim Survival Analysis Across 3 Platforms |
Venita DePuy |
source
presentation source |
22 |
| PHUSE US |
2018 |
It's Time To Change |
David Iberson-Hurst |
source |
14 |
| PHUSE US |
2018 |
Lead Programmer Needs Help: Dedicated Programming Project Manager to the Rescue! |
Smitha Nathan,
Bhavin Busa |
source |
5 |
| PHUSE US |
2018 |
Mapping Mirena Users in the US |
Jose F. Diaz,
Maria Mac |
source
presentation source |
2 |
| PHUSE US |
2018 |
Mine the Gap: How the Role of Data Scientist Fills a Need in the Pharmaceutical Industry |
Michael S Rimler,
Jorine Putter |
source
presentation source |
8 |
| PHUSE US |
2018 |
Programmers are from Mars and Statisticians are from Venus |
Shweta Padmanaban,
Sangeetha Sathaiah |
source
presentation source |
6 |
| PHUSE US |
2018 |
Project Programmer Role |
Michael Gunshenan,
Rebecca Greenwood |
source
poster source |
4 |
| PHUSE US |
2018 |
Ready Set Go: Planning and Preparing a CDISC Submission |
Maria Dalton |
source
presentation source |
11 |
| PHUSE US |
2018 |
Registry/Observational Studies: Study Designs Data Sources and Key Steps in Designing Such Studies |
Anupama Sheoran |
source
presentation source |
6 |
| PHUSE US |
2018 |
Role of Associate Director of Biomedical Informatics in Clinical Review at the FDA |
Nhi Beasley |
source |
2 |
| PHUSE US |
2018 |
SDTM and SEND: An Integrated View and Approach |
Veena Nataraj,
Cheryl Riel |
source
presentation source |
11 |
| PHUSE US |
2018 |
SDTM: It is Not all Black and White |
Swapna Pothula,
Roman Radelicki |
source |
7 |
| PHUSE US |
2018 |
Shaken But Not Stirred: An Example of Subject Classification using Multidimensional Scaling |
Manuel Sandoval Garcia |
source
presentation source |
7 |
| PHUSE US |
2018 |
Split-Coalesce Tumor Data Handling Woes and Safety-Efficacy Dilemma |
Idya Muthukumar |
source
presentation source |
11 |
| PHUSE US |
2018 |
Standard Analyses and Displays for Common Data in Clinical Trials - The Journey Continues! [poster] |
Nhi Beasley |
source |
1 |
| PHUSE US |
2018 |
Subgroup Explorer and AdEPro - The Full Picture on Clinical Trial Data [presentation] |
Madhurima Majumder,
Erya Huang |
source |
20 |
| PHUSE US |
2018 |
Supporting a Data Review and Visualization Application with SDTM |
Deepika Sunkara,
Jagadish Dhanraj |
source
presentation source |
6 |
| PHUSE US |
2018 |
The Untapped Potential of the Protocol Representation Model |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source
presentation source |
10 |
| PHUSE US |
2018 |
Transforming Clinical Trials with Linked Data |
Tim P. Williams,
Armando Oliva |
source
presentation source |
9 |
| PHUSE US |
2018 |
Use of HL7 FHIR as eSource to Pre-populate CDASH Case Report Forms Using a CDISC ODM API |
Samuel Hume,
Geoff Low |
source
presentation source |
12 |
| PHUSE US |
2018 |
Using the TFL Workbench for Standards Governance |
Hansjörg Frenzel,
Iain Humphreys |
source |
9 |
| PHUSE US |
2018 |
Web Codebooks - Interactive Data Summaries for Clinical Trial Data |
Jeremy Wildfire,
Spencer Childress |
source
presentation source |
6 |
| PharmaSUG |
2018 |
A Conceptual Strategy and Macro Approach for Partial Date Handling in Data De-Identification |
Amy Caison,
Kelsey Reppert |
source |
8 |
| PharmaSUG |
2018 |
A Framework for Implementing [Conflicting] FDA Guidance |
Todd Case |
source |
6 |
| PharmaSUG |
2018 |
A SAS Macro to Create Validation Summary of Dataset Report |
Zemin Zeng |
source |
6 |
| PharmaSUG |
2018 |
ADaM for Medical Devices: Extending the Current ADaM Structures |
Julia Yang,
Sandra Minjoe |
source |
7 |
| PharmaSUG |
2018 |
Advanced Visualization using TIBCO Spotfire and SAS |
Ajay Gupta |
source |
14 |
| PharmaSUG |
2018 |
AGING MAN_AGEMENT or millennial TECH_AGEMENT - road ahead for organizations |
Charan Kumar K J |
source |
12 |
| PharmaSUG |
2018 |
Analysis of Oncology Studies for Programmers and Statisticians |
Kevin Lee |
source |
7 |
| PharmaSUG |
2018 |
Analyzing Adverse Events of Special Interest using Lab Tests and Toxicity Grades |
Vamsi Krishna Medarametla,
Liz Thomas,
Gokul Vasist |
source |
6 |
| PharmaSUG |
2018 |
Automate Clinical Trial Data Issue Checking and Tracking |
Krishna Avula,
Dale LeSueur |
source |
5 |
| PharmaSUG |
2018 |
BEACH: an open platform for building interactive and automatic analysis powered by R/Shiny |
Danni Yu,
Michael Man |
source |
19 |
| PharmaSUG |
2018 |
Building Simulated CRF Data for Study Mock-Ups |
Ashley Kesler,
Hisham Madi,
Jonathan W. Duggins,
James E. Blum |
source |
10 |
| PharmaSUG |
2018 |
Challenges in Implementing Device Related ADaM and SDTM Standards in a Drug-Device Study |
Wenying Tian,
Maureen Maunsell,
Karin LaPann |
source |
9 |
| PharmaSUG |
2018 |
Compare Pharmacokinetic Data Submission Processes in CDISC Environment |
Xiaopeng Li,
Shallabh Mehta,
Edward Elam |
source |
7 |
| PharmaSUG |
2018 |
Complexity in collection of PGx data and challenges in mapping to SDTM |
Rama Kudaravalli |
source |
9 |
| PharmaSUG |
2018 |
Creating and Customizing Graphics using Graph Template Language |
Saihua Liu,
Yanmei Zhang,
Titania Dumas-Roberson |
source |
9 |
| PharmaSUG |
2018 |
Data Management and CDISC Formatting for Transdermal Patches |
Lois Lynn |
source |
11 |
| PharmaSUG |
2018 |
Designing Flexible Data Standards Models |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2018 |
Easy CSR In-Text Table Automation, Oh My |
Janet E. Stuelpner |
source |
6 |
| PharmaSUG |
2018 |
Electronic Data Submission and Utilization in Japan |
Yuki Ando |
source |
25 |
| PharmaSUG |
2018 |
Exploring use of R for Clinical trials |
Kalpesh Prajapati,
Parvee Kumar |
source |
7 |
| PharmaSUG |
2018 |
Generating Define.xml from Pinnacle 21 Validator |
Pinky Anandani |
source |
15 |
| PharmaSUG |
2018 |
How to Be a Great (Stats or Programming) Manager: Advice from an Underling |
Mary Grovesteen |
source |
6 |
| PharmaSUG |
2018 |
Implementation of ADaM Basic Data Structure on Genetic Variation Data for Pharmacogenomics Studies |
Linghui Zhang |
source |
10 |
| PharmaSUG |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Mei Dey |
source |
15 |
| PharmaSUG |
2018 |
Let's get to the Source and streamline it to the End |
Jennifer Price |
source |
6 |
| PharmaSUG |
2018 |
Leveraging Standards for Effective Visualization of Early Efficacy in Clinical Trial Oncology Studies |
Kelci J. Miclaus,
Lili Li |
source |
12 |
| PharmaSUG |
2018 |
Link Up Sync Up: Calculation of concordance and discordance rates between Independent Review Facility (IRF) and Investigator site data using SAS |
Bhargav Koduru,
Girish Kankipati |
source |
10 |
| PharmaSUG |
2018 |
No News Is Good News: A Macro to Reveal the Untold Normal Lab Results |
Ming Yan |
source |
7 |
| PharmaSUG |
2018 |
PK Data Explained |
Timothy J. Harrington |
source |
9 |
| PharmaSUG |
2018 |
Preparing the Office of Scientific Investigations (OSI) Requests for Submissions to FDA |
Zihui Lin,
Wei Cui,
Yaling Teng,
Ran Li |
source |
9 |
| PharmaSUG |
2018 |
Preventing premature unblinding in PK/PD related studies |
Debbie Sisco,
Alice Zong |
source |
11 |
| PharmaSUG |
2018 |
Programmer's Guide for OSI Deliverables - Creation of Site Level Summary Dataset and Automation of BIMO Listins Generation |
Charanjit Kahlon,
Kristie Kooken,
Bhavin Busa,
Dharmendra Tirumalasetti |
source |
10 |
| PharmaSUG |
2018 |
Programming Support for Anti-Drug Antibody Pharmacokinetics in Therapeutic Protein Drug Development |
Linghui Zhang,
Jiannan Kang |
source |
11 |
| PharmaSUG |
2018 |
Report Compatibility: System to evaluate your code against volatile sources. |
Joseph Cooney,
Randy Santiano,
Craig Brelage |
source |
12 |
| PharmaSUG |
2018 |
Review programs used for submission and their input to the define-XML 2.0 |
Ari Siggaard Knoph,
Morten Hasselstrm Jensen,
Bo Sølgaard Andersen |
source |
11 |
| PharmaSUG |
2018 |
Risk-based Validation in Clinical Trial Reporting: Focus on What Matters Most |
Amber Randall,
William Coar |
source |
10 |
| PharmaSUG |
2018 |
SDTMs in a Medical Device Trial - A First Attempt |
Phil Hall |
source |
6 |
| PharmaSUG |
2018 |
Second Primary Malignancy (SPM) Analyses in a Disease Registry Study |
Jane Lu,
Shankar Srinivasan,
Robert Knight |
source |
6 |
| PharmaSUG |
2018 |
Sense and Censorability: Learn censoring techniques with ADTTE for your survival |
Shilpakala Vasudevan |
source |
12 |
| PharmaSUG |
2018 |
Some Common Programming Errors and Possible Solutions That Could Impact a Successful NDA/BLA |
Amos Shu |
source |
5 |
| PharmaSUG |
2018 |
Speed Up SDTM/ADaM Dataset Development with If-Less Programming |
Lei Zhang,
John Lu |
source |
17 |
| PharmaSUG |
2018 |
Statistician in my Soul. Statistical Questions from SPA |
Nadiia Hryhorenko |
source |
12 |
| PharmaSUG |
2018 |
Stay ahead of the game: Know the SDTM compliance check reject messages before creating your SDTM datasets |
Lixiang Larry Liu,
Yuqin Li |
source |
6 |
| PharmaSUG |
2018 |
The Changing Clinical Data Analytics Landscape - Visualization & Beyond |
Siddartha Kondapally,
Kishore Pothuri,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2018 |
Tips and Tricks to Enhance RTF Output |
Rohini Rao |
source |
8 |
| PharmaSUG |
2018 |
To Error is Human: An Overview of Human Errors in SAS Programming and How to Mitigate Them |
Nagadip Rao |
source |
9 |
| PharmaSUG |
2018 |
Trial Summary: The Golden Gate towards a Successful Submission |
Bhargav Koduru,
Girish Kankipati |
source |
9 |
| PharmaSUG |
2018 |
Triangulating Multiple Sources of Contradictory Prescription Data - a Real-World Case Study |
Vidhya Parameswaran |
source |
13 |
| PharmaSUG |
2018 |
Tumor Dashboard |
Sudhir Singh |
source |
6 |
| PharmaSUG |
2018 |
Using JMP Scripting Language (JSL) to create an application interface for automated analysis of Lab Data in Clinical Trial |
Dongsun Cao |
source |
11 |
| PharmaSUG |
2018 |
Using Simulation to Create Enrollment Plans |
Jim Box |
source |
7 |
| PharmaSUG |
2018 |
Watch Out For Blind Spots While Keeping Up With the Speed of Evolving Standards and Regulations |
Srinivas Veeragoni |
source |
14 |
| PharmaSUG |
2018 |
When a Clinical Trial Lasts Forever: A Reporting Solution for Post-Market Surveillance of Cardiac Rhythm Devices |
Becky DeBus |
source |
8 |
| SGF |
2018 |
A Macro for Last Observation Carried Forward |
Jonson Jiang |
source |
5 |
| SGF |
2018 |
Auto-populating Microsoft PowerPoint Presentations So You Don't Have To |
Kaitie Lawson |
source |
17 |
| SGF |
2018 |
Automation of Clinical Trial Result Posting to ClinicalTrials.gov and EudraCT |
Sherry Meeh |
source |
9 |
| SGF |
2018 |
Personal Lending: What is Customer Price/Credit Optimization? Is Experimental Design Inevitable? |
Yuri Medvedev |
source |
20 |
| SGF |
2018 |
The Anatomy of Clinical Trials Data: A Beginner's Guide |
Venky Chakravarthy |
source |
14 |
| SESUG |
2017 |
An Introduction to Visit Window Challenges and Solutions |
Mai Ngo |
source |
6 |
| SESUG |
2017 |
Building Heat Maps for Data Cleaning and Beyond |
Kristen Much,
Nicole Bader |
source |
12 |
| SESUG |
2017 |
Enrollment Simulation in Clinical Trials |
Venita DePuy |
source |
5 |
| SESUG |
2017 |
Meta-Analysis and Matrix Multiplication: Adapting an IML-Based Macro for DerSimonian and Laird's Error Calculation to use Base SAS |
Venita DePuy |
source |
16 |
| SESUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| SESUG |
2017 |
Timing Variables In Clinical Trials: Avoiding Common Mistakes And Dealing With Unforeseen Issues |
Gregory Weller |
source |
4 |
| SCSUG |
2017 |
Risk Based Monitoring (RBM) with SAS Visual Analytics |
Prasoon Sangwan,
Piyush K. Singh,
Faraz Khan |
source |
10 |
| PHUSE EU |
2017 |
A Better Way of Representing Clinical Trial Data Using SAS Graphs [presentation] |
Murali Neela |
source |
1 |
| PHUSE EU |
2017 |
Adverse Events Data Over Time |
Kriss Harris |
source
presentation source |
11 |
| PHUSE EU |
2017 |
Ahead of the Curve: Leading with Industry Data Requirements |
Nancy Haeusser |
source
presentation source |
8 |
| PHUSE EU |
2017 |
An FDA Submission Experience Using the CDISC Standards |
Angelo Tinazzi,
Cédric Marchand |
source
presentation source |
15 |
| PHUSE EU |
2017 |
Analysis Results Metadata 1.0 for Define-XML 2.0 - Benefits to Statistical Analysis |
Lionel Debecq |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Anonymisation of Clinical Study Reports |
Julie De Wever,
Marie-Anne Thil |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Approach to EMA Policy 0070 - From Data Science Perspective |
Jorine Putter |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Assessing New CFDA Requirements on Data Integrity Using Risk-Based Monitoring and Enrollment Patterns |
Wenjun Bao,
Richard C. Zink,
Geoffrey A. Mann |
source
presentation source |
13 |
| PHUSE EU |
2017 |
Automated Anonymisation of Protected Personal Data in Clinical Reports |
Azad Dehghan,
Cathal Gallagher |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Breaking the Mould: Clinical Trials Data as RDF |
Tim P. Williams,
Armando Oliva |
source
presentation source |
6 |
| PHUSE EU |
2017 |
CDISC Transport Standards - A Glance |
Edwin Ponraj Thangarajan,
Giri Balasubramanian |
source
presentation source |
14 |
| PHUSE EU |
2017 |
Clinical Metadata - Web-based metadata management with a CDISC mindset |
Andrew Ndikom,
Liang Wang |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Connected Trials |
Abi Velurethu |
source
presentation source |
10 |
| PHUSE EU |
2017 |
Considerations and Conventions in the Submission of the SDTM Tumor and Response Domain |
Jerry Salyers,
Fred Wood |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Data Cleaning Technique for Business Analytics: What Stats Van Do for DM |
Adam Korczynski |
source
presentation source |
16 |
| PHUSE EU |
2017 |
Decrypting SDTM Trial Design Datasets for Complex Study Designs |
Charumathy Sreeraman |
source
presentation source |
14 |
| PHUSE EU |
2017 |
Detecting Treatment Emergent Adverse Events (TEAEs) |
Matthias Lehrkamp |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Devices Big Data and Real World Evidence |
Mike Collinson |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Dipping our Fingers into the World of Data Representation - A Visual Journey Using Encapsia Clinica |
Minola Ilica |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Efficiency Ratios as a Method of Determining Statistical Computing Environment Effectiveness |
Andy Richardson |
source
presentation source |
6 |
| PHUSE EU |
2017 |
EMA Policy 0070: Data Utility in Anonymized Clinical Study Reports (CSRs) |
Jean-Marc Ferran,
Sarah Nevitt |
source |
23 |
| PHUSE EU |
2017 |
Evaluation of Re-identification Risk for Anonymized Clinical Documents |
Parvee Kumar,
Rajan Sareen |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Experiences of Managing Quality Registry Data for Effective Exploration |
Catharina Dahlbo |
source
presentation source |
6 |
| PHUSE EU |
2017 |
FlexRandomizer: Easy Randomisation in Real Time |
Priyadarshan Shinde,
Mangesh Kulkarni |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Formedix On: A Powerful Platform to Accelerate Clinical Trials |
Kevin Burges |
source
presentation source |
2 |
| PHUSE EU |
2017 |
From Programmer to Patient. Why it is Good to be a Clinical Programmer When You Are Seriously Ill |
Colin Brown |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Futile or Not? An Interim Analysis Case Study |
Ingrid Franklin |
source
presentation source |
9 |
| PHUSE EU |
2017 |
Health Technology Assessment PRO Least Squares Mean Difference Programming Techniques Using SAS |
Yirong Cao,
Siory Traoré |
source
presentation source |
11 |
| PHUSE EU |
2017 |
How a Metadata Repository can Facilitate Automated Data Collection Processes |
Judith Goud |
source
presentation source |
8 |
| PHUSE EU |
2017 |
How to Fit Longitudinal Data with Proc MCMC |
Maud Henion |
source
presentation source |
16 |
| PHUSE EU |
2017 |
Implementing JumpStart at Novo Nordisk A/S |
Kina Ulkaer Jørgensen |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Industry Standards - What Else Exists Beside CDISC |
Joerg Dillert |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Interactive Visualisation of Clinical Laboratory Parameters with SAS Stored Processes and JQuery Ajax |
Volker Hart |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Job of Jobs |
Kris Lauwers,
Raphael Noirfalise |
source
presentation source |
3 |
| PHUSE EU |
2017 |
KeyDAN: a Clinical Data De-identification Solution |
Stéphane Chollet |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Leverage Automation to Accelerate the Creation of Submission-ready Artifacts |
Serena Pierson,
Lourdes Devenney |
source |
4 |
| PHUSE EU |
2017 |
Managing Study Workflow Using the Resource Description Framework (RDF) |
Armando Oliva |
source |
7 |
| PHUSE EU |
2017 |
Patient-level Data-sharing (PLDS) Initiatives in Pharmaceutical Companies |
Sophie Buyle |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Plausible Adversaries in Re-Identification Risk Assessment |
Lukas Kniola |
source
presentation source |
10 |
| PHUSE EU |
2017 |
Presenting Study Results form a Metadata-driven Ecosystem |
Rajwanur Rahman |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Qlik Sense for Pharmacovigilance [presentation] |
Daniel Andersen |
source |
9 |
| PHUSE EU |
2017 |
REACTing to Data: The Use of Data Visualisation within Early Clinical StatisticalProgramming at AstraZeneca |
Shyamprasad Perisetla,
Suzanne Tautz |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Real World Data Surprises |
Ewa Sleszynska-Dopiera,
Jan Rudnik |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Robust Study Database Build: An Effective Start Towards Creation of Quality SDTMs |
Onkar Tajarekar |
source
presentation source |
9 |
| PHUSE EU |
2017 |
Surviving your Statistician: A Programmer's Guide to Survival Analysis |
James Diserens |
source
presentation source |
11 |
| PHUSE EU |
2017 |
The Impact of Regulations on Immuno-OncologySubmissions |
Geoffrey A. Mann |
source
presentation source |
8 |
| PHUSE EU |
2017 |
The Model Statistician Insights into Model Selection Techniques in Clinical Trials |
Peter Williams |
source
presentation source |
6 |
| PHUSE EU |
2017 |
The Untapped Potential of the Protocol Representation Model |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source
presentation source |
10 |
| PHUSE EU |
2017 |
Tips and Tricks to Create In-text Tables in Clinical Trial Reporting Using SAS |
Rafi Rahi |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Topology-based Clinical Data Mining: Identifying Hidden Patterns in Clinical Datasets |
Sergey Glushakov |
source
presentation source |
18 |
| PHUSE EU |
2017 |
Use of Fast Healthcare Interoperability Resources (FHIR) in the Generation of Real-World Evidence |
Trisha Simpson,
Regina Zopf |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Using VBScript for Perfecting Statistical Reports |
Ekaterina Torchinskaya,
Andrey Myslivets |
source
presentation source |
9 |
| PHUSE EU |
2017 |
Visualising CDSIC SDTM for Monitoring and Review |
Philip Bartle |
source
presentation source |
11 |
| PHUSE EU |
2017 |
Visualizing Multiple Endpoints: Extending the Use of Forest Plots in Clinical Trials |
James R. Johnson,
Mark Jaros |
source
presentation source |
10 |
| MWSUG |
2017 |
Correcting for Selection Bias in a Clinical Trial |
Shana Kelly |
|
8 |
| MWSUG |
2017 |
No News Is Good News: A Smart Way to Impute Missing Clinical Trial Lab Data |
Ming Yan |
|
4 |
| MWSUG |
2017 |
Patient Safety with SAS Visual Analytics |
Piyush K. Singh,
Prasoon Sangwan,
Ghiyasuddin Mohammed Faraz Khan |
|
12 |
| WUSS |
2017 |
A Critique of Implementing the Submission Data Tabulation Model (SDTM) for Drugs and Medical Devices |
Carey G. Smoak |
source |
16 |
| WUSS |
2017 |
SDTMs in a Medical Device Trial - A First Attempt |
Phil Hall |
source |
5 |
| WUSS |
2017 |
Show Me The Job! |
Richelle Serrano |
source |
4 |
| WUSS |
2017 |
Which Paint Brush Shall I Choose -- Mapping Out Your Visualization Plan for Clinical Studies |
Chen Shi |
source |
5 |
| PharmaSUG CN |
2017 |
Effective Statistical Programming Preparation and Support for CFDA Self-Inspections and Onsite Inspections |
Peng Wan |
|
5 |
| PharmaSUG CN |
2017 |
How to define Treatment Emergent Adverse Event (TEAE) in crossover clinical trials |
Mengya Yin,
Wen Tan |
|
6 |
| PharmaSUG CN |
2017 |
One Step to Produce Shift Table by Using PROC REPORT |
Haiqiang Luo |
|
7 |
| PharmaSUG CN |
2017 |
Overview of OSI Deliverables from Programming Perspective |
Wang Zhang |
|
6 |
| PharmaSUG CN |
2017 |
Strip Special & Non-Printable Characters in Your Data Set |
Ying Liu |
|
6 |
| PharmaSUG |
2017 |
A Critique of Implementing the Submission Data Tabulation Model (SDTM) for Drugs and Medical Devices |
Carey G. Smoak |
source |
16 |
| PharmaSUG |
2017 |
A Guide To Programming Patient Narratives |
Renuka Tammisetti,
Karthika Bhavadas |
source |
6 |
| PharmaSUG |
2017 |
A novel method to track mapping of all CRF variables into SDTM datasets. |
Aishhwaryapriya Elamathivadivambigai |
source |
7 |
| PharmaSUG |
2017 |
Adverse Event Data over Time |
Kriss Harris |
source |
11 |
| PharmaSUG |
2017 |
Ahead of the Curve: Leading with Industry Data Requirements |
Maria Dalton,
Nancy Haeusser |
source |
17 |
| PharmaSUG |
2017 |
Analyzing data from multiple clinical trials using SAS Real World Evidence |
Jay Paulson,
David Olaleye |
source |
13 |
| PharmaSUG |
2017 |
Automated Generation of Clinical Study Reports using SAS and RTF (Literate programming) |
Rajaram Venkatesan,
Julien Sauser,
Carlos Antonio De Castro |
source |
13 |
| PharmaSUG |
2017 |
Awareness from Electronic Data Submission to PMDA and FDA -- Lesson & Learnt from hands-on experiences -- |
Yuichi Nakajima,
Takashi Kitahara,
Ryan Hara |
source |
12 |
| PharmaSUG |
2017 |
Beyond - Just fix it!- Application of Root Cause Analysis Methodology in SAS Programming. |
Nagadip Rao |
source |
8 |
| PharmaSUG |
2017 |
Challenge for Dramatic Streamlining of TLFs Creation Process with SAS and Java |
Yohei Takanami,
Fumihiro Yamasaki |
source |
8 |
| PharmaSUG |
2017 |
Clinical and Vendor Database Harmony; Can-t we all just get along? |
Brian Armstrong,
Renee Kerwin |
source |
9 |
| PharmaSUG |
2017 |
Clinical Trials Data: It-s a Scary World Out There! or Code that Helps You Sleep at Night |
Scott Horton |
source |
10 |
| PharmaSUG |
2017 |
ClinicalTrials.gov Results: an End of Study Deliverable That Should Be Considered at Study Startup |
Maya Barton,
Elizabeth Paynter |
source |
9 |
| PharmaSUG |
2017 |
Combining Survival Analysis Results after Multiple Imputation of Censored Event Times |
Jonathan L Moscovici,
Bohdana Ratitch |
source |
11 |
| PharmaSUG |
2017 |
Considerations and Conventions in the Submission of the SDTMIG Tumor and Response Domains |
Jerry Salyers,
Fred Wood |
source |
7 |
| PharmaSUG |
2017 |
Considerations in Submitting Standardized Electronic Data Under the Animal Rule: The Use of Domains in the SDTMIG and the SENDIG |
Fred Wood |
source |
7 |
| PharmaSUG |
2017 |
Creating Define-XML version 2 including Analysis Results Metadata with the SAS Clinical Standards Toolkit |
Lex Jansen |
source |
31 |
| PharmaSUG |
2017 |
Data Integrity: One step before SDTM |
Pavan Kathula,
Sonal Torawane |
source |
9 |
| PharmaSUG |
2017 |
Data Monitoring Committee Report Programming: Considering a Risk-Based Approach to Quality Control |
Amber Randall,
Bill Coar |
source |
9 |
| PharmaSUG |
2017 |
Data Transparency, de-identification strategies, and platforms available for sharing data |
Arun Raj Vidhyadharan,
Sunil Mohan Jairath |
source |
10 |
| PharmaSUG |
2017 |
Effective Ways to Perfect the Visualization of Clinical Trial Results |
Amos Shu |
source |
6 |
| PharmaSUG |
2017 |
Good Programming Practices at Every Level |
Maria Dalton |
source |
6 |
| PharmaSUG |
2017 |
Good versus better SDTM: Including Screen Failure Data in the Study SDTM? |
Henry B. Winsor,
Mario Widel |
source |
9 |
| PharmaSUG |
2017 |
How to define Treatment Emergent Adverse Event (TEAE) in crossover clinical trials |
Mengya Yin,
Wen Tan |
source |
6 |
| PharmaSUG |
2017 |
How to find the best MDR solution for your organization |
Kevin Lee |
source |
3 |
| PharmaSUG |
2017 |
Implementation of STDM Pharmacogenomics/Genetics Domains on Genetic Variation Data |
Linghui Zhang |
source |
12 |
| PharmaSUG |
2017 |
Implementing Patient Report Outcome data in clinical trials analysis |
Qi Wang |
source |
7 |
| PharmaSUG |
2017 |
Innovation and Regulatory Review What is JumpStart? |
Alan Shapiro |
source |
24 |
| PharmaSUG |
2017 |
Is There a Date In That Comment? Use SAS To Find Out. |
Keith Hibbetts |
source |
4 |
| PharmaSUG |
2017 |
Laboratory Data Standardization with SAS |
Charley Z. Wu,
Dona-Lyn Wales |
source |
12 |
| PharmaSUG |
2017 |
LBTEST/LBSTRESU and ADaM lab parameters: The dilemma of mapping one-to-many or many-to-one |
Michelle Barrick |
source |
5 |
| PharmaSUG |
2017 |
Lead Programmer Needs Help: Dedicated Programming Project Manager to the Rescue! |
Gloria Boye,
Aparna Poona,
Bhavin Busa |
source |
7 |
| PharmaSUG |
2017 |
Let-s Check Data Integrity Using Statistical (SAS) Programmers with SAS |
Harivardhan Jampala |
source |
17 |
| PharmaSUG |
2017 |
Leveraging Centralized Programming Resources Using SAS Integration Technologies |
Tony Chang |
source |
8 |
| PharmaSUG |
2017 |
Leveraging Study Data Reviewer-s Guide (SDRG) in Building FDA-s Confidence in Sponsor-s Submitted Datasets |
Xiangchen (Bob) Cui,
Min Chen,
Letan (Cleo) Lin |
source |
10 |
| PharmaSUG |
2017 |
Make it personal: Upgrade your figures by adding individual patient data to the common figure types |
Yuliia Bahatska,
Christiane Ahlers |
source |
20 |
| PharmaSUG |
2017 |
Multi-Dimensional Arrays: Add Derived Parameters |
Siddharth Kumar Mogra |
source |
7 |
| PharmaSUG |
2017 |
Multiple Imputation: A Statistical Programming Story |
Christopher J. Smith,
Scott Kosten |
source |
16 |
| PharmaSUG |
2017 |
Multiplicity Controlled Analyses Using SAS/IML |
Xingxing Wu,
Hangtao Xu |
source |
8 |
| PharmaSUG |
2017 |
Pilot Meta-Analysis of HPA Axis Suppression Studies on Topical Corticosteroids using ADaM Datasets derived from Legacy Data |
Lillian Qiu,
Hon-Sum Ko |
source |
5 |
| PharmaSUG |
2017 |
Programming Efficiency in the Creation of ADaM BDS Datasets |
Ellen (Zihui) Lin |
source |
11 |
| PharmaSUG |
2017 |
Quality Check your CDISC Data Submission Folder Before It Is Too Late! |
Bhavin Busa |
source |
9 |
| PharmaSUG |
2017 |
RELREC - SDTM Programmer-s Bermuda Triangle |
Charumathy Sreeraman |
source |
12 |
| PharmaSUG |
2017 |
Roadmap for Managing Multiple CRO Vendors |
Veena Nataraj,
Karin LaPann |
source |
7 |
| PharmaSUG |
2017 |
SAS Macro for Derivation of Best Overall Response per RECIST v. 1.1 |
Bob Zhong,
Jiangfan Li,
Hong Xie,
Peter De Porre,
Kenneth Maahs,
Kyounghwa Bae |
source |
9 |
| PharmaSUG |
2017 |
SDTM - Just a Walk in the (Theme) Park, Exploring SDTM in the Most Magical Place on Earth |
Christine McNichol |
source |
9 |
| PharmaSUG |
2017 |
SDTM Cartography - Learn To Create SDTM Mapping Specifications |
Donna Sattler,
Mike Lozano |
source |
7 |
| PharmaSUG |
2017 |
Show Me The Job! |
Richelle Serrano,
Kevin Lee |
source |
4 |
| PharmaSUG |
2017 |
Sponsor Oversight of CROs Data Management and Biostatistical Abilities |
Lois Lynn |
source |
7 |
| PharmaSUG |
2017 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| PharmaSUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| PharmaSUG |
2017 |
The %NEWSURV Family of Macros: An Update on the Survival Plotting Macro %NEWSURV and an Introduction to Expansion Macros |
Jeffrey P. Meyers |
source |
21 |
| PharmaSUG |
2017 |
The Do-s/Don-ts, An SDTM Validation Perspective. The should/shouldn-t when explaining issues in the Study Data Reviewers Guide |
Thomas Guinter |
source |
8 |
| PharmaSUG |
2017 |
The Untapped Potential of the Protocol Representation Model |
Frank C. DiIorio,
Jeffrey M. Abolafia |
source |
10 |
| PharmaSUG |
2017 |
Topology-based Clinical Data Mining for Discovery of Hidden Patterns in Multidimensional Data |
Sergey Glushakov,
Iryna Kotenko,
Andrey Rekalo |
source |
20 |
| PharmaSUG |
2017 |
Translating Statistics into Knowledge by Examples Using SAS Graphic Procedures |
Tao Shu,
Jianfei Jiang |
source |
11 |
| PharmaSUG |
2017 |
Usage of Pinnacle 21 Community Toolset 2.x.x for Clinical Programmers |
Sergiy Sirichenko,
Michael DiGiantomasso |
source |
23 |
| PharmaSUG |
2017 |
Visualizing Enrollment Over Time |
Laura Gruetzner |
source |
11 |
| PharmaSUG |
2017 |
Work with me here-(or there or anywhere): Practical Cloud Collaboration with JMP Clinical for Clinical Trial Data Reviews |
Kelci J. Miclaus,
Drew Foglia |
source |
14 |
| SGF |
2017 |
A Critique of Implementing the Study Data Tabulation Model (SDTM) for Drugs and Medical Devices |
Carey G. Smoak |
source |
16 |
| SGF |
2017 |
Automatically Map CDASH Data to the Study Data Tabulation Model (SDTM) Structure |
Hao Xu,
Hong Chen |
source |
18 |
| SGF |
2017 |
Quality Control Programming: A Lost Art? |
Amber Randall,
Bill Coar |
source |
15 |
| SGF |
2017 |
SAS: A Unifying Tool That Manages Hospital and Research Pharmacy Data and Reporting |
Robert MacArthur,
Arman Altincatal |
source
pdf |
8 |
| SCSUG |
2016 |
%EventChart: A Macro to Visualize Data with Multiple Timed Events |
Andrew Peng |
source |
6 |
| SESUG |
2016 |
Cover Your Assumptions with Custom %str(W)ARNING Messages |
Shane Rosanbalm |
source |
7 |
| SESUG |
2016 |
How To Win Friends and Influence People - A Programmer's Perspective in Effective Human Relationships |
Priscilla Gathoni |
source |
8 |
| SESUG |
2016 |
Surviving the Interim: Insights Into Interim Survival Analyses |
Venita DePuy |
source |
31 |
| PHUSE EU |
2016 |
A Standardised Approach to De-identification |
Christopher C. Hurley |
source
presentation source |
13 |
| PHUSE EU |
2016 |
Blur Software Demonstration |
Cathal Gallagher |
source
presentation source |
3 |
| PHUSE EU |
2016 |
Calculating the Risk of Re-identification of Patient-level Data Using a Quantitative Approach |
Lukas Kniola |
source
presentation source |
9 |
| PHUSE EU |
2016 |
Case Study in Support of German Payer Evidence |
Frank Senk |
source
presentation source |
5 |
| PHUSE EU |
2016 |
Challenges and Opportunities with the Implementation of a Single-instance Cloud Research Platform |
Doug Bain |
source
presentation source |
16 |
| PHUSE EU |
2016 |
Clinical Data in Business Intelligence |
Mike Collinson |
source
presentation source |
7 |
| PHUSE EU |
2016 |
Constructing a Clinical Data Warehouse for Nutrition Studies [presentation] |
Paul Vervuren |
source |
27 |
| PHUSE EU |
2016 |
Constructing Interoperable Study Documents From A Semantic Technology-based Repository |
Colin de Klerk |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Data De-identification Made Simple |
Jørgen Mangor Iversen |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Data Sharing 3 Years on - From Baby to Toddler... |
Katherine Tucker |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Data Standards Governance |
João Gonçalves |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Developing MDR Metadata Requirements for Operational Implementation |
Andy Richardson,
Scott A. Bahlavooni |
source
presentation source |
5 |
| PHUSE EU |
2016 |
Does the Concept of a 'Sentient Enterprise' Apply to the Clinical Trial Execution Process? |
Peter Grolimund |
source
presentation source |
7 |
| PHUSE EU |
2016 |
Early Data Review [presentation] |
Graham Oakley |
source
presentation
presentation source |
1 |
| PHUSE EU |
2016 |
Efficiency comes From Reusability and Repeatability |
Hanming Tu,
Dave Evans |
source
presentation source |
10 |
| PHUSE EU |
2016 |
End-to-end Data and Metadata: It's Not Only a Dream, It's a Reality |
Gerald Neveu |
source |
6 |
| PHUSE EU |
2016 |
EnForeSys - An Advanced Patient Enrolment Forecaster with Monte Carlo Simulations |
Ritika Yadav,
Swechhya Bista |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Get Kitted Out - A Practical Guide to SAS Certifications, MOOCs and Hands-on Experience |
Hannes Engberg Raeder |
source |
6 |
| PHUSE EU |
2016 |
How to Effectively Deal with Hard-coding and CDISC Controlled Terminology in Clinical Studies |
Lennert van der Zee |
source
presentation source |
10 |
| PHUSE EU |
2016 |
How to Handle Different Versions of SDTM & Define Generation in a Single Day |
Edwin Ponraj Thangarajan,
Giri Balasubramanian |
source
presentation source |
22 |
| PHUSE EU |
2016 |
How to Review a CRF - A Statistical Programmer's Perspective |
Elsa Lozachmeur |
source
presentation source |
7 |
| PHUSE EU |
2016 |
Integrating the New EMA Requirements on Public Disclosure in the Study Conduct [presentation] |
Jean-Marc Ferran |
source |
20 |
| PHUSE EU |
2016 |
Interactive Visualisation of Linked Data |
Tim P. Williams |
source
presentation source |
8 |
| PHUSE EU |
2016 |
Japanese Electronic Submission in CDISC Formats |
Takashi Kitahara |
source
presentation source |
8 |
| PHUSE EU |
2016 |
Keeping Track of Database Changes During Database Lock |
Sanjiv Ramalingam |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Making the Leap from Excel to a Database Used for Reporting |
Shafi Chowdhury,
Marco Ackermann |
source
presentation source |
8 |
| PHUSE EU |
2016 |
Metadata on the Go: Achieving Metadata Accuracy and Consistency Continually |
Swapna Pothula |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Multiplicity Issues in Clinical Trials - Look at it with a Magnifying Glass! |
Madhusudhan Bandi |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Non-printable and Special Characters? BYTE Me! |
Louise Sims |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Programmed Patient Narratives Using SAS |
Prafulla Girase,
Daniel J. Boisvert |
source
presentation source |
7 |
| PHUSE EU |
2016 |
Protocol Representation: The Forgotten CDISC Model |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Reflections on the Effects of Data Pooling |
Catharina Dahlbo |
source
presentation source |
4 |
| PHUSE EU |
2016 |
Standard Methods for Analysis and Reporting of VAS or NRS Derived Pain Relief Response Scores |
James R. Johnson |
source
presentation source |
14 |
| PHUSE EU |
2016 |
Standard Safety Visualisation Set-up Using Spotfire |
Michaela Mertes |
source
presentation source |
10 |
| PHUSE EU |
2016 |
The Playbook: Real-world Data to Real-world Intelligence |
Laurie Rose,
S. Robert Collins |
source
presentation source |
7 |
| PHUSE EU |
2016 |
The TFL Workbench: Tools to Standardise and Accelerate Table, Figure and Listing (TFL) Programming |
Iain Humphreys,
Hansjörg Frenzel |
source
presentation source |
10 |
| PHUSE EU |
2016 |
The Tortoise Versus the Hare - And the Winner is... |
Meena Rahman,
Rebecca Leivers |
source
presentation source |
4 |
| PHUSE EU |
2016 |
Upstream with Your Statistician and a Data Visualisation Paddle |
Nick Cowans |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Use of Fast Healthcare Interoperability Resources (FHIR) in the Generation of Real World Evidence (RWE) |
Regina Zopf,
Jeffrey M. Abolafia,
Bhargava Reddy |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Using Graphics to Review and Present PK/PD Data for Maximum Impact |
Shafi Chowdhury,
Rajwanur Rahman |
source |
9 |
| PHUSE EU |
2016 |
What Auditors Want |
Angelo Tinazzi,
Cédric Marchand |
source
presentation source |
8 |
| PHUSE EU |
2016 |
What is high quality study metadata? |
Sergiy Sirichenko,
Max Kanevsky |
source
presentation source |
9 |
| MWSUG |
2016 |
Frequentist and Bayesian Interim Analysis in Clinical Trials: Group Sequential Testing and Posterior Predictive Probability Monitoring Using SAS |
Kechen Zhao |
|
14 |
| MWSUG |
2016 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng,
Mike Wise |
|
22 |
| MWSUG |
2016 |
Pre-Data Checks for SDTM Development |
Abhinav Srivastva |
|
10 |
| MWSUG |
2016 |
Read html files and create standard tables for BISR at KUMC |
Chuanwu Zhang,
John Keighley,
Byron J. Gajewski |
|
7 |
| MWSUG |
2016 |
The Power of Cumulative Distribution Function (CDF) Plot in Assessing Clinical Outcomes |
Min Chen,
Patricia Kultgen |
|
6 |
| PharmaSUG CN |
2016 |
Proportion difference and confidence interval based on Cochran-Mantel-Haenszel method in stratified multi-center clinical trial |
Huiping Zhang |
|
5 |
| WUSS |
2016 |
A Case of Retreatment - Handling Retreated Patient Data |
Sriramu Kundoor,
Seattle Genetics,
Sumida Urval |
source |
4 |
| WUSS |
2016 |
Are you ready for Dec 17th, 2016 - CDISC compliant data submission? |
Kevin Lee |
source |
6 |
| WUSS |
2016 |
Building Better ADaM Datasets Faster With If-Less Programming |
Lei Zhang |
source |
17 |
| WUSS |
2016 |
Constructing Confidence Intervals for the Differences of Binomial Proportions in SAS |
William Garner |
source |
13 |
| WUSS |
2016 |
Customized Flowcharts Using SAS Annotation |
Abhinav Srivastva |
source |
10 |
| WUSS |
2016 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng,
Mike Wise,
Justina M. Flavin |
source |
20 |
| WUSS |
2016 |
SDTM Bookmarking Automation: Leveraging SAS, Ghostscript and Form-Visit Study Data |
Nasser Al Ali,
Maria Paz |
source |
6 |
| WUSS |
2016 |
Why and What Standards for Oncology Studies (Solid Tumor, Lymphoma and Leukemia)? |
Kevin Lee |
source |
7 |
| PharmaSUG |
2016 |
"It is a standard, so it is simple, right?": Misconceptions and Organizational Challenges of Implementing CDISC at a CRO |
Susan H.M. Boquist,
Adam J. Sicard |
source |
5 |
| PharmaSUG |
2016 |
A Dose Escalation Method for Dual-Agent in Phase 1 Cancer Clinical Trial using the SAS MCMC Procedure |
Gwénaël Le Teuff,
Mohamed Amine Bayar |
source |
14 |
| PharmaSUG |
2016 |
A SAS Macro Tool to Automate Generation of Customized Patient Profile in PDF Documents |
Haining Li,
Merit E. Cudkowicz,
Hong Yu |
source |
6 |
| PharmaSUG |
2016 |
An Intersection of Pharma and Medical Devices - Development of Companion Diagnostics in Conjunction with Targeted Therapies |
Carey G. Smoak |
source |
4 |
| PharmaSUG |
2016 |
Associated Persons Domains - Who? What? Where? When? Why? How? |
Alyssa M. Wittle,
Michael Stackhouse |
source |
6 |
| PharmaSUG |
2016 |
Automatic Consistency Checking of Controlled Terminology among SDTM Datasets, Define.xml, and NCI/CDISC Controlled Terminology for FDA Submission |
Min Chen,
Xiangchen (Bob) Cui |
source |
13 |
| PharmaSUG |
2016 |
Building Efficiency and Quality in SDTM Development Cycle |
Kishore Pothuri,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2016 |
Considerations and Conventions within the Therapeutic Area User Guides (TAUGs) |
Jerry Salyers,
Kristin Kelly,
Fred Wood |
source |
8 |
| PharmaSUG |
2016 |
Creating Define-XML version 2 including Analysis Results Metadata with the SAS Clinical Standards Toolkit |
Lex Jansen |
source |
29 |
| PharmaSUG |
2016 |
Data Visualization for Quality Control in NONMEM Data set |
Linghui Zhang |
source |
9 |
| PharmaSUG |
2016 |
Delivering a quality CDISC compliant accelerated submission using an outsourced model |
Mei Dey,
Diane Peers |
source |
8 |
| PharmaSUG |
2016 |
Don-t Agonize, Organize: Maximizing efficiency and effectiveness of SAS Programming in Clinical Trials projects, by using Project Management Organizing Methodologies |
Shefalica Chand |
source |
8 |
| PharmaSUG |
2016 |
Efficient Safety Assessment in Clinical Trials using the Computer-generated AE Narratives of JMP Clinical |
Richard C. Zink,
Drew Foglia |
source |
13 |
| PharmaSUG |
2016 |
Empowering Users By Creating Data Visualization Applications In R/Shiny |
Sudhir Singh,
Brian Munneke,
Amulya R. Bista,
Jeff Cai |
source |
8 |
| PharmaSUG |
2016 |
Enough of Clinical ... Let's talk Pre-Clinical! |
Arun Raj Vidhyadharan,
Sunil Mohan Jairath |
source |
5 |
| PharmaSUG |
2016 |
Everything or Nothing - A Better Confidence Intervals for Binomial Proportion in Clinical Trial Data Analysis |
Sakthivel Sivam,
Subbiah Meenakshisundaram |
source |
8 |
| PharmaSUG |
2016 |
Handling Interim and Incomplete Data in a Clinical Trials Setting |
Paul Stutzman |
source |
13 |
| PharmaSUG |
2016 |
Importance of Niche Provider for Successful NDA Submission: Rescue Case Study |
Aparna Poona,
Bhavin Busa,
Tim Southwick |
source |
9 |
| PharmaSUG |
2016 |
Introduction of Semantic Technology for SAS programmers |
Kevin Lee |
source |
15 |
| PharmaSUG |
2016 |
Meaningful Presentation of Clinical Trial Data with Multiple Y-Axes Graph |
Mina Chen |
source |
5 |
| PharmaSUG |
2016 |
Moving from Data Collection to Data Visualization and Analytics: Leveraging CDISC SDTM Standards to Support Data Marts |
Steven R. Kirby,
Terek Peterson |
source |
8 |
| PharmaSUG |
2016 |
Novel Programming Methods for Change from Baseline Calculations |
Mina Chen,
Peter W. Eberhardt |
source |
7 |
| PharmaSUG |
2016 |
Preparing Legacy Format Data for Submission to the FDA - When & Why Must I Do It, What Guidance Should I Follow? |
David C. Izard |
source |
11 |
| PharmaSUG |
2016 |
Programming Support for Exposure-Response Analysis in Oncology Drug Development |
Peter Lu,
Hong Yan |
source |
8 |
| PharmaSUG |
2016 |
Scrambled Data - A Population PK/PD Programming Solution |
Sharmeen Reza |
source |
8 |
| PharmaSUG |
2016 |
SDTM Metadata: The Output is only as Good as the Input |
Sue Sullivan |
source |
9 |
| PharmaSUG |
2016 |
SDTM Trial Summary Domain: Putting Together the TS Puzzle |
Kristin Kelly,
Jerry Salyers,
Fred Wood |
source |
13 |
| PharmaSUG |
2016 |
Summarizing Adverse Events of Interest - Onset, Duration, and Resolution |
John Saida Shaik,
Avani Kaja |
source |
6 |
| PharmaSUG |
2016 |
The CDISC's are coming!! |
Annapurna Ravi,
Caroline Gray |
source |
7 |
| PharmaSUG |
2016 |
The New STREAM Procedure as a Virtual Medical Writer |
Joseph W. Hinson |
source |
13 |
| PharmaSUG |
2016 |
The Standard for the Exchange of Nonclinical Data (SEND): History, Basics, and Comparisons with Clinical Data |
Fred Wood |
source |
10 |
| PharmaSUG |
2016 |
There is No Time Like Present-Being from Elf to the True Self |
Rajinder Kumar,
Sudarshan Reddy Shabadu,
Houde Zhang |
source |
4 |
| PharmaSUG |
2016 |
Transforming Biomarker Data into an SDTM based Dataset |
Kiran Cherukuri |
source |
7 |
| PharmaSUG |
2016 |
Usage of Pinnacle 21 Community Toolset 2.1.1 for Clinical Programmers |
Sergiy Sirichenko,
Michael DiGiantomasso,
Travis Collopy |
source |
19 |
| PharmaSUG |
2016 |
What HIGHLOW Can Do for You |
Kristen Much,
Kaitlyn Steinmiller |
source |
12 |
| PharmaSUG |
2016 |
What is high quality study metadata? |
Sergiy Sirichenko,
Max Kanevsky |
source |
9 |
| PharmaSUG |
2016 |
What makes a "Statistical Programmer" different from a "Programmer" |
Arun Raj Vidhyadharan,
Sunil Mohan Jairath |
source |
12 |
| PharmaSUG |
2016 |
What-s the Case? Applying Different Methods of Conducting Retrospective Case/Control Experiments in Pharmacy Analytics |
Aran Canes |
source |
8 |
| SGF |
2016 |
3N Validation to Validate PROC COMPARE Output |
Amarnath Vijayarangan |
source
presentation |
7 |
| SGF |
2016 |
An Efficient Algorithm in SAS to Reconcile Two Different Serious Adverse Event (SAE) Data Sources |
Zhou Hui |
source |
7 |
| SGF |
2016 |
Careers in Biotatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| SGF |
2016 |
Data Review Listings on Auto-Pilot: Using SAS and Windows Server to Automate Reports and Flag Incremental Data Records |
Victor Lopez,
Heli Ghandehari,
Bill Knowlton,
Christopher J. Swearingen |
source |
12 |
| SGF |
2016 |
Graphical Results in Clinical Oncology Studies |
Nora Ruel |
source |
14 |
| SGF |
2016 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng,
Justina M. Flavin,
Michael Wise |
source |
20 |
| SGF |
2016 |
Missing Values: They Are NOT Nothing |
Justin Jia,
Shan Shan Lin |
source |
19 |
| SGF |
2016 |
PROC IMSTAT Boosts Knowledge Discovery in Big-Database (KDBD) in a Pharmaceutical Company |
Yoshitake Kitanishi,
Ryo Kiguchi,
Akio Tsuji,
Hideaki Watanabe |
source |
7 |
| MWSUG |
2015 |
Good SAS Programming Practices |
Pat O'Meara |
|
4 |
| MWSUG |
2015 |
Project Management of SAS Tasks - Excel Dashboard without Using Any Program |
Kalaivani Raghunathan |
|
5 |
| PHUSE EU |
2015 |
'Dude. Where's My Graph?' RDF Data Cubes for Clinical Trial Data |
Tim P. Williams,
Marc Andersen |
source
presentation source |
7 |
| PHUSE EU |
2015 |
A Lot More than Patient Data |
Nigel Montgomery,
Satyapal Gudla |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Are Your Ready for SEND? |
Roman Radelicki |
source
presentation source |
8 |
| PHUSE EU |
2015 |
AstraZeneca Clinical Trial Transparency and External Sharing of Individual Patient-level Data |
Natalie Andrews |
source
presentation source |
3 |
| PHUSE EU |
2015 |
Automated generation of program templates with metadata based specification documents for integrated analysis |
Thomas Wollseifen |
source
presentation source |
11 |
| PHUSE EU |
2015 |
Blinding the Unblinded |
Angelo Tinazzi,
Dean Shults |
source
presentation source |
6 |
| PHUSE EU |
2015 |
Close operation between Developers and End-Users is Vital to Deployment of CDISC Standard Software |
Donald Benoot |
source
presentation source |
8 |
| PHUSE EU |
2015 |
Constructing a Simple Data Repository [presentation] |
Magnus Mengelbier |
source |
19 |
| PHUSE EU |
2015 |
Data De-identification: Balancing Patient Privacy, Data Utility and Good Programming Practices |
Jon Davidson,
David Handelsman |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Data Encoding:All Characters for All Countries |
Donna Dutton |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Data Scientist - What It Is (Not) |
Michaela Jahn |
source
presentation source |
4 |
| PHUSE EU |
2015 |
Data-centric System Development Life Cycle for Automated Clinical Data Development Systems |
Kevin Lee |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Dataset-XML - A New CDISC Standard for Data Exchange |
Julie A. Maddox,
Lex Jansen |
source
presentation source |
16 |
| PHUSE EU |
2015 |
De-Id: 'The What' and 'The How' of de-identifying your Clinical Trial Data |
Gavin Winpenny,
Stephen Bamford |
source
presentation source |
11 |
| PHUSE EU |
2015 |
Detecting Irregularities in Electronic Patient-reported Data |
John van Bemmelen |
source
presentation source |
10 |
| PHUSE EU |
2015 |
Dynamic, Powerful, User-friendly SQL Joins Made Easy with %VARLIST, a Generic SAS Macro Function |
Jean-Michel Bodart |
source
presentation source |
8 |
| PHUSE EU |
2015 |
E2E Data Standards: The Need for a New Generation of Metadata Repositories |
Isabelle de Zegher |
source
presentation source |
4 |
| PHUSE EU |
2015 |
Efficient Data Reviews and Quality in Clinical Trials Using CDISC Data Standards |
Valérie Nedbal |
source |
11 |
| PHUSE EU |
2015 |
Establish the Maximum Tolerated Dose in Phase 1 Trials Using the 3+3 Method |
Anup Pillai |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Facing Your Fear of the Unknown - Handling Missing Data |
Amanda Reilly |
source
presentation source |
7 |
| PHUSE EU |
2015 |
FDA Review Principles Applied to CRO Oversight |
Sascha Ahrweiler,
Grace Ignacio |
source
presentation source |
7 |
| PHUSE EU |
2015 |
Flexible Solutions for Insight and Data-driven Innovation |
Catharina Dahblo |
source
presentation source |
6 |
| PHUSE EU |
2015 |
From Data Management to Statistical Programming: A Real-Life Change |
Benjamin Lerbour |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Future Drug Applications with No Tables, Listings and Graphs? |
Kirsten Langendorf |
source
presentation source |
5 |
| PHUSE EU |
2015 |
How a Clinical Data Repository can Support Pharmacovigilance |
Panteleo Nacci |
source
presentation source |
7 |
| PHUSE EU |
2015 |
How to Reduce Bias in the Estimates of Count Data Regression |
Ashwini Joshi,
Sumit Singh |
source
presentation source |
10 |
| PHUSE EU |
2015 |
Improving CDISC SDTM Data Quality & Compliance Right from the Beginning |
Bharat Chaudhary,
Padamsimh Balekundri |
source
presentation source |
9 |
| PHUSE EU |
2015 |
Independent Double Programming - Are We Doing the Right Thing? [presentation] |
Beate Hientszch |
source |
1 |
| PHUSE EU |
2015 |
Innovative Approach to Building an Adaptive Trial Design in Medidata Rave |
Joris De Bondt,
Tine Seeuws |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Metadata Snapshots: How SAS Drug Development API Macros Can Help |
Melissa R. Martinez |
source
presentation source |
12 |
| PHUSE EU |
2015 |
PASS and the Programmer |
Rachel Bowman |
source
presentation source |
7 |
| PHUSE EU |
2015 |
PHUSE De-identification Working Group: Providing identification Standards to CDISC Data Models |
Jean-Marc Ferran,
Khaled El Eman |
source
presentation source |
13 |
| PHUSE EU |
2015 |
Programming Strategically for PK/PD Data |
Grace Lu |
source
presentation source |
8 |
| PHUSE EU |
2015 |
Slim Down Your Data |
Mickael Borne |
source
presentation source |
10 |
| PHUSE EU |
2015 |
Study Anonymisation: From Request to Delivery |
Kelly Mewes,
Sai Jandhyala |
source
presentation source |
11 |
| PHUSE EU |
2015 |
The Data Listing Facility: Data is Just a Few Clicks Away |
Luigi De Vittorio |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Work Harder or Work Smarter? |
Colin Brown |
source
presentation source |
4 |
| WUSS |
2015 |
3N Validation to Validate PROC COMPARE Output |
Amarnath Vijayarangan |
source |
6 |
| WUSS |
2015 |
A Risk Factor Coding Custom Report Created With ODS Report Writing Interface With Recent Literature and Peer Review |
Robert Springborn |
source |
13 |
| WUSS |
2015 |
Graphical Results in Clinical Studies A focus on graphics used in oncology |
Nora Ruel,
Paul Frankel |
source |
12 |
| WUSS |
2015 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng |
source |
23 |
| WUSS |
2015 |
No Regrets: Hiring for the Long Term in Statistical Programming |
Chris Moriak,
Graham Wilson,
Elizabeth Meeson |
source |
7 |
| WUSS |
2015 |
SAPs are for saps: A guide to the ins and outs of SAPs in iterative, observational, or publication-oriented research |
Michelle Turner,
Lawrence Rasouliyan |
source |
4 |
| PharmaSUG CN |
2015 |
A Macro to Automatically Select Covariates from Prognostic Factors and Exploratory Factors for Multivariate Cox PH Model |
Yu Cheng |
|
6 |
| PharmaSUG CN |
2015 |
A proposal for intervention and event partial date time imputation [presentation] |
Zhao Chunpeng |
|
13 |
| PharmaSUG CN |
2015 |
Approaches to Missing Data in the Analysis of SpondyloArthritis International Society (ASAS 20) Response and the Creation of the Related CDISC Compliant Analysis Datasets |
Christine Joy Dureza |
|
12 |
| PharmaSUG CN |
2015 |
Clinical trials optimization: Monte Carlo Simulation modeling and SAS applications |
Ye Meng |
|
5 |
| PharmaSUG CN |
2015 |
Comparison of Three Methods in Calculating Confidence Intervals for Rate Differences in Non-inferior Clinical Trials |
Yaohua Huang |
|
4 |
| PharmaSUG CN |
2015 |
Handling multiple y axes using SAS Graphs |
Mina Chen,
Peter W. Eberhardt |
|
5 |
| PharmaSUG CN |
2015 |
Hands-on Tutorial for Piecewise Linear Mixed-effects Models Using SAS PROC MIXED |
Qinlei Huang |
|
15 |
| PharmaSUG CN |
2015 |
Multilingual data support in Dataset-XML with SAS Clinical Data Integration |
Jing Gao |
|
12 |
| PharmaSUG CN |
2015 |
SAS End-to-End solutions in Clinical Trial |
Emma Liu |
|
17 |
| PharmaSUG CN |
2015 |
SAS Tools for Working with Dataset-XML files |
Lex Jansen |
|
18 |
| PharmaSUG CN |
2015 |
SDTM Electronic Submissions to FDA: Guidelines and Best Practices |
Christina Chang,
Kyle Chang |
|
6 |
| PharmaSUG CN |
2015 |
Statistics And Programming In The Globally Evolving Landscape Of Clinical Trial Registration And Results (CTRR) Disclosure |
Paul Ngai,
Joyce Hauze |
|
8 |
| PharmaSUG CN |
2015 |
Summary level clinical site data for data integrity review and inspection planning in NDA and BLA submission [presentation] |
Jingwei Gao,
Nancy Bauer |
|
41 |
| PharmaSUG CN |
2015 |
Tips for efficient CDISC eCRT production |
Lanting Li,
Yu Zhu,
Yuejuan Meng,
Huan Zhu |
|
11 |
| PharmaSUG CN |
2015 |
Use of SAS for Risk-Based Monitoring of Survival Endpoints and Adverse Event Data in Clinical Trials |
Zhizhuo Zhang,
Sichan Tang,
Ka Chun Chong,
Benny Chung-Ying Zee |
|
5 |
| PharmaSUG CN |
2015 |
Why Statistical Analysis Plan (SAP) should be comprehensive. |
Riddhi Merchant,
Ranjith Prayankotveettil |
|
6 |
| PharmaSUG |
2015 |
A Methodology of Laboratory Data Reporting of Potentially Clinical Significant Abnormality (PCSA) for Clinical Study Report |
Xiangchen (Bob) Cui,
Min Chen |
source |
21 |
| PharmaSUG |
2015 |
A New Era: Open access to clinical Trial Data - A case study |
Aruna Kumari Panchumarthi,
Jacques Lanoue |
source |
6 |
| PharmaSUG |
2015 |
A Toolkit to Create a Dynamic Excel Format Metadata to Assist SDTM Mapping Process |
Huei-Ling Chen,
Helen Wang |
source |
11 |
| PharmaSUG |
2015 |
A Web-Based Approach to Fighting Analysis Chaos |
Gordon Fancher,
Rajeev Karanam,
Shawn Hopkins |
source |
7 |
| PharmaSUG |
2015 |
Adding Subversion Operations to the SAS Enhanced Editor |
Oscar F. Cheung,
Kenneth W. Borowiak |
source |
5 |
| PharmaSUG |
2015 |
Analysis Methods for a Sequential Parallel Comparison Design (SPCD) |
Harry Haber,
James Zuazo,
Linda LaMoreaux |
source |
11 |
| PharmaSUG |
2015 |
Begin with the End in Mind - Using FDA Guidance Documents as Guideposts when Planning, Delivering and Archiving Clinical Trials |
David C. Izard |
source |
12 |
| PharmaSUG |
2015 |
Clinical knowledge helps SAS programmers in the pharmaceutical industry get job done better |
Yingqiu Yvette Liu |
source |
4 |
| PharmaSUG |
2015 |
Considerations in Conforming Data from Multiple Implantable Medical Devices to CDISC Standards Using SAS |
Julia Yang |
source |
9 |
| PharmaSUG |
2015 |
CRO, TLF, SOP? OMG!: A Beginner's Guide to the Clinical Research Organization |
Mandy Bowen,
Otis Evans,
Stephen Terry |
source |
7 |
| PharmaSUG |
2015 |
DIABETES: Submission Data Standards and Therapeutic End Points |
Naveed M Khaja |
source |
9 |
| PharmaSUG |
2015 |
Firefighters - clinical trial analysis teams |
Iryna Kotenko |
source |
4 |
| PharmaSUG |
2015 |
Graphical Presentation of Clinical Data in Oncology Trials |
Murali Kanakenahalli,
Avani Kaja |
source |
10 |
| PharmaSUG |
2015 |
Lessons Learned from the QC Process in Outsourcing Model |
Faye Yeh |
source |
5 |
| PharmaSUG |
2015 |
LOCF vs. LOV in Endpoint DTYPE Development with CDISC ADaM Standards |
Maggie Ci Jiang |
source |
6 |
| PharmaSUG |
2015 |
Managing Custom Data Standards in SAS Clinical Data Integration |
Melissa R. Martinez |
source |
17 |
| PharmaSUG |
2015 |
Missing Data For Repeated Measures: Single Imputation VS Multiple Imputation |
Giulia Tonini,
Simona Scartoni,
Camilla Paoli,
Andrea Nizzardo,
Angela Capriati |
source |
10 |
| PharmaSUG |
2015 |
MMRM: Macro for Selecting Best Covariance Structure with the Method of Interest |
Linga Reddy Baddam,
Sudarshan Reddy Shabadu,
Chunxue Shi |
source |
7 |
| PharmaSUG |
2015 |
No Regrets: Hiring for the Long Term in Statistical Programming |
Chris Moriak,
Graham Wilson,
Elizabeth Meeson |
source |
7 |
| PharmaSUG |
2015 |
Now You See It, Now You Don't - Using SAS to De-Identify Data to Support Clinical Trial Data Transparency |
David Handelsman |
source |
7 |
| PharmaSUG |
2015 |
OSI Packages: What you need to know for your next NDA or BLA Submission |
Thaddea Dreyer,
Tatiana Scetinina |
source |
10 |
| PharmaSUG |
2015 |
Patient Profiles and SAS Visual Analytics |
Pritesh Desai,
S. Robert Collins |
source |
9 |
| PharmaSUG |
2015 |
PhUSE De-Identification Working Group: Providing De-Identification Standards to CDISC Data Models |
Jean-Marc Ferran,
Jacques Lanoue |
source |
8 |
| PharmaSUG |
2015 |
Programming Pharmacokinetic (PK) Timing and Dosing Variables in Oncology Studies: Demystified |
Kiran Cherukuri |
source |
9 |
| PharmaSUG |
2015 |
Qualification Process for Standard Scripts in the Open Source Repository with Cloud Services |
Hanming Tu,
Dante Di Tommaso,
Dirk Spruck,
Christopher C. Hurley,
Nancy Brucken |
source |
6 |
| PharmaSUG |
2015 |
SAS Tools for Working with Dataset-XML files |
Lex Jansen |
source |
18 |
| PharmaSUG |
2015 |
SDTM TE, TA, and SE Domains: Demystifying the Development of SE |
Kristin Kelly,
Fred Wood,
Jerry Salyers |
source |
6 |
| PharmaSUG |
2015 |
Subset without Upsets: Concepts and Techniques to Subset SDTM Data |
Jhelum Naik,
Sajeet Pavate |
source |
6 |
| PharmaSUG |
2015 |
Summing up - SDTM Trial Summary Domain |
Yi Liu,
Jenny Erskine,
Stephen Read |
source |
9 |
| PharmaSUG |
2015 |
Tackling Clinical Lab Data in Medical Device Environment |
Juan Wu,
Min Lai |
source |
7 |
| PharmaSUG |
2015 |
The 5 Most Important Clinical SAS Programming Validation Steps |
Brian C. Shilling |
source |
6 |
| PharmaSUG |
2015 |
The Most Common Issues in Submission Data |
Sergiy Sirichenko,
Max Kanevsky |
source |
9 |
| PharmaSUG |
2015 |
Things Are Not Always What They Look Like: PROC FORMAT in Action |
Peter W. Eberhardt,
Lucheng Shao |
source |
23 |
| PharmaSUG |
2015 |
Toward Adoption of Agile Software Development in Clinical Trials |
Troy Martin Hughes |
source |
7 |
| PharmaSUG |
2015 |
Two different use cases to obtain best responses using RECIST 1.1: SDTM and ADaM |
Kevin Lee,
Vikash Jain |
source |
17 |
| PharmaSUG |
2015 |
Unpacking an Excel Cell: Dealing with Multi-Line Excel Cells in SAS |
Lucheng Shao |
source |
10 |
| PharmaSUG |
2015 |
Update: Development of White Papers and Standard Scripts for Analysis and Programming |
Nancy Brucken,
Michael Carniello,
Mary Nilsson,
Hanming Tu |
source |
4 |
| PharmaSUG |
2015 |
Usage of OpenCDISC Community Toolset 2.0 for Clinical Programmers |
Sergiy Sirichenko,
Michael DiGiantomasso,
Travis Collopy |
source |
19 |
| PharmaSUG |
2015 |
Use of SAS Reports for External Vendor Data Reconciliation |
Soujanya Konda |
source |
12 |
| PharmaSUG |
2015 |
Using Meta-data to Identify Unused Variables on Input Data Sets |
Keith Hibbetts |
source |
4 |
| PharmaSUG |
2015 |
Utilizing SAS for Cross-Report Verification in a Clinical Trials Setting |
Daniel Szydlo,
Iraj Mohebalian,
Marla J. Husnik |
source |
12 |
| PharmaSUG |
2015 |
Where are the SAS Jobs? |
Beth Ward,
Chelsea Jackson |
source |
3 |
| SGF |
2015 |
Visualizing Clinical Trial Data: Small Data, Big Insights |
Michael Drutar,
Elliot Inman |
source |
18 |
| SESUG |
2014 |
A Comprehensive Automated Data Management System For Clinical Trials |
Heather F. Eng,
Jason A. Lyons,
Theresa M. Sax |
source |
12 |
| PHUSE EU |
2014 |
A Day in the Life of a Data Sharing Specialist [presentation] |
Kelly Mewes |
source |
29 |
| PHUSE EU |
2014 |
A New Era: Open Access to Clinical Trial Data [presentation] |
Guillaume Breton |
source |
21 |
| PHUSE EU |
2014 |
Analysis of Time to FDA Medwatch Safety Alert for Therapeutic Monoclonal Antibodies |
Pavla Kadlecová,
Vid Stanulovic |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Analysis of Time to FDA Medwatch Safety Alert for Therapeutic Monoclonal Antibodies |
Pava Kadlecova,
Vid Stanulovic |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Automated Generation of Program Documentation by Means of Tagged SAS Comments and Metadata for Integrated Analysis |
Thomas Wollseifen |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Big Data - Step towards High Performance Analytics |
Dhiraj Dabhi |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Biomarker as Essential Part of Clinical Development |
Renuka Chinthapally |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Challenges of Different MedDRA Versions for Integrated Data and Databases |
Peter Bonata |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Checking Symmetry in Predefined Time Assessments |
Antonio Nieto,
José Luis Jiménez Moro |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Clinical Site Dataset in eSubmissions to the FDA |
Stefanie Sturm |
source
presentation source |
3 |
| PHUSE EU |
2014 |
Clinical Study Data Processes @ LEO Pharma |
Joergen Iversen |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Collaborative Development of an Open Source Repository for Standardised Analysis Using Cloud Services [presentation] |
Michael Carniello,
Hamming TU |
source |
1 |
| PHUSE EU |
2014 |
Concept for a Clinical Trial Reporting System |
Daniil Shliakhov |
source
presentation source |
2 |
| PHUSE EU |
2014 |
Considerations in Creating Transparent SDTM-Based Datasets |
Jerry Salyers,
Richard Lewis |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Creating Standard Analyses and Displays for Common Safety Assessments in Clinical Study Reports |
Mary Nilsson,
Ann Croft |
source
presentation source |
3 |
| PHUSE EU |
2014 |
Data Challenges in Adaptive Trials |
Claudio Garutti |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Data Transparency through Metatada Management |
Judith Goud,
Julie Smiley |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Data Transparency: Moving from Bad Pharma to Good Science [presentation] |
Gary Hearfield,
Katherine Tucker |
source |
1 |
| PHUSE EU |
2014 |
Development of Exploratory Statistical Programmers Based in India |
Jan Stefanek |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Discover Define-XML |
Mark Wheeldon,
Kevin Burges |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Do You Like What You See? - Understanding Data in Magnetic Resonance Imaging Studies |
Oliver Wirtz |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Dynamic Oceans and Static Poolings of Clinical Trial Data in NVx |
Panteleo Nacci |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Evaluating the Tradeoff between Quality of Life through Quality-Adjusted Survival Analysis |
Lawrence Rasouliyan |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Every Study is Special! - Governing Data Standards |
Chris Price,
Elizabeth Nicol |
source
presentation source |
12 |
| PHUSE EU |
2014 |
From Gene Expression to Expression Cartography, Grade Correspondence Analysis Application in Class Comparison Studies |
Edyta Winciorek |
source
presentation source |
6 |
| PHUSE EU |
2014 |
From ODM to SDTM: An End-to-End Approach Applied to Phase I Clinical Trials |
Alexandre Mathis |
source
presentation source |
5 |
| PHUSE EU |
2014 |
How the Release of the Therapeutic Area Asthma User Guide Affects an Ongoing Submission |
Nick De Donder |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Implementation of Oncology Specific SDTM Domains |
Jacintha Eben |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Interactive Data Visualisation of Adverse Event Clinical Trial Data with the D3.js. Script Library |
Johann Laurent,
Hugh McDevitt |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Lessons Learned by Comparing "using SAS" as and Epidemiological Researcher and "using SAS" as a Statistical Programmer |
Joris Derks |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Managing the Change - Evolving Statistical Programmers to Clinical Data Scientists |
Sascha Ahrweiler |
source
presentation source |
10 |
| PHUSE EU |
2014 |
MedDRA - Beyond that Basic AE Report. How SMQs and MedDRA Structure can Enhance Reporting |
Pamela J. Giese |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Medical Data Review and Exploratory Data Analysis using Data Visualisation |
Joel Allen,
Vinod Kerai |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Models, Metadata and Messaging: Exploring Standards Governance in the CDISC Era |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Monitoring Clinical Trials with a SAS Risk-Based Approach |
Laurie Rose |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Multiple Imputation: Better than Single Imputation in Pain Studies |
Ashik Chowdhury |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Oncology Efficacy Endpoints |
Sarah Berenbrick |
source
presentation source |
3 |
| PHUSE EU |
2014 |
PROC EASTMONITOR - A SAS Add-on for Monitoring Adaptive Clinical Trials |
Sheetal Solanki,
Ajay Sathe |
source
presentation source |
15 |
| PHUSE EU |
2014 |
Programming and Statistics in the Academics Environment [presentation] |
Arne Ring |
source |
21 |
| PHUSE EU |
2014 |
Risk based monitoring using integrated clinical development platform Authors |
Sita Rama Swamy Peddiboyina,
Shailesh Vijay Joshi |
source
presentation source |
9 |
| PHUSE EU |
2014 |
SAS in Clinical Trial - A Relook at Project Management, Tools and Software Engineering |
Sameera Nandigama |
source
presentation source |
12 |
| PHUSE EU |
2014 |
SDTM Mapping Becomes more EASY with SAS Clinical Data Integration |
Saumilkumar Tripathi |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Signal Detection of Misconduct in Clinical Trials |
Geoffrey A. Mann,
Richard C. Zink |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Standards Driven Innovation [presentation] |
Frederik Malfait |
source |
36 |
| PHUSE EU |
2014 |
Successfully Embracing Challenges to CDISC Standards [presentation] |
Elke Sennewald |
source |
30 |
| PHUSE EU |
2014 |
The Capish Information Model - Simplify Access to Your Data |
Anna Berg,
Catharina Dahlbo |
source
presentation source |
8 |
| PHUSE EU |
2014 |
The On-Going Evolutionary Changes of our Industry [presentation] |
Christian Mueller |
source |
34 |
| PHUSE EU |
2014 |
The PHUSE Therapeutic Area Wiki Page |
Jothy Kalathiparampil,
Oliver Wirtz |
source
presentation source |
2 |
| PHUSE EU |
2014 |
The Quality System in Good Pharmacovigilance Practice (GVP) |
Veronique Chapalain |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Traceability: Plan Ahead for Future Needs |
Sandra Minjoe |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Transparency in the Time of Constant Change |
Todd Case |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Unuttered Questions of Statistical Programmers |
Aparajita Dey |
source
presentation source |
10 |
| PHUSE EU |
2014 |
Update on Regulatory Guidance: Data Standardisation Planning for Clinical Development Programs |
James R. Johnson |
source
presentation source |
10 |
| PHUSE EU |
2014 |
Using SAS Arrays |
Ruurd Bennink |
source
presentation source |
7 |
| MWSUG |
2014 |
A Comprehensive Automated Data Management System For Clinical Trials |
Heather F. Eng,
Jason A. Lyons,
Theresa M. Sax |
|
12 |
| MWSUG |
2014 |
Case Study: Generating Clinical Trial Summary Plots from an ORACLE database using the SAS Macro Language |
Shannon L. Morrison |
|
8 |
| MWSUG |
2014 |
So You Want to be SAS Certified |
Ben Cochran |
|
10 |
| PharmaSUG CN |
2014 |
Brief Introduction of Oncology Domains in SDTMIG,Version 3.2 |
Haishan Kadeerbai |
|
3 |
| PharmaSUG CN |
2014 |
Collapsing Adverse Event Records |
Haiqiang Luo |
|
7 |
| PharmaSUG CN |
2014 |
Data Transparency and Sharing: Research Benefits, Risks and the Future |
Janet E. Stuelpner,
Matthew J. Becker |
|
3 |
| PharmaSUG CN |
2014 |
Plotting Against Cancer: Creating Oncology Plots Using SAS |
Debpriya Sarkar |
|
30 |
| PharmaSUG CN |
2014 |
Visualizing Clinical Trial Data |
Matthew J. Becker |
|
10 |
| WUSS |
2014 |
Big Data in a Small Trial: Visual and Statistical Analyses in an N-of-1 Clinical Trial |
Marie Boman-Davis |
source |
6 |
| WUSS |
2014 |
Careers in Biostatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| WUSS |
2014 |
Dealing with Missing Data in Clinical Trials |
Lucheng Shao |
source |
12 |
| WUSS |
2014 |
Quick Analysis and Visualization of Excluded and Missing Data |
Polina Kukhareva |
source |
9 |
| PharmaSUG |
2014 |
A User Friendly Tool to Facilitate the Data Integration Process |
Yang Wang,
Boxun Zhang |
source |
6 |
| PharmaSUG |
2014 |
Adopted Changes for SDTMIG v3.1.3 and 2013 OpenCDISC Upgrades |
Yi Liu,
Stephen Read |
source |
17 |
| PharmaSUG |
2014 |
Attain 100% Confidence in Your 95% Confidence Interval |
Indu Nair,
Binal Patel |
source |
9 |
| PharmaSUG |
2014 |
Bad Date: How to find true love with Partial Dates! |
Namrata Pokhrel |
source |
11 |
| PharmaSUG |
2014 |
Building Better Programming Teams with Situational Exposure Training |
Elizabeth Reinbolt,
Steven R. Kirby |
source |
3 |
| PharmaSUG |
2014 |
Careers in Biostatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| PharmaSUG |
2014 |
Challenges in Moving to a Multi-tier Server Platform |
Carey G. Smoak |
source |
5 |
| PharmaSUG |
2014 |
Clinical Data Dashboards for Centralized Monitoring Using SAS and Microsoft SharePoint |
Jagan Mohan Achi |
source |
9 |
| PharmaSUG |
2014 |
Clinical Study Report Review: Statistician's Approach |
Amita Dalvi |
source |
6 |
| PharmaSUG |
2014 |
Clinical Trial Data Integration: The Strategy, Benefits, and Logistics of Integrating Across a Compound |
Natalie Reynolds,
Keith Hibbetts |
source |
12 |
| PharmaSUG |
2014 |
Come Out of Your Shell: A Dynamic Approach to Shell Implementation in Table and Listing Programs |
Paul Burmenko,
Tony Cardozo |
source |
13 |
| PharmaSUG |
2014 |
Common Variables in Adverse Event and Exposure analysis datasets specific for Oncology clinical trials |
Haridasan Namboodiri |
source |
11 |
| PharmaSUG |
2014 |
Considerations in Creating SDTM Trial Design Datasets |
Jerry Salyers,
Richard Lewis,
Kimberly Minkalis,
Fred Wood |
source |
9 |
| PharmaSUG |
2014 |
Cover the Basics, Tool for structuring data checking with SAS |
Ole Zester |
source |
10 |
| PharmaSUG |
2014 |
Creating Define-XML version 2 with the SAS Clinical Standards Toolkit 1.6 |
Lex Jansen |
source |
33 |
| PharmaSUG |
2014 |
Data Standards Development for Therapeutic Areas: A Focus on SDTM-Based Datasets |
Fred Wood,
Diane Wold,
Rhonda Facile,
Wayne Kubick |
source |
10 |
| PharmaSUG |
2014 |
Dealing with Missing Data in Clinical Trials |
Lucheng Shao |
source |
13 |
| PharmaSUG |
2014 |
DefKit : A Micro Framework for CDISC Define-XML Application Development |
Lei Zhang |
source |
23 |
| PharmaSUG |
2014 |
Demystify "Ten years of pharma programming experience required" - What hiring managers actually look for |
Peng Yang |
source |
3 |
| PharmaSUG |
2014 |
Developing Graphical Standards: A Collaborative, Cross-Functional Approach |
Mayur Uttarwar,
Murali Kanakenahalli |
source |
5 |
| PharmaSUG |
2014 |
Discover Define-XML |
Mark Wheeldon,
Kevin Burges |
source |
12 |
| PharmaSUG |
2014 |
Effective Use of Metadata in Analysis Reporting |
Jeffrey M. Abolafia |
source |
9 |
| PharmaSUG |
2014 |
Factor Analysis of Scale for Assessment of Negative Symptoms using SAS Software |
Ben Adeyi,
David Shen |
source |
8 |
| PharmaSUG |
2014 |
Good versus Better SDTM - Why "Good Enough" May No Longer Be Good Enough When It Comes to SDTM |
Henry B. Winsor |
source |
6 |
| PharmaSUG |
2014 |
Graphical Representation of Patient Profile for Efficacy Analyses in Oncology |
William Wu,
Xiaoxian Dai,
Linda Gau |
source |
7 |
| PharmaSUG |
2014 |
Handling with missing data in clinical trials for time-to-event variables |
Giulia Tonini,
Simona Scartoni,
Angela Capriati |
source |
9 |
| PharmaSUG |
2014 |
How To Win Friends and Influence People - A Programmer's Perspective in Effective Human Relationships |
Priscilla Gathoni |
source |
9 |
| PharmaSUG |
2014 |
Kaizen |
Usha Kumar |
source |
5 |
| PharmaSUG |
2014 |
Let Hash SUMINC Count For You |
Joseph W. Hinson |
source |
7 |
| PharmaSUG |
2014 |
Linking Healthcare Claims and Electronic Health Records (EHR) for Patient Management - Diabetes Case Study |
Paul A. LaBrec |
source |
17 |
| PharmaSUG |
2014 |
Methodology for Non-Randomized Clinical Trials: Propensity Score Analysis |
Dan Conroy |
source |
5 |
| PharmaSUG |
2014 |
Monitoring Quality, Time and Costs of Clinical Trial Programming Projects using SAS |
Jagan Mohan Achi |
source |
4 |
| PharmaSUG |
2014 |
Pharma Company Questions and Answers |
Joseph J. Hantsch |
source |
3 |
| PharmaSUG |
2014 |
QC made easy using macros |
Prashanthi Selvakumar |
source |
7 |
| PharmaSUG |
2014 |
Quickly Organize Statistical Output for Review |
Bradford J. Danner |
source |
4 |
| PharmaSUG |
2014 |
Reducing Variable Lengths for Submission Dataset Size Reduction |
Sandra VanPelt Nguyen |
source |
6 |
| PharmaSUG |
2014 |
Risk-Based Approach to Identifying and Selecting Clinical Sites for Sponsor's Preparation for FDA/EMA Inspection |
Xiangchen (Bob) Cui |
source |
21 |
| PharmaSUG |
2014 |
Risk-Based Monitoring of Clinical Trials Using JMP Clinical |
Richard C. Zink,
Kelci J. Miclaus |
source |
15 |
| PharmaSUG |
2014 |
Route to SDTM Implementation in In-Vitro Diagnostic Industry: Simple or Twisted |
Carey G. Smoak,
Sofia Shamas,
Chowdagam Chaitanya,
Don Lim,
Girish Rajeev |
source |
10 |
| PharmaSUG |
2014 |
Survival Analysis Approaches and New Developments using SAS |
Jane Lu,
David Shen |
source |
13 |
| PharmaSUG |
2014 |
The New Tradition: SAS Clinical Data Integration |
Vincent J. Amoruccio,
Janet E. Stuelpner |
source |
18 |
| PharmaSUG |
2014 |
Tips for Creating SAS-Based Applications for Oracle Clinical |
Kunal Agnihotri,
Kenneth W. Borowiak |
source |
6 |
| PharmaSUG |
2014 |
Tips to Manipulate the Partial Dates |
Deli Wang,
Chunxia Lin |
source |
4 |
| PharmaSUG |
2014 |
Update: Development of White Papers and Standard Scripts for Analysis and Programming |
Nancy Brucken,
Michael Carniello,
Mary Nilsson,
Hanming Tu |
source |
3 |
| SGF |
2014 |
Automatic and Efficient Post-Campaign Analyses By Using SAS Macro Programs |
Justin Jia,
Amanda Lin |
source |
12 |
| SGF |
2014 |
Bayesian Framework in Early Phase Drug Development with SAS Examples |
Howard Liang |
source |
4 |
| SGF |
2014 |
Combined SAS ODS Graphics Procedures with ODS to Create Graphs of Individual Data |
Howard Liang |
source |
6 |
| SGF |
2014 |
Converting Clinical Database to SDTM: The SAS Implementation |
Hong Chen |
source |
5 |
| SGF |
2014 |
Plotting Against Cancer: Creating Oncology Plots Using SAS |
Debpriya Sarkar |
source |
30 |
| SGF |
2014 |
Programmatic Challenges of Dose Tapering Using SAS |
Iuliana Barbalau,
Chen Shi,
Yang Yang |
source |
9 |
| SGF |
2014 |
Risk-Based Monitoring of Clinical Trials Using JMP Clinical |
Richard C. Zink |
source |
14 |
| SGF |
2014 |
Sensitivity Analysis in Multiple Imputation for Missing Data |
Yang Yuan |
source |
12 |
| SGF |
2014 |
The Commonly Used Statistical Methods to Control The Probability of an Overall Type I Error and the Application in Clinical Trial |
Lixiang Yao |
source |
7 |
| WUSS |
2013 |
Building a Controlled Statistical Programming Environment |
Wayne F. Woo |
source |
10 |
| WUSS |
2013 |
Challenges in Moving to a Multi-tier Server Platform |
Carey G. Smoak |
source |
5 |
| WUSS |
2013 |
Creating Graphical Patient Profiles Using SAS |
William Garner |
source |
12 |
| WUSS |
2013 |
Customize Comparison Tables for Clinical Studies |
Polina Kukhareva,
Katherine J. Roggenkamp |
source |
12 |
| WUSS |
2013 |
Generation of Subset Listings |
William Coar |
source |
13 |
| WUSS |
2013 |
Graphical Representation of Patient Profile for Efficacy Analyses in Oncology |
William Wu,
Xiaoxian Dai,
Linda Gau |
source |
7 |
| WUSS |
2013 |
Implementation of DEFINE.XML Generators using SAS Hash Objects and User-Defined Functions |
Lei Zhang |
source |
19 |
| WUSS |
2013 |
Need to Find a Date? |
William Coar |
source |
8 |
| SESUG |
2013 |
Imputing Dose Levels for Adverse Events |
John R. Gerlach,
Igor Kolodezh |
source |
8 |
| SESUG |
2013 |
KAPLAN-MEIER ANALYSIS: A PRACTICAL GUIDE FOR PROGRAMMERS |
Madhi Saranadasa |
source |
7 |
| PHUSE EU |
2013 |
ADaM Standards - Organising the Unorganised |
Heike Reichert |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Call for Scripts and Get Involved with FDA/PHUSE Scripts Repository |
Lina Ulkjaer Jorensen |
source
presentation source |
2 |
| PHUSE EU |
2013 |
CARE to CRaM |
Greg Fuller |
source
presentation source |
16 |
| PHUSE EU |
2013 |
Central Statistical Monitoring in Action |
Francois Torche,
Erik Doffagne |
source |
6 |
| PHUSE EU |
2013 |
Computation of Cls for Binomial Proportions in SAS and its Practical Difficulties |
Jose Abraham |
source
presentation source |
8 |
| PHUSE EU |
2013 |
Cross-sectional and Episodic Deduplication in Record Linkage |
Rients van Wijngaarden |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Define-XML v2 - What's New |
Lex Jansen |
source
presentation source |
15 |
| PHUSE EU |
2013 |
Descriptive Summary Tables Made Easy |
Shafi Chowdhury,
Mohammad Siddick |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Economic Evaluation in Clinical Trials. You Can Do it with SAS |
Artur Usov |
source
presentation source |
12 |
| PHUSE EU |
2013 |
Elephants and Storms - Using Big Data Techniques for Analysis of Large and Changing Datasets |
Geoff Low |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Help your Fellow Colleagues: Customised SAS Graphs Could Provide Peek into Subject's Progress |
Arun Lal,
Jari Ahvenainen |
source
presentation source |
8 |
| PHUSE EU |
2013 |
HL7 RIM - An Introduction for Non-Technical Professionals |
Joerg Dillert |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Mission Possible: Your Assignment is to Validate Output for a Study |
Susan Fehrer Coulson |
source
presentation source |
7 |
| PHUSE EU |
2013 |
My Big Data Experience - Getting my Feet Wet in the PUddle and Still Treading Water 2 Years Later |
Robert Walls |
source
presentation source |
10 |
| PHUSE EU |
2013 |
My First QlikView Application "CTI" [presentation] |
Anthony Caudard |
source |
12 |
| PHUSE EU |
2013 |
of 7 |
Jules Van der Zalm |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Oncology Endpoints: An Unexpected Journey |
Waseem Jugon,
Mijanur Rahman |
source |
12 |
| PHUSE EU |
2013 |
Organising Deliverables for Clinical Trials - The Concept of Analyses and its Implementation in EXACT |
Hansjörg Frenzel |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Orphan Indication Therapies: Programming for a Patient Population without Options [presentation] |
Todd Case |
source |
24 |
| PHUSE EU |
2013 |
Patient Cloud and the Future of Clinical Trials [presentation] |
Christopher Temme |
source |
24 |
| PHUSE EU |
2013 |
Pharmacokinetics Standardisation: Patients' Healthcare is Becoming Central |
Francois Vandenhende |
source
presentation source |
4 |
| PHUSE EU |
2013 |
Posch-Bauer Seamless Test with SAS |
Antonio Nieto,
Javier Gómez |
source
presentation source |
4 |
| PHUSE EU |
2013 |
Reporting on Oracle Clinical by JReview |
Fleury Randrianarivo |
source
presentation source |
2 |
| PHUSE EU |
2013 |
SDTM Oncology Domains: From Patient to Data to Narrative |
Kennenth Stolzfus |
source
presentation source |
4 |
| PHUSE EU |
2013 |
Semantic Technology and CDISC Standards |
Frederik Malfait,
Scott A. Bahlavooni |
source
presentation source |
13 |
| PHUSE EU |
2013 |
Spotfire for Statisticians and Statistical Programmers [presentation] |
Alistair Dootson,
Mark Demesmaeker |
source |
17 |
| PHUSE EU |
2013 |
Standard Protocols Using Guided Navigation [presentation] |
Michaela Jahn |
source |
15 |
| PHUSE EU |
2013 |
Standardising the Standards - The Benefits of Consistency |
Nathan James |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Standards for the Management of Clinical Trial Data, Why are they Needed, What is Needed? |
Isabelle Abousahl |
source
presentation source |
11 |
| PHUSE EU |
2013 |
Statistics: The Fourth Dimension of a "Statistical Programmer" |
Gauri Khatu,
Vibhavari Inamadar |
source |
12 |
| PHUSE EU |
2013 |
The AZ-PLM Nausea Study: A Novel Patient-Centric Collaboration |
Jim Weatherall,
Alderley Park |
source
presentation source |
10 |
| PHUSE EU |
2013 |
The Missing Link: Results Level Metadata |
Jeffrey M. Abolafia |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Time Travel for Librarians: Versioning Complex Library Metadata for Past, Present or Future Retrieval |
Nico De Leeuw,
Ine Felsenstein |
source
presentation source |
12 |
| PHUSE EU |
2013 |
Using PROC GENMOD to Analyses Ratio to Placebo in Change of Dactylitis |
Imgard Hollweck |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Utilising Data Warehousing to Validate Clinical Trial Projects and to Select and Recruit Patients [presentation] |
Tim Armitage |
source |
39 |
| PHUSE EU |
2013 |
Visual Approaches for Safety Analysis and Review of Clinical Trials [presentation] |
Valérie Nedbal |
source |
34 |
| NESUG |
2013 |
Converting from a Windows Based SAS Computing Environment to a UNIX Based SAS Computing Environment |
Ginger Redner,
Dan Maloney |
|
8 |
| NESUG |
2013 |
How to Create High Level Data Review Tools |
Xiaoyu (Sean) Liu |
|
4 |
| NESUG |
2013 |
How to Handle Binomial Proportion with Zero Frequency |
Tulin Shekar |
|
11 |
| NESUG |
2013 |
Merging SAS Programming Groups: Phased-in Approach |
Margaret M. Coughlin,
Alfredo Rojas |
|
5 |
| NESUG |
2013 |
The Ultimate Macro to Generate Summary Tables |
Lan Hu,
Xiaoqiang Wang |
|
12 |
| NESUG |
2013 |
Use of SAS for Clinical Trial Management and Risk-Based Monitoring of Multicenter Clinical Trial Data from Electronic Data Capture Tools |
Bob Hall,
David Gagnon |
|
14 |
| PharmaSUG |
2013 |
A Drug Safety Reporting System in SAS |
Yang Wang,
Shawn Hopkins,
Norm Fox,
Raghu Kumbharathi,
Tom Hunter |
source |
7 |
| PharmaSUG |
2013 |
A Picture is worth 3000 words!! 3D Visualization using SAS |
Suhas R. Sanjee |
source |
6 |
| PharmaSUG |
2013 |
A Simple Interface for Meta-Data |
Magnus Mengelbier |
source |
8 |
| PharmaSUG |
2013 |
Analysis of Concomitant Medication Data |
Joseph J. Hantsch,
Karl Miller |
source |
4 |
| PharmaSUG |
2013 |
Atypical Applications of the UPDATE Statement |
John Henry King |
source |
5 |
| PharmaSUG |
2013 |
Bayesian Analysis of Survival Data with SAS PHREG Procedure |
Ryan Brady |
source |
8 |
| PharmaSUG |
2013 |
Be a Dead Cert for a SAS Cert: How to prepare for the most important SAS Certifications in the Pharmaceutical Industry |
Hannes Engberg Raeder |
source |
10 |
| PharmaSUG |
2013 |
Clinical Trials: If You Can Explain Them to Second Graders, You Can Explain Them to Anyone! |
Lara E.H. Guttadauro |
source |
5 |
| PharmaSUG |
2013 |
Combining Analysis Results from Multiply Imputed Categorical Data |
Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly |
source |
19 |
| PharmaSUG |
2013 |
Communication of Statistical Findings by Tables and Graphs |
Howard Liang |
source |
12 |
| PharmaSUG |
2013 |
Defensive Programming and Error-handling: The Path Less Travelled |
Tracy Sherman,
Angela S. Ringelberg |
source |
9 |
| PharmaSUG |
2013 |
Deployment of SAS Programming Contract Staff: Pathway to Sinkhole or Best Strategy for Programming Division? |
Parag Shiralkar |
source |
5 |
| PharmaSUG |
2013 |
Doctoring Your Clinical Trial with Adaptive Randomization: SAS Macros to Perform Adaptive Randomization |
Jenna Colavincenzo |
source |
9 |
| PharmaSUG |
2013 |
Efficient Statistical Review Using the ExcelXP Tagset |
Bradford J. Danner |
source |
5 |
| PharmaSUG |
2013 |
Experiences in Preparing Summary Level Clinical Site Data within NDA's Submission for FDA's Inspection Planning |
Xiangchen (Bob) Cui |
source |
19 |
| PharmaSUG |
2013 |
Flags for Facilitating Statistical Analysis Using CDISC Analysis Data Model |
Chun Feng,
Xiaopeng Li,
Nancy Wang |
source |
6 |
| PharmaSUG |
2013 |
From Standards that Cost To Standards that Save: Cost Effective Standards Implementation |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
9 |
| PharmaSUG |
2013 |
Imputing Dose Levels for Adverse Events |
John R. Gerlach,
Igor Kolodezh |
source |
8 |
| PharmaSUG |
2013 |
Introduction to the CDISC Standards |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2013 |
Is Your Data Set Really Validated: Beware of "Blind-Fold" Validation |
Nehan Mohan,
Gayatri Karkera |
source |
4 |
| PharmaSUG |
2013 |
JMP versus JMP Clinical for Interactive Visualization of Clinical Trials Data |
Doug Robinson,
Jordan Hiller |
source |
11 |
| PharmaSUG |
2013 |
Just Press the Button: Generation of SAS Code to Create Analysis Datasets directly from an SAP - Can it be Done? |
Endri Endri,
Rowland Hale |
source |
8 |
| PharmaSUG |
2013 |
Leveraging SDTM Standards to Cut Datasets at Any Visit |
Anthony L. Feliu,
Stephen W. Lyons |
source |
12 |
| PharmaSUG |
2013 |
Macro %D_ADSL - Automating ADSL Creation from Metadata File |
Jian Hua (Daniel) Huang |
source |
9 |
| PharmaSUG |
2013 |
Mapping Unique Aspects of Implantable Medical Device Study Data to CDISC SDTM Medical Device Domains |
Timothy L Bullock,
Sini Nair,
Ramkumar Krishnamurthy,
Todd M. Gross |
source |
12 |
| PharmaSUG |
2013 |
MedDRA - Beyond that Basic AE Report. How SMQs and MedDRA Structure can Enhance Reporting |
Pamela J. Giese |
source |
10 |
| PharmaSUG |
2013 |
Mission Possible: Your Assignment is to Validate Output for a Study |
Susan Fehrer Coulson,
Kevin R. Coulson |
source |
7 |
| PharmaSUG |
2013 |
Practice of SMQs for Adverse Events in Analysis of Safety Data and Pharmacovigilance |
Gary Chen,
David Shen |
source |
11 |
| PharmaSUG |
2013 |
Reliability Assessment of Image Data in Oncology and Psychology Studies |
Li Zhang,
David Shen,
Gary Chen |
source |
7 |
| PharmaSUG |
2013 |
SAS GTL: Improving Patients Safety and Study Efficiency |
Masaki Mihaila |
source |
11 |
| PharmaSUG |
2013 |
SAS Programmer to Clinical SAS Programmer |
Gayatri Karkera,
Nehan Mohan |
source |
7 |
| PharmaSUG |
2013 |
Some Strategies for Validating Your Data before Submission |
Frank L. Roediger,
Sandeep Juneja |
source |
8 |
| PharmaSUG |
2013 |
SQL Subqueries: Usage in Clinical Programming |
Sri Pavan Vemuri |
source |
7 |
| PharmaSUG |
2013 |
Standardizing the Standards: A Road Map for Establishing, Implementing and Unifying Standards in Your Organization |
Amy Caison,
Jhelum Naik,
Tammy Jackson |
source |
9 |
| PharmaSUG |
2013 |
The Challenges and Opportunities for SAS Statistical Programmers in Two Commonly Used CRO Resourcing Models |
Mark Matthews,
R. Mouly Satyavarapu |
source |
6 |
| PharmaSUG |
2013 |
Time to Event Analysis in the Pharmaceutical and Medical Device Industries |
Helen M. Chmiel,
Evan L. Ritzema |
source |
8 |
| PharmaSUG |
2013 |
Using the SAS Clinical Standards Toolkit 1.5 to Import CDISC ODM Files |
Lex Jansen |
source |
28 |
| PharmaSUG |
2013 |
Using Workflows and Metadata Information to Standardize Business Processes in Pharmaceutical Programming |
Peng Yang,
Wei Liu,
Julie A. Maddox |
source |
9 |
| SGF |
2013 |
A Practical Approach to Creating Define.XML by Using SDTM Specifications and Excel functions |
Amos Shu |
source
pdf |
7 |
| SGF |
2013 |
Communicating Standards: A Code Review Experience |
David A. Scocca |
source |
4 |
| SGF |
2013 |
Cox Proportional Hazard Model Evaluation in One Shot |
Polina Kukhareva |
source |
11 |
| SGF |
2013 |
Developing Your SDTM Programming Toolkit |
David A. Scocca |
source |
10 |
| SGF |
2013 |
Doctoring Your Clinical Trial with Adaptive Randomization: SAS Macros to Perform Adaptive Randomization |
Jenna Colavincenzo |
source |
9 |
| SGF |
2013 |
Easy Button: A Process for Generating Standardized Safety- and Non-Safety- Related Clinical Trial Reports |
Jiannan Hu,
Mominul Islam,
Sanjiv Ramalingam,
Xiangchen (Bob) Cui,
Yanwei Han |
source |
14 |
| SGF |
2013 |
Implementing CDISC, SDTM, and ADaM in a SAS Environment |
Pankaj Bhardwaj |
source
pdf |
4 |
| SGF |
2013 |
Running SAS Programs Using Skype |
Romain Miralles |
source |
6 |
| SGF |
2013 |
Statistical Graphics for Clinical Research Using ODS Graphics Designer |
Wei Cheng |
source |
12 |
| SGF |
2013 |
The Hash-of-Hashes as a "Russian Doll" Structure: An Example with XML Creation |
Joseph W. Hinson |
source |
21 |
| SGF |
2013 |
Using PROC GENMOD to Investigate Drug Interactions: Beta Blockers and Beta Agonists and Their Effect on Hospital Admissions |
Hui Fen Tan,
Raymond Gregory,
Ronald B. Low,
Shunsuke Ito,
Vann Dunn |
source |
10 |
| NESUG |
2012 |
A Practical Application of PROC GPLOT and PROC GCHART and Annotate to Clinical Trial Data |
Tulin Shekar |
|
7 |
| NESUG |
2012 |
A SAS Program to Construct Simultaneous Confidence Intervals of Relative Risk for Multiple Adverse Events |
Xiaoli Lu |
|
6 |
| NESUG |
2012 |
A Visual Approach to Monitoring Case Report Form Submission During Clinical Trials |
Rebecca Horney,
Karen Jones,
Annette Wiseman |
|
7 |
| NESUG |
2012 |
Applying Business Analytics to Optimize Clinical Research Operations |
David Handelsman |
|
8 |
| NESUG |
2012 |
Harnessing the Power of SAS ISO 8601 Informats, Formats, and the CALL IS8601_CONVERT Routine |
Kim M. Wilson |
|
15 |
| NESUG |
2012 |
Process Simplification - The Simple Way! X |
Minal Vyas |
|
12 |
| NESUG |
2012 |
Quality Assurance: Best Practices in Clinical SAS Programming |
Parag Shiralkar |
|
8 |
| SCSUG |
2012 |
Dirty Data? Clean it up with SAS. |
Gabriela Cantu |
source |
11 |
| PHUSE EU |
2012 |
A Long Way Down from an Output-Window to the Bottom of PDF - Some Shortcuts |
Karl-Ernst Siegler |
source
presentation source |
8 |
| PHUSE EU |
2012 |
A Peak at PK - An Introduction to Pharmacokinetics |
Hannah Twittchet,
Paul Grimsey |
source
presentation source |
9 |
| PHUSE EU |
2012 |
A Supplement to the SAS Survival Guide - Nonparametric Regression |
Karl-Ernst Siegler |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Bootstrap simulations to estimate Overall Survival based on the distribution of a historical control |
Antonio Nieto,
Javier Gómez |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Centralised Risk-Based Source Data Verification |
Shafi Chowdhury,
Mokhfur Alam Chowdhury |
source
presentation source |
4 |
| PHUSE EU |
2012 |
Changing SAS Discipline into the Life Science Sector |
Chris Gibby |
source
presentation source |
4 |
| PHUSE EU |
2012 |
Clinical Reference Library: Metadata and Standards Management in a Single Tool [presentation] |
Jonathan Peachey,
Colin Sprink |
source |
12 |
| PHUSE EU |
2012 |
Controlling Controlled Terminology |
Ryan Burns |
source
poster source |
5 |
| PHUSE EU |
2012 |
Cost Effective Standards Implementation: A New Paradigm for the Drug Development Life Cycle |
Jeff Abolafio,
Frank C. DiIorio |
source
presentation source |
9 |
| PHUSE EU |
2012 |
East6: Software for Designing, Simulating and Monitoring Group Sequential Trials |
Hrishikesh Kulkarni,
Sheetal Solanki |
source
presentation source |
12 |
| PHUSE EU |
2012 |
Enhancing Research Through Clinical Data Standardisation |
Pankaj Bhardwaj |
source
poster source |
1 |
| PHUSE EU |
2012 |
Improving Data Management with Systems Integration and Next Generation Data Flow |
Richard Davies |
source
presentation source |
4 |
| PHUSE EU |
2012 |
JMP Clinical 4.0 [presentation] |
Valérie Nedbal |
source |
45 |
| PHUSE EU |
2012 |
Legacy Data Conversion: A Journey of Discovery |
Panteleo Nacci,
Novartis Vaccines |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Master Data Management and Possible Applications for Clinical Trial Data |
Bill J. Gibson |
source
presentation source |
2 |
| PHUSE EU |
2012 |
Medical Data Review and Exploratory Data Analysis using Data Visualization |
Vinod Kerai |
source
poster source |
6 |
| PHUSE EU |
2012 |
New Approaches to Validation for SaaS-based Clinical Computing Solutions in the Cloud |
Tony Hewer |
source
presentation source |
7 |
| PHUSE EU |
2012 |
One Approach to a Metadata and Data Standards Repository |
Bill J. Gibson |
source
poster source |
4 |
| PHUSE EU |
2012 |
Optimizing Data Validation |
Andrew Newbigging |
source
presentation source |
10 |
| PHUSE EU |
2012 |
Process Simplification - The Simple Way! |
Neeraj Malhotra |
source
presentation source |
11 |
| PHUSE EU |
2012 |
Real-World Application of the Protocol Representations Model |
Joshua Pines,
Michelle Marlborough |
source
presentation source |
1 |
| PHUSE EU |
2012 |
SAS 9.3 Migration - A Project Experience |
Jules Van der Zalm,
Raymond Ebben |
source
presentation source |
12 |
| PHUSE EU |
2012 |
Spotting DILI for FDA Submission |
Nicola Tambascia,
Sven Greiner |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Superior gRaphics in Statistical Reports |
Sameer Bamnote |
source
presentation source |
8 |
| PHUSE EU |
2012 |
The 3 Year Obsession: Length of Experiences the Sole Determinant of Competence? |
Meghana Bhagwat,
Manjusha Gode |
source
presentation source |
9 |
| PHUSE EU |
2012 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Understanding SAS...the SAS-sy Way! |
Amar Nayak |
source
poster source |
8 |
| PHUSE EU |
2012 |
Using Workflows to Standardize Business Processes and Best Practices in Pharmaceutical Programming |
Mark Lambrecht,
Julie A. Maddox |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Validation in Epidemiological Studies [presentation] |
Raimund Storb |
source |
24 |
| PHUSE EU |
2012 |
What Makes Oncology Special? |
Johanna Mursic |
source
presentation source |
2 |
| SESUG |
2012 |
A SAS Macro Approach to Assign CTCAE Grades to Laboratory |
Mei Dey,
Lisa Pyle |
source |
10 |
| SESUG |
2012 |
A Visual Approach to Monitoring Case Report Form Submission During Clinical Trials |
Rebecca Horney,
Perry Point |
source |
7 |
| SESUG |
2012 |
Developing a Complete Picture of Patient Safety in Clinical Trials |
Richard C. Zink,
Russell D. Wolfinger |
source |
5 |
| SESUG |
2012 |
SAS Programming tips and techniques for Data Mapping |
Sheetal Nisal |
source |
7 |
| SESUG |
2012 |
The SDTM Programming Toolkit |
David A. Scocca |
source |
10 |
| MWSUG |
2012 |
Project Automation and Tracking Using SAS |
Rajesh Lal |
|
12 |
| WUSS |
2012 |
Assessing Interim Data Using Figures |
William Coar |
source |
6 |
| WUSS |
2012 |
Composite Indices for Health Outcomes in Epidemiologic Studies: Multi-dimensional Coding Using SAS |
Nadia Chung,
Huiyan Ma,
Jenna Voutsinas,
Leslie Bernstein,
Sophia Wang,
James Lacey |
source |
7 |
| WUSS |
2012 |
Dynamically Determine Treatment Populations and Denominators |
Ruth Johnson |
source |
10 |
| WUSS |
2012 |
Up To Speed With Categorical Data Analysis |
Maura E. Stokes |
source |
25 |
| PharmaSUG CN |
2012 |
A SAS Macro Application to Create Mock Tables in Statistical Analysis Plans for Phase I Clinical Studies |
Yao Huang |
|
7 |
| PharmaSUG CN |
2012 |
An Illustration of Rate Difference Estimation with SAS in Logistic Regression |
Yun Guo,
Victor Wu,
Xinyu Xu,
Crystal Cheng |
ppt |
7 |
| PharmaSUG CN |
2012 |
Clinical Review on iPad with DEFINE.XML |
Sy J. Truong |
|
10 |
| PharmaSUG |
2012 |
"Analysis-ready" - Considerations, Implementations, and Real World Applications |
Ellen (Zihui) Lin,
Beiying Ding |
source |
6 |
| PharmaSUG |
2012 |
A Comparison of Two Commonly Used CRO Resourcing Models for SAS/ Statistical Programmers |
R. Mouly Satyavarapu |
source |
5 |
| PharmaSUG |
2012 |
An Innovative ADaM Programming Tool for FDA Submission |
Xiangchen (Bob) Cui,
Min Chen,
Tathabbai Pakalapati |
source |
25 |
| PharmaSUG |
2012 |
Application of Meta-Analysis in Clinical Trials |
Marina Komaroff |
source |
7 |
| PharmaSUG |
2012 |
Automation of Comparing ODS RTF Outputs in Batch using VBA and SAS |
Dongsun Cao |
source |
8 |
| PharmaSUG |
2012 |
Avoiding a REL-WRECK; Using RELREC Well |
Karl Miller,
Joseph J. Hantsch,
Janet E. Stuelpner |
source |
6 |
| PharmaSUG |
2012 |
Clinical Laboratory Results, Old and New Pains |
Mario Widel,
Scott A. Bahlavooni |
source |
6 |
| PharmaSUG |
2012 |
Considerations in the Submission of Pharmacokinetics (PK) Data in an SDTM-Compliant Format |
Fred Wood,
Peter Schaefer,
Richard Lewis |
source |
8 |
| PharmaSUG |
2012 |
Could Have, Would Have, Should Have! Adopting Good Programming Standards, Not Practices, to Survive An Audit. |
Vincent J. Amoruccio |
source |
17 |
| PharmaSUG |
2012 |
Creating SAS Report Outline Using the Output Delivery System for Online Review |
Sue X. Zhang |
source |
11 |
| PharmaSUG |
2012 |
Experience of Generating an XML file and Uploading Serious and Frequent Adverse Events to ClinicalTrials.gov |
Juan Wu,
Min Lai |
source |
9 |
| PharmaSUG |
2012 |
Experiences in Leading a Company-Wide First CDISC Filing from a Programming Perspective |
Sho-Rong Lee |
source |
6 |
| PharmaSUG |
2012 |
Gilding the Lily: Boutique Programming in TAGSETS.RTF |
Rohini Rao,
Paul D. Hamilton |
source |
9 |
| PharmaSUG |
2012 |
Giving Data a Voice: Partnering with Medical Writing for Best Reporting Practices |
Katherine Troyer,
Brit Minor |
source |
8 |
| PharmaSUG |
2012 |
Harnessing the Power of SAS ISO 8601 Informats, Formats, and the CALL IS8601_CONVERT Routine |
Kim M. Wilson |
source |
15 |
| PharmaSUG |
2012 |
How to keep the project on budget in the clinical trial study |
Kevin Lee |
source |
4 |
| PharmaSUG |
2012 |
Multiple Applications of ADaM Time-to-Event Datasets |
Huei-Ling Chen,
Helen Wang |
source |
6 |
| PharmaSUG |
2012 |
One at a Time; Producing Patient Profiles and Narratives |
Joseph J. Hantsch,
Janet E. Stuelpner |
source |
6 |
| PharmaSUG |
2012 |
Pattern-Mixture Models as Linear Combinations of Least Squares Means from MMRM with Delta Method Variance Estimation |
Bohdana Ratitch,
Michael O'Kelly |
source |
15 |
| PharmaSUG |
2012 |
SAS File Design: Guidelines for Statisticians and Data Managers |
Douglas Zirbel |
source |
6 |
| PharmaSUG |
2012 |
SDTM Domain Development on the Critical Path - Strategies for Success |
David C. Izard |
source |
5 |
| PharmaSUG |
2012 |
SDTM Domain Mapping with Structured Programming Methodology |
Chengxin Li,
Jing-Wei Gao,
Nancy Bauer |
source |
8 |
| PharmaSUG |
2012 |
Sending Emails in SAS to Facilitate Clinical Trial |
Frank Fan |
source |
8 |
| PharmaSUG |
2012 |
Statistical Graphics for Clinical Research Using ODS Graphics Designer |
Wei Cheng |
source |
23 |
| PharmaSUG |
2012 |
Study on Good Programming Practices in Health and Life Sciences |
Arthur Collins,
Mark Foxwell,
Beate Hientzsch,
Cindy Q. Song |
source |
4 |
| PharmaSUG |
2012 |
The Application of SAS Perl Regular Expression in Clinical Trial Studies - Batch Processing SAS Programs |
Zhong Yan,
Kimberly Jones |
source |
7 |
| PharmaSUG |
2012 |
Transposing Tables from Long to Wide: A Novel Approach Using Hash Objects |
Joseph W. Hinson,
Changhong Shi |
source |
11 |
| PharmaSUG |
2012 |
Using PROC COMPARE to identify new and updated records in a subject listing |
Mark McLaughlin |
source |
5 |
| PharmaSUG |
2012 |
Using SAS to Calculate Noncompartmental Urine Parameters |
Vanessa Rubano,
Modesta Wiersema |
source |
8 |
| PharmaSUG |
2012 |
Using Skype to run SAS programs |
Romain Miralles |
source |
6 |
| PharmaSUG |
2012 |
Waterfall Charts in Oncology Trials - Ride the Wave |
Niraj J. Pandya |
source |
8 |
| SGF |
2012 |
Applying Business Analytics to Optimize Clinical Research Operations |
David Handelsman |
source |
8 |
| SGF |
2012 |
Automated Process for Routine Clinical and Safety Data Monitoring Reports: An Integration of EDC Database, Microsoft Outlook, and SAS |
Songtao Jiang,
Hsini T. Liao |
source |
6 |
| SGF |
2012 |
Deciphering PROC COMPARE Codes: The Use of the bAND Function |
Joseph W. Hinson,
Margaret M. Coughlin |
source |
9 |
| SGF |
2012 |
Inflated Beta Regression: Zero, One, and Everything in Between |
Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac |
source |
11 |
| SGF |
2012 |
One at a Time; Producing Patient Profiles and Narratives |
Joseph J. Hantsch,
Janet E. Stuelpner |
source |
6 |
| SGF |
2012 |
SAS and Microsoft SharePoint: Project and Resource Management Tools and Techniques for Large, Globally Distributed Programming Teams |
Stetson Line |
source |
9 |
| SGF |
2012 |
SAS Macros to Transpose SDTM Data Sets Automatically |
Chunmao Wang |
source |
7 |
| SGF |
2012 |
SAS Tools for Cost-Effective and High-Quality Clinical Trial Reporting |
Paul J. Novotny,
Angelina Tan,
Nathan R. Foster,
Jeff A. Sloan |
source |
10 |
| SGF |
2012 |
Simple Version Control of SAS Programs and SAS Data Sets |
Magnus Mengelbier |
source |
11 |
| SGF |
2012 |
Techniques for Generating Dynamic Code from SAS DICTIONARY Data |
Jingxian Zhang |
source |
7 |
| SGF |
2012 |
Using DDE and VBA Techniques to Import Data from Microsoft Word Tables in Programming Specification Files into SAS |
Mei Li,
Zemin Zeng |
source |
9 |
| SCSUG |
2011 |
A Well Designed Process and QC Tool for Integrated Summary of Safety Reports |
Huei-Ling Chen |
source |
6 |
| SESUG |
2011 |
Development of a SAS Macro for Automated Data Cleaning of Major Outcomes of Interest in Hematopoietic Cell Transplantation |
Peigang Li,
Min Chen,
Zhiwei Wang |
source |
7 |
| SESUG |
2011 |
Permutated-block randomization with varying block sizes using SAS Proc Plan |
Lei Li |
source |
6 |
| WUSS |
2011 |
Analyze This? Supporting Clinical Decisions Graphically When Not Enough Data is Available A Study Case: Challenges in NCI CTCAE Version 4 Grading |
Sheila Dayog |
source |
4 |
| WUSS |
2011 |
Clinical Data Review on iPad with DEFINE.XML |
Sy J. Truong |
source |
10 |
| WUSS |
2011 |
Consistency of Treatment Effect cross Regions |
Yunfeng Li |
source |
6 |
| WUSS |
2011 |
Hunting for Columbus' Eggs in the SAS Programming World: A Guidance to Creative Thinking for SAS Programmers |
Alice M. Cheng |
source |
12 |
| WUSS |
2011 |
Reading and Writing RTF Documents as Data: Automatic Completion of CONSORT Flow Diagrams |
Arthur L. Carpenter |
source |
7 |
| WUSS |
2011 |
SAS Program as a Backup Tool for an Adaptive Randomization System |
Yajie Wang |
source |
9 |
| WUSS |
2011 |
Sending Emails in SAS to Facilitate Clinical Trial |
Frank Fan |
source |
10 |
| WUSS |
2011 |
Statistical Graphics for Clinical Research Using ODS Graphics Designer |
Wei Cheng |
source |
23 |
| WUSS |
2011 |
Up To Speed With Categorical Data Analysis |
Maura E. Stokes |
source |
25 |
| WUSS |
2011 |
Use CDISC SDTM as a data middle-tier to streamline your SAS infrastructure |
Kalyani Chilukuri |
source |
8 |
| PHUSE EU |
2011 |
A Career in the Pharmaceutical Industry |
James McDermott |
source
presentation source |
10 |
| PHUSE EU |
2011 |
Access Control Execution Systems (ACES) |
Shailesh Kulthe,
Eric Silva |
source |
10 |
| PHUSE EU |
2011 |
Architect - A Platform for Design and Analysis Software for Clinical Trials |
Shashank Maratkar |
source |
12 |
| PHUSE EU |
2011 |
Bayesian hypothesis testing for proportions |
Antonio Nieto,
Javier Gómez |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Challengers Facing the Programmer in Observational Research |
Laurence Carpenter |
source
presentation source |
4 |
| PHUSE EU |
2011 |
ClinXPORT a software to streamline the analysis and reporting of clinical trials with SAS |
Juline Vanwinsberghe,
Francois Vandenhende |
source |
9 |
| PHUSE EU |
2011 |
Collaboration versus conflict: building successful working relationships |
Diana Stuart |
source
presentation source |
5 |
| PHUSE EU |
2011 |
Introduction of Pharmaco-economics for non-health economists |
Elhem Sbaa |
source
presentation source |
4 |
| PHUSE EU |
2011 |
JMP Clinical for the Expl oration of Legacy studies |
Robert Eric Huisden |
source
poster source |
4 |
| PHUSE EU |
2011 |
Much ADaM about Nothing - a PROC Away in a Day |
Endri Endri,
Rowland Hale |
source
presentation source |
8 |
| PHUSE EU |
2011 |
New Starter Models for Pharmaceutical companies and Clinical Research Organisations (CROs) |
Lovemore Gakava |
source
presentation source |
4 |
| PHUSE EU |
2011 |
Queries management: Interfacing SAS with in-house EDC application |
Virginie Freytag,
Michel Toussaint |
source
poster source |
5 |
| PHUSE EU |
2011 |
SAS Clinical Data Integration |
Bill J. Gibson |
source |
2 |
| PHUSE EU |
2011 |
SAS Drug Development as a platform governing data standards specification and clinical data exchange between pharmaceutical organizations |
Tina Apers |
source
presentation source |
56 |
| PHUSE EU |
2011 |
SDTM Domain QS: Challenges and Pitfalls - an Interpretation Guide to the Implementation Guide |
Knut Mueller |
source
presentation source |
6 |
| PHUSE EU |
2011 |
State of the union: what does the future hold for statistical programming in Europe [presentation] |
Leo Valmas |
source |
28 |
| PHUSE EU |
2011 |
Study Composer: a CRF design tool enabling the re-use of CDISC define.xml metadata |
Philippe Verplancke |
source
presentation source |
5 |
| PHUSE EU |
2011 |
The Nycomed outsourcing model - Data standardisation experience after three years [presentation] |
Berthold Traub |
source |
25 |
| PHUSE EU |
2011 |
Three Unique Case Studies - On the Trail of the Holy Grail of SDTM Implementation |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| PHUSE EU |
2011 |
Translating eClinical Data - The Art and Science of Data |
Nikki Dowlman |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Using R to Validate Results of Other Programming Environments |
Nikhil Abhyankar,
Vidyagouri Prayag |
source
presentation source |
8 |
| PHUSE EU |
2011 |
Using the SAS Clinical Standards Toolkit to work with the CDISC ODM model |
Lex Jansen |
source
presentation source |
20 |
| MWSUG |
2011 |
Creating a Clean Multi-Tabbed SDTM Dataset Specification Spreadsheet |
Dongju Liu,
William Conover |
|
5 |
| MWSUG |
2011 |
Driving Clinical Safety Reviews with Data Standards |
Geoffrey A. Mann |
|
7 |
| MWSUG |
2011 |
Managing Datasets at Library Level via Dynamically Constructed, DICTIONARY Tables-Driven SAS Code |
Jingxian Zhang |
|
9 |
| MWSUG |
2011 |
Objective tumor response and RECIST criteria in cancer clinical trials |
Jian Yu |
|
6 |
| MWSUG |
2011 |
Oncology Trials 101 - The Basics and Then Some |
David J. Polus |
|
4 |
| MWSUG |
2011 |
Optimizing Clinical Research Operations with Business Analytics |
David Handelsman |
|
6 |
| MWSUG |
2011 |
Pagination in Clinical Trial PROC REPORT ODS |
Chao Su,
William Conover |
|
5 |
| MWSUG |
2011 |
Summary Statistics in Rows |
John Henry King |
|
15 |
| MWSUG |
2011 |
Win With SAS, JMP, and Interest In-House Groups |
Charles E. Shipp,
Kirk Paul Lafler |
|
6 |
| NESUG |
2011 |
A Practical and Efficient Approach in Generating AE (Adverse Events) Reports Within a Clinical Study Environment |
Jiannan Hu |
|
8 |
| NESUG |
2011 |
A Utility to Validate the LoT |
Mukesh Garg,
David Etris,
Vikash Jain |
|
4 |
| NESUG |
2011 |
Authoring Quality Process Documents for Clinical Trial Programmers |
Jane E. Marrer |
|
13 |
| NESUG |
2011 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| NESUG |
2011 |
Glorified PROC CONTENTS for Secondary Source Data |
Bruce Thomas |
|
15 |
| NESUG |
2011 |
Introduction to PK/PD Data Structures and Process Optimization to Get Analysis-Ready Data |
Smitha Mullapudi |
|
4 |
| NESUG |
2011 |
Merging SAS Programming Groups: MERGE or join? |
Margaret M. Coughlin,
Alfredo Rojas |
|
6 |
| NESUG |
2011 |
PROC REPORT: Various Reporting Layouts in Clinical Study Reports and Advance Techniques |
Santosh Bari |
|
6 |
| NESUG |
2011 |
Product Repository: Oblectives and Utilization - A Case Study |
Amit Bhanose,
Smitha Mullapudi |
|
5 |
| NESUG |
2011 |
Survival Analysis: K-M Plot with Confidence Band |
Santosh Bari,
Himanshu Patel |
|
9 |
| NESUG |
2011 |
The 5 Most Important Clinical SAS Programming Validation Steps |
Brian C. Shilling |
|
6 |
| PharmaSUG |
2011 |
A Cost-Effective SDTM Conversion for NDA Electronic Submission |
Xiangchen (Bob) Cui,
Scott E. Moseley,
Min Chen |
source |
12 |
| PharmaSUG |
2011 |
A Non-Invasive Macro to Track Submission Metadata in SAS Drug Development |
Katrina E. Canonizado,
Bradford J. Danner,
Matthew J. Wiedel |
source |
8 |
| PharmaSUG |
2011 |
Automated Generation of Clinical Study Reports |
Suhas R. Sanjee,
Rajavel Ganesan,
Jason Clark |
source |
4 |
| PharmaSUG |
2011 |
Brave New World: How to Adapt to the CDISC Statistical Computing Environment |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
11 |
| PharmaSUG |
2011 |
Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner |
Patricia B. Cerrito |
source |
15 |
| PharmaSUG |
2011 |
Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains |
Janet E. Stuelpner,
Jack Shostak |
source |
12 |
| PharmaSUG |
2011 |
Cost-Effectiveness Of Primary PCI At Hospitals Without Onsite CaABG |
Pedro Ramos |
source |
21 |
| PharmaSUG |
2011 |
Creating Forest Plots Using SAS/GRAPH and the Annotate Facility |
Amanda Tweed |
source |
7 |
| PharmaSUG |
2011 |
Creating Hyperlinked PDF Graphical Patient Profiles with PROC REPORT |
William Conover |
source |
11 |
| PharmaSUG |
2011 |
Data Edit-checks Integration using ODS Tagset |
Niraj J. Pandya,
Vinodh Paida |
source |
6 |
| PharmaSUG |
2011 |
Efficiencies Realized in Building and Utilizing ADaM from SDTM |
Shirish Nalavade,
Parag Shiralkar |
source |
5 |
| PharmaSUG |
2011 |
Epidemiology in Drug Development |
Catherine Sigler,
Annette Stemhagen |
source |
3 |
| PharmaSUG |
2011 |
Evaluating Safety Signals in Clinical Trials: the Dirichlet-NBD Model Implementation with SAS |
Yuqin Li,
Xiaohai Wan |
source |
7 |
| PharmaSUG |
2011 |
Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures |
Bohdana Ratitch,
Michael O'Kelly |
source |
10 |
| PharmaSUG |
2011 |
Keeping Patients on Schedule, The Art of Visit Windows and Cycle Slotting |
Paul K. Slagle |
source |
4 |
| PharmaSUG |
2011 |
New Tips and Tricks for Creating a Harmonized, Report-Friendly SDTM and ADaM Lab Data for a Clinical Study Report |
Xiangchen (Bob) Cui,
Min Chen,
Scott E. Moseley |
source |
12 |
| PharmaSUG |
2011 |
Oncology Trials 101 - The Basics and Then Some |
David J. Polus |
source |
4 |
| PharmaSUG |
2011 |
Producing Clinical Laboratory Shift Tables From ADaM Data |
Rao Bingi |
source |
12 |
| PharmaSUG |
2011 |
Project Automation and Tracking Using SAS |
Rajesh Lal |
source |
12 |
| PharmaSUG |
2011 |
Resolving OpenCDISC Error Messages Using SAS |
Virginia Redner,
John R. Gerlach |
source |
10 |
| PharmaSUG |
2011 |
Run your reports through that last loop to standardize the presentation attributes |
Niraj J. Pandya |
source |
6 |
| PharmaSUG |
2011 |
Semi log plots - Getting the axis tick mark labels in expanded Log10 scale |
Nehan Mohan |
source |
5 |
| PharmaSUG |
2011 |
Statistical Analysis of Adverse Events in Randomized Clinical Trials Using SAS |
Dongsun Cao,
Xiaomin He |
source |
12 |
| PharmaSUG |
2011 |
The Illusion of Good Data, or How Not to Think of a Blue Elephant |
Kim Truett |
source |
6 |
| PharmaSUG |
2011 |
The Standard for the Exchange of Nonclinical Data (SEND): History and Basics |
Fred Wood,
Lou Ann Kramer |
source |
9 |
| PharmaSUG |
2011 |
Trials and Tribulations of SDTM Trial Design |
Fred Wood,
Mary Lenzen |
source |
5 |
| PharmaSUG |
2011 |
Using SAS for Modeling and Simulation in Drug Development - A Review and Assessment of Some Available Tools |
Melvin S. Munsaka,
Michael Carniello |
source |
10 |
| PharmaSUG |
2011 |
Using Visual Basic for Application to Produce Table of Contents from SAS Output List Files |
Zemin Zeng,
Mei Li,
Meng Pan |
source |
5 |
| SGF |
2011 |
A Non-Invasive Macro to Track Submission Metadata in SAS Drug Development |
Katrina E. Canonizado,
Bradford J. Danner,
Matthew J. Wiedel |
source |
8 |
| SGF |
2011 |
Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains |
Janet E. Stuelpner,
Jack Shostak |
source |
12 |
| SGF |
2011 |
Driving Clinical Safety Reviews with Data Standards |
Geoffrey A. Mann |
source |
7 |
| SGF |
2011 |
Modeling Percentage Outcomes: The %Beta_Regression Macro |
Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac |
source |
12 |
| SGF |
2011 |
Optimizing Clinical Research Operations with Business Analytics |
David Handelsman |
source |
6 |
| SGF |
2011 |
State of the Union: The Crossroads of CDISC Standards and SAS Supporting Role |
Michael J. Molter,
Chris Decker |
source |
14 |
| SGF |
2011 |
Ten Ways to Improve the Efficiency of Clinical Statistical Programming |
Amos Shu |
source |
5 |
| SGF |
2011 |
Up To Speed With Categorical Data Analysis |
Gary G. Koch,
Maura E. Stokes |
source |
25 |
| SGF |
2011 |
Using the PRELOADFMT Option with User-Defined Formats to Create Summary Tables |
Suwen Li,
Yi Hua,
Daniel Li,
Bob Lan |
source |
11 |
| SGF |
2011 |
What CDISC Means to SAS Programmers |
Kevin Lee |
source |
3 |
| NESUG |
2010 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| NESUG |
2010 |
Clinical Trials Analysis & Reporting Performance Metrics |
Ellen L. Asam,
Donna Usavage |
|
6 |
| NESUG |
2010 |
ClinicalTrials.gov: Creating an XML upload from SAS |
Daniel J. Boisvert,
Andy Illidge,
Troy A. Ruth |
|
11 |
| NESUG |
2010 |
Delivering a Simple Randomization list using RTF |
MinJung Yoon |
|
5 |
| NESUG |
2010 |
Macro for Computing Complier-Average Causal Effect of Treatment (CACE) Using Instrumental Variable Method |
Patricia R. Houck,
Sati Mazumdar,
Benoit H. Mulsant |
|
3 |
| NESUG |
2010 |
Non Printable & Special Characters: Problems and how to overcome them |
Sridhar R. Dodlapati,
Praveen Lakkaraju,
Naresh Tulluru,
Zemin Zeng |
|
13 |
| NESUG |
2010 |
The 5 Biggest Challenges of ADaM |
Terek J. Peterson,
David C. Izard |
|
11 |
| NESUG |
2010 |
The 5 Most Important Clinical SAS Programming Validation Steps |
Brian C. Shilling |
|
6 |
| NESUG |
2010 |
The Nitty-Gritty of FDA Electronic Submission: A Programmer's Perspective |
Sandeep N. Beniwal |
|
9 |
| NESUG |
2010 |
The Past, Present, and Future of Clinical Data Standards |
Chris Decker |
|
10 |
| NESUG |
2010 |
Traffic Lighting Your Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS |
Vincent DelGobbo |
|
28 |
| SCSUG |
2010 |
Creating Customized Word Tables with Table of Contents using SAS ODS RTF for Clinical Studies |
Sue X. Zhang |
source |
12 |
| SCSUG |
2010 |
Impact of model mis-specification on conditional power in interim survival analysis |
Chao L. Chen |
source |
9 |
| SCSUG |
2010 |
Win With SAS, JMP, and Interest In-House Groups |
Charles E. Shipp,
Kirk Paul Lafler |
source |
6 |
| WUSS |
2010 |
Blocked Randomization with Randomly Selected Block Sizes: A Flexible SAS Macro |
Jimmy Thomas Efird |
source |
3 |
| WUSS |
2010 |
Creating a Patient Profile using CDISC SDTM |
Marc Desgrousilliers |
source |
5 |
| WUSS |
2010 |
Managing Systems Projects with ClinAction |
Joffrey Daras |
source |
12 |
| WUSS |
2010 |
Patient Profile Reports on iPhone and iPad |
Sy J. Truong |
source |
7 |
| WUSS |
2010 |
Strategies for Building and Utilizing an Integrated Safety Database Using SAS |
Denise J. Smith |
source |
11 |
| WUSS |
2010 |
Traffic Lighting Your Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS |
Vincent DelGobbo |
source |
28 |
| PHUSE EU |
2010 |
AstraZENeca and the ART of metadata maintenance |
Paul Frost |
source
presentation source |
11 |
| PHUSE EU |
2010 |
Bridging the communication gap: implementing metadata standards in trial protocols |
Annabel Acs |
source
presentation source |
7 |
| PHUSE EU |
2010 |
CDISC integration in a clinical data management system |
Peter Van Reusel |
source
presentation source |
13 |
| PHUSE EU |
2010 |
Converting Data to CDISC Models: Research Project on Metadata Extraction, Exploration and Pooling |
Ronald Steinhau,
Dimitri Kutsenko |
source
presentation source |
4 |
| PHUSE EU |
2010 |
Defining "Compliance" for Analysis Data |
Chris Decker,
Randall Austin |
source
presentation source |
7 |
| PHUSE EU |
2010 |
Driving value through Standardization - Industry Challenges and Best Practices [presentation] |
Henry Levy |
source |
15 |
| PHUSE EU |
2010 |
From Data Capture to Decision Making Innovation through Standardization |
Michaela Jahn,
Stephan Laage-Witt |
source |
5 |
| PHUSE EU |
2010 |
Good Clinical Practices OR "Why we do What we do the Way we do it" |
Elaine Dempsey |
source
presentation source |
5 |
| PHUSE EU |
2010 |
GSTARS a complete strategy for the reporting [presentation] |
Alain Vasseur |
source |
30 |
| PHUSE EU |
2010 |
How Do I Map That? - SDTM Implementation Challenges |
Chris Price |
source
presentation source |
11 |
| PHUSE EU |
2010 |
Initial Investment in CDISC Data Standards in Clinical Organisations |
Kenneth Stolzfus |
source |
10 |
| PHUSE EU |
2010 |
Interactive Clinical Data Review for Safety Assesment and Trial Operations Management |
Michael O'Connell |
source
presentation source |
13 |
| PHUSE EU |
2010 |
iPad - Innovation or Gadget |
Niels Mathiesen |
source
presentation source |
11 |
| PHUSE EU |
2010 |
New CDISC migration strategies and tools: determining the best approach and employing automated data mapping [presentation] |
Michael Weitz,
Lauren Spiess |
source |
29 |
| PHUSE EU |
2010 |
PCKG: Managing SAS Macro Libraries |
Magnus Mengelbier |
source
presentation source |
1 |
| PHUSE EU |
2010 |
Phase III Macro-System |
Wolf-Dieter Batz |
source
presentation source |
6 |
| PHUSE EU |
2010 |
Project management (Dashboard and Metrics) with QlickView |
Stéphane Pirault |
source
presentation source |
12 |
| PHUSE EU |
2010 |
Risk Radar for the Outsourcing of Clinical Trials: The Best Guide for Success |
Randy Ramin-Wright,
Raffael Jovine |
source
presentation source |
12 |
| PHUSE EU |
2010 |
Statistical Graphics for Review and Reporting in Clinical Development |
Kerstin Pietzko,
Michael O'Connell |
source
poster source |
12 |
| PHUSE EU |
2010 |
The Innovative Medicines Initiative Knowledge Management [presentation] |
Ann Marie Martin |
source |
50 |
| PHUSE EU |
2010 |
The Use of Meta Data in Creating, Transforming and Transporting Clinical Data |
Gregory C. Steffens |
source
presentation source |
9 |
| PHUSE EU |
2010 |
Traceability between SDTM and ADaM converted analysis datasets |
Florence Somers,
Michael Knoessl |
source
presentation source |
7 |
| PHUSE EU |
2010 |
Uncover Useful Patterns in Clinical Trials Safety Data with JMP Clinical |
Valérie Nedbal |
source |
7 |
| PHUSE EU |
2010 |
Useful Tips for Analysis of Variance (ANOVA) in Multicentre, Placebo Controlled Clinical Trials |
Joanna Romaniuk |
source
presentation source |
12 |
| PHUSE EU |
2010 |
Using Data and Text Mining to drive Innovation |
David Smith |
source
presentation source |
6 |
| PHUSE EU |
2010 |
Validation Strategies for Report Objects and Programs - Challenges and Obstacles in a Risk Based World |
Christoph Ziegler,
Beate Hientzsch |
source
presentation source |
12 |
| PHUSE EU |
2010 |
Why "Context Driven Content Management" should be considered by the pharmaceutical industry |
Karsten Fogh Ho-Lanng |
source
presentation source |
6 |
| MWSUG |
2010 |
Comparing JMP and SAS for Validating Clinical Trials |
Sandra D. Schlotzhauer |
|
18 |
| MWSUG |
2010 |
Medical Guidelines: Consensus Panel Versus Healthcare Analytics |
Patricia B. Cerrito |
|
17 |
| MWSUG |
2010 |
Using SAS to Assess and Model Time-to-Event Data with Non-Proportional Hazards |
Michael G. Wilson |
|
24 |
| MWSUG |
2010 |
Win With SAS, JMP, and Interest In-House Groups |
Charles E. Shipp,
Kirk Paul Lafler |
|
6 |
| SESUG |
2010 |
Traffic Lighting Your Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS |
Vincent DelGobbo |
source |
28 |
| PharmaSUG |
2010 |
%disposition_plot: A Macro Application for Clinical Study Disposition Analysis |
Yao Huang |
|
8 |
| PharmaSUG |
2010 |
Accessing and using the metadata from the define.xml |
Lex Jansen |
|
22 |
| PharmaSUG |
2010 |
Accessing the metadata from the define.xml using XSLT transformations |
Lex Jansen |
|
70 |
| PharmaSUG |
2010 |
Analytics in the Converging Health and Life Sciences Industries: The Catalyst for the Next Generation of Healthcare |
Matt Gross |
|
15 |
| PharmaSUG |
2010 |
Assessing superiority/futility in a clinical trial: from multiplicity to simplicity with SAS |
Philip J. d'Almada,
Laura Aberle |
|
9 |
| PharmaSUG |
2010 |
Checking for SDTM Compliance: The Need for Human Involvement |
Fred Wood,
Adrienne Boyance |
|
8 |
| PharmaSUG |
2010 |
Clinical Programming For Novice |
Ramesh Ayyappath |
|
5 |
| PharmaSUG |
2010 |
ClinicalTrials.gov: Creating an XML upload from SAS |
Daniel J. Boisvert,
Andy Illidge,
Troy A. Ruth |
|
11 |
| PharmaSUG |
2010 |
Considerations for Building an Integrated Safety Database Using SAS |
Denise J. Smith,
Daniel Schulz,
Gayle Kloss,
Wei Cheng |
|
10 |
| PharmaSUG |
2010 |
Creating Customized Word Tables with Table of Contents using SAS ODS RTF for Clinical Studies |
Sue X. Zhang |
|
12 |
| PharmaSUG |
2010 |
Data Annotations in Clinical Trial Graphs |
Sudhir Singh |
|
10 |
| PharmaSUG |
2010 |
Don't run away, it's only Labs |
Lucy Wang,
Paul K. Slagle |
|
4 |
| PharmaSUG |
2010 |
Dynamic Determination of Mixed Model Covariance Structures in Double-blind Clinical Trials |
Matthew Davis |
|
7 |
| PharmaSUG |
2010 |
ECG Feature Detection Using SAS |
Suhas R. Sanjee,
Sridhar Vijendra |
|
9 |
| PharmaSUG |
2010 |
Embedded Special Characters |
Kiran K. Karidi,
Mahipal Vanam,
Sridhar R. Dodlapati |
|
5 |
| PharmaSUG |
2010 |
Evolving role of statistical SAS programmers in the pharmaceutical industry |
Venkata Sekhar Bhamidipati,
Haiping Zhou |
|
5 |
| PharmaSUG |
2010 |
From SAP to ADaM: The Nuts and Bolts |
Nancy Brucken,
Paul K. Slagle |
|
9 |
| PharmaSUG |
2010 |
Good Clinical Practices OR "Why we do What we do the Way we do it" |
Elaine Dempsey |
|
7 |
| PharmaSUG |
2010 |
Handling Non-English Clinical Trials Data in SDTM Conversions for US-FDA Submissions |
Ramanan D. Bathala |
|
5 |
| PharmaSUG |
2010 |
Help! The EX Domain is Now an Analysis Dataset! What Do I Do?!? |
David C. Izard |
|
4 |
| PharmaSUG |
2010 |
How to build ADaM from SDTM: A real case study |
Jian Hua (Daniel) Huang |
|
12 |
| PharmaSUG |
2010 |
In-Depth Review of Validation Tools to Check Compliance of CDISC SDTM-Ready Clinical Datasets |
Bhavin Busa,
Kimberly Lindfield |
|
52 |
| PharmaSUG |
2010 |
Insights into ADaM |
Matthew J. Becker |
|
9 |
| PharmaSUG |
2010 |
Linear Mixed Models in Clinical Trials using PROC MIXED |
Danyang Bing,
Xiaomin He |
|
12 |
| PharmaSUG |
2010 |
Medical Device and Diagnostic Industry 101 |
Carey G. Smoak |
|
5 |
| PharmaSUG |
2010 |
Non Printable & Special Characters: Problems and how to overcome them |
Sridhar R. Dodlapati,
Praveen Lakkaraju,
Naresh Tulluru,
Zemin Zeng |
|
13 |
| PharmaSUG |
2010 |
Online Query Management System: An Innovative SAS/IntrNet Solution for Clinical Data Management |
Romain Miralles |
|
12 |
| PharmaSUG |
2010 |
Operational Uses of Patient Profiles ... Even in an eCTD and SDTM World |
Terek J. Peterson |
|
8 |
| PharmaSUG |
2010 |
Quality in a World of "Standards" with Differences! |
Sandra VanPelt Nguyen |
|
9 |
| PharmaSUG |
2010 |
The 5 Biggest Challenges of ADaM |
Terek J. Peterson |
|
11 |
| PharmaSUG |
2010 |
The CDISC/FDA Integrated Data Pilot: A Final Summary of Findings, Reviewer Feedback, and Recommendations Implementing CDISC Standards Within and Across Studies |
Chris Decker |
|
20 |
| PharmaSUG |
2010 |
The Compliance and Implementation of Clinical Trial Outcome Disclosure on ClinicalTrials.gov |
Eric T. Sun,
Craig Anderson |
|
13 |
| PharmaSUG |
2010 |
The Manager's Skill Set: How to Move from Programmer to Manager |
Paul A. LaBrec |
|
7 |
| PharmaSUG |
2010 |
The Ubiquitous Clinical Trials Data Summary Table "Summary Statistics in Rows" |
John Henry King |
|
15 |
| PharmaSUG |
2010 |
Traffic Lighting Your Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS |
Vincent DelGobbo |
|
28 |
| PharmaSUG |
2010 |
Use Base SAS FILENAME URL to Build Surveillance and Monitoring System for New Clinical Trial Registration |
Xin Wei,
James Cai,
Jim Rosinski |
|
7 |
| PharmaSUG |
2010 |
Validate it Again?! Get SAS to do it! |
Carol Matthews,
Ginger Lewis,
Olga Belotserkovsky |
|
13 |
| SGF |
2010 |
A Macro to Create a Batch Submit SAS Program |
Helen C. Sun,
Cindy Wong |
source |
5 |
| SGF |
2010 |
Analytics in the Converging Health and Life Sciences Industries: The Catalyst for the Next Generation of Healthcare |
Matt Gross |
source |
15 |
| SGF |
2010 |
Automating SDTM File Creation: Speeding Up the Process with Metadata Files |
Daphne E. Ewing |
source |
7 |
| SGF |
2010 |
Clinical Trials Simulation: A Publicly Available, Grid-Enabled, GUI-Driven SAS System |
Peter H. Westfall,
Alex Dmitrienko,
Cynthia DeSouza,
Alin Tomoiaga |
source |
13 |
| SGF |
2010 |
Establishing Consistent Programming for Pharmaceutical Safety Summarizations Using a DOW Loop |
Bradford J. Danner,
Steven R. Kirby |
source |
8 |
| SGF |
2010 |
SAS One-liners |
Stephen Hunt |
source |
6 |
| SGF |
2010 |
The Past, Present, and Future of Clinical Data Standards |
Chris Decker |
source |
10 |
| SGF |
2010 |
Traffic Lighting Your Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS |
Vincent DelGobbo |
source
zip |
28 |
| SGF |
2010 |
Understanding the define.xml File and Converting It to a Relational Database |
Lex Jansen |
source |
20 |
| SGF |
2010 |
Win With SAS, JMP, and Interest In-House Groups |
Charles E. Shipp,
Kirk Paul Lafler |
source |
6 |
| SESUG |
2009 |
Enrollment Simulation in Clinical Trials |
Venita DePuy |
source |
4 |
| PHUSE EU |
2009 |
A Year in Pharma |
Gemma Bishop |
source |
4 |
| PHUSE EU |
2009 |
An Animated Guide: The Logical Cascade through the --ORRES Variable |
Russell M. Lavery |
source |
12 |
| PHUSE EU |
2009 |
Automation using SAS & C#.NET for CROs and Pharmaceuticals |
Giri Balasubramanina,
Gopinath Viswanathan |
source
presentation source |
13 |
| PHUSE EU |
2009 |
Building and maintaining a clinical data warehouse - challenges and opportunities for pharmaceutical programmers [presentation] |
Juergen Kuebler |
source |
15 |
| PHUSE EU |
2009 |
Clinical Database acceptance: what statistical review checks are necessary to validate a database? |
Genevieve Jehl |
source |
12 |
| PHUSE EU |
2009 |
ClinicalTrials.gov - a programmers perspective |
Ralf Minkenberg |
source
presentation source |
6 |
| PHUSE EU |
2009 |
Data review: To see or not to see.. |
Estelle Tiemtore |
source
presentation source |
6 |
| PHUSE EU |
2009 |
Generate Define.xml & Define.pdf from Metadata Environment |
Rohit Banga |
source
presentation source |
11 |
| PHUSE EU |
2009 |
Graphical Reporting of Clinical Trial Data with SAS ODS Graphics |
Hans-Rainer Pauli |
source |
47 |
| PHUSE EU |
2009 |
Health Authority questions: how to deal with the diversity |
Annabelle Millischer-Foulon |
source
presentation source |
5 |
| PHUSE EU |
2009 |
Implementation of CDISC Standards at Nycomed [presentation] |
Berthold Traub |
source |
31 |
| PHUSE EU |
2009 |
Industry Standard Good Programming Practice for Clinical Trials (using SAS) |
Mark Foxwell |
source
presentation source |
4 |
| PHUSE EU |
2009 |
Insights into ADaM |
Matthew J. Becker |
source
presentation source |
9 |
| PHUSE EU |
2009 |
Managing your metadata efficiently |
Kirsten Langendorf,
Mikkel Traun |
source |
12 |
| PHUSE EU |
2009 |
Medical Research: What should Programmers prepare for? |
Emilie Brennion |
source |
12 |
| PHUSE EU |
2009 |
Requirements, Specifications and Programming - How to ... cooperate with Statisticians in an effective way ... accelerate the production of report objects ... create technical specifications out of programs |
Christoph Ziegler |
source
presentation source |
8 |
| PHUSE EU |
2009 |
SBPOP - A Computational Tool Supporting Model Based Drug Development - Application to the Renin-Angiotensin System |
Bruno Bieth,
Henning Schmidt |
source
presentation source |
10 |
| PHUSE EU |
2009 |
Software validation in clinical trials: strategy, implementation and experiences in the MAKS project |
Jessica Wisniewski,
Daniel Wachtlin |
source |
2 |
| PHUSE EU |
2009 |
The CDISC/FDA Integrated Data Pilot: A Case Study in Implementing CDISC Standards to support an Integrated Review |
Chris Decker |
source
presentation source |
15 |
| PHUSE EU |
2009 |
The Pharmaceutical Industry is under pressure to evolve for many reasons. How does this impact on the role of the Statistician and Statistical Programmers? |
Gail Kniveton |
source |
15 |
| PHUSE EU |
2009 |
The role of the statistician in data monitoring committees |
Fritz Schindel |
source |
28 |
| PHUSE EU |
2009 |
Validate it Again?! Get SAS to do it! |
Carol Matthews,
Ginger Lewis |
source |
14 |
| NESUG |
2009 |
Developing Standard Processes and Tools to Capture Analysis Requirements for a Clinical Trial |
Jane E. Marrer |
|
8 |
| NESUG |
2009 |
LOCF: It's more than just carrying forward |
Vikash Jain,
Niraj J. Pandya |
|
10 |
| NESUG |
2009 |
Sol LeWitt and the CDISC Initiative: A Comparative Essay |
Karin LaPann |
|
10 |
| NESUG |
2009 |
Successful Lab Result Conversion for LAB Analysis Data with Minimum Effort |
Pushpa Saranadasa |
|
8 |
| NESUG |
2009 |
Using Macros to Build a Robust, Data Driven Proc GLM |
Ginger Lewis,
Frank J. Tedesco |
|
9 |
| WUSS |
2009 |
BRIDGing CDASH to SAS: How Harmonizing Clinical Trial and Healthcare Standards May Impact SAS Users |
Clinton Brownley |
source |
6 |
| WUSS |
2009 |
How a SAS/IntrNet tool was created at the FDA for the detection of potential drug-induced liver injury using data with CDISC standard |
Kate Gelperin,
Ted J. Guo,
John Senior |
source |
17 |
| WUSS |
2009 |
Reporting Quality of Cancer Care for the National Comprehensive Cancer Network - A SAS Bridge to Excel |
Joyce C. Niland,
Anna ter Veer,
Rebecca Ottesen,
Ann Vanderplas,
Julie A. Kilburn,
Dorothy Romanus |
source |
10 |
| WUSS |
2009 |
The CDISC Study Data Tabulation Model (SDTM): History, Perspective, and Basics |
Fred Wood |
source |
9 |
| PharmaSUG |
2009 |
A SAS Macro Application for Generating Patient-Level Reports in Clinical Studies |
Yao Huang |
|
4 |
| PharmaSUG |
2009 |
Adhoc Analysis of Site By Treatment Interaction |
Alan Davis |
|
9 |
| PharmaSUG |
2009 |
ARROW Clinical Data Analysis System: An Integration of Statistical Analysis and Reporting |
Cheng Jun Tian,
Denis Michel |
|
9 |
| PharmaSUG |
2009 |
Arrow Statistical Graphic System |
Cheng Jun Tian,
Qin Li,
Jiangfan Li |
|
15 |
| PharmaSUG |
2009 |
Automate the Process of Creating and Updating Titles and Footnotes of TLG for a Clinical Study Report from a Table Shell Document |
Xiangchen (Bob) Cui,
Shan Chen,
Mei Wu |
|
18 |
| PharmaSUG |
2009 |
Automating Section 14 in Clinical Study Reports |
Haibin Shu,
Bala Cynwyd |
|
3 |
| PharmaSUG |
2009 |
Biostatistics and Data Management - A match made in ... Tasmania? |
Elaine Dempsey |
|
2 |
| PharmaSUG |
2009 |
Chic FREQ and UNIVARIATE |
Jasmin Fredette |
|
14 |
| PharmaSUG |
2009 |
Clinical Trial Reporting Using SAS/GRAPH SG Procedures |
Susan L. Schwartz |
|
21 |
| PharmaSUG |
2009 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
|
6 |
| PharmaSUG |
2009 |
Converting the define.xml to a Relational Database to Enable Printing and Validation |
Lex Jansen |
|
18 |
| PharmaSUG |
2009 |
Data Capture to Trial-Specific Metadata for Analysis Data Sets: Automation Along the Way |
Sathish Sundaram,
Ganesh Munuswamy,
Mominul Islam |
|
6 |
| PharmaSUG |
2009 |
Dynamic reporting - a data driven approach |
Shan Bai |
|
4 |
| PharmaSUG |
2009 |
Empowering SAS Programmers: The Role of the Manager |
Carey G. Smoak |
|
3 |
| PharmaSUG |
2009 |
Establishing Consistent Programming for Pharmaceutical Safety Summarizations Using a DOW Loop |
Bradford J. Danner,
Steven R. Kirby |
|
8 |
| PharmaSUG |
2009 |
Fitting Compartmental Models to Multiple Dose Pharmacokinetic Data using SAS PROC NLMIXED |
Jing Su,
Peng Sun,
Xiaodong Li,
Alan H. Hartford |
|
9 |
| PharmaSUG |
2009 |
Generic System for Generating Data Listings |
Cheng Jun Tian |
|
15 |
| PharmaSUG |
2009 |
Implementation Plan for CDISC SDTM & ADaM Standards at MedImmune |
Alan Meier |
|
11 |
| PharmaSUG |
2009 |
Medical Coding System for Clinical Trials - 21 CFR Part 11 Compliant SAS/AF Application |
Annie S. Guo |
|
12 |
| PharmaSUG |
2009 |
Modeling the Treatment Effect on a Median of a Percent Change from Baseline in a Log-normal Variable Using SAS PROC NLMIXED |
Aiming Yang |
|
5 |
| PharmaSUG |
2009 |
Statistics for Clinical Trial SAS Programmers 1: paired t-test |
Kevin Lee |
|
6 |
| PharmaSUG |
2009 |
Technical Support in Biometrics |
Wei Dong |
|
4 |
| PharmaSUG |
2009 |
Understanding the define.xml and converting it to a relational database |
Lex Jansen |
|
17 |
| PharmaSUG |
2009 |
Using CDISC Lab Terminology and Determining Standard Units |
Matthew Davis |
|
7 |
| PharmaSUG |
2009 |
When Simpler is Better - Visualizing Laboratory Data Using "SG Procedures" |
Wei Cheng |
|
10 |
| PharmaSUG |
2009 |
Working with a CRO/TPO Using SDD to Implement an Adaptive Design Clinical Trial Monitored by a DMC |
Maruful Chowdhury Eli Lilly |
|
3 |
| SGF |
2009 |
%QLS SAS Macro: A SAS Macro for Analysis of Longitudinal Data Using Quasi-Least Squares |
Hanjoo Kim,
Justine Shults |
source |
12 |
| SGF |
2009 |
A Framework to Customize Frame: Building an Interactive Report Web Portal by ODS |
Xin Wei |
source |
10 |
| SGF |
2009 |
Backpacking Your Way through CDISC: A Budget-Minded Guide to Basic Concepts and Implementation |
Rachel Brown,
Jennifer K. Fulton |
source |
7 |
| SGF |
2009 |
Clinical SAS Programming: Analysis and Mitigation of Risk |
Parag Shiralkar |
source |
6 |
| SGF |
2009 |
Clinical Trial Reporting Using SAS/GRAPH SG Procedures |
Susan L. Schwartz |
source |
21 |
| SGF |
2009 |
Test Linearity between Continuous Confounder and Binary Outcome First, Run Multivariate Regression Analysis Second |
Jiming Fang,
Peter C. Austin,
Jack V. Tu |
source |
8 |
| WUSS |
2008 |
Simple and Effective Way to Validate Clinical Graphs |
Rajesh Venkkataram |
source |
10 |
| WUSS |
2008 |
When Simpler is Better - Visualizing Laboratory Data Using "SG Procedures" |
Wei Cheng |
source |
10 |
| SESUG |
2008 |
Calculating the point estimate and confidence interval of Hodges-Lehmann's median using SAS software |
Lingling Han |
source |
7 |
| PHUSE EU |
2008 |
A game of snakes and ladders |
Kerry Gordon |
source |
6 |
| PHUSE EU |
2008 |
A gentle introduction to Survival Analysis |
Martin Scottt,
Angelo Tinazzi |
source |
13 |
| PHUSE EU |
2008 |
Alias Macros, A Flexible Versioning System for Standard SAS Macros |
Jean-Michel Bodart,
Guido Wendland |
source |
7 |
| PHUSE EU |
2008 |
Automated Drug Safety Signal Detection with Guided Ana |
Eric C. Brinsfield,
David Olaleye |
source |
7 |
| PHUSE EU |
2008 |
Being a lead programme in ac CRO:Is it better or worse than in a pharma company? |
Alex Grigg |
source |
5 |
| PHUSE EU |
2008 |
Biostatistics and Data Management - A match made in ... Tasmania? |
Elaine Dempsey |
source |
2 |
| PHUSE EU |
2008 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
source |
6 |
| PHUSE EU |
2008 |
Data Standardisation, Clinical Data Warehouse and SAS Standard Programs |
Jean-Marc Ferran,
Mikkel Traun |
source |
8 |
| PHUSE EU |
2008 |
Developing a clinical reporting system collaboratively under an Open Source software license. |
Ann Marie Martin |
source |
7 |
| PHUSE EU |
2008 |
Dynamic Decimal Precision and Alignment in Clinical Trial Summary Tables and Patient Data |
Stephen Hunt,
Brian P. Fairfield-Carter |
source |
8 |
| PHUSE EU |
2008 |
Exchange of Information for the Statistical Analysis and Reporting of PK Parameter Data |
Ann Cuijpers,
Sarah Rusch |
source |
2 |
| PHUSE EU |
2008 |
Implementing CDISC at Boehringer Ingelheim |
Michael Knoessl,
Peter Leister |
source |
5 |
| PHUSE EU |
2008 |
Improving the Quality of Data |
Ester Schoeman |
source |
7 |
| PHUSE EU |
2008 |
Risk Based Approach Applied to the Validation of Report Objects |
Christoph Ziegler |
source |
8 |
| PHUSE EU |
2008 |
Statistically guided review of safety data in clinical trials |
Michael O'Connell,
Harry Southworth |
source |
12 |
| PHUSE EU |
2008 |
Statistics for Non-Statisticians |
Shambhavi Nayak |
source |
10 |
| PHUSE EU |
2008 |
SYMBOL TYPE AND COLOUR IN GRAPHS |
Diederik Pietersma |
source |
7 |
| PHUSE EU |
2008 |
The application of SDTM in a disease (oncology)-oriented organization |
Angelo Tinazzi,
Enrica Paschetto |
source |
8 |
| PHUSE EU |
2008 |
The X-Factor - Recruiting the Best |
Rachel Bowman |
source |
5 |
| PHUSE EU |
2008 |
Using SAS 9 in Clinical Research |
Gregory S. Barnes Nelson |
source |
11 |
| MWSUG |
2008 |
A Multivariate Ranking Procedure to Assess Treatment Effects |
Alan Y Chiang,
Grace Li,
Ying Ding,
Ming-Dauh Wang |
|
7 |
| MWSUG |
2008 |
Creating Macros for Survival Data in Oncology Study |
Jagannath Ghosh |
|
8 |
| MWSUG |
2008 |
Using Direct Standardization SAS Macro for a Valid Comparison in Observational Studies |
Daojun Mo,
Xia Li,
Alan Zimmermann |
|
11 |
| PNWSUG |
2008 |
Applied Aspects of Using Multiple Imputation in Clinical Data |
Christina Gullion |
|
7 |
| PNWSUG |
2008 |
Introduction to Clinical Trials in Pharmaceutical Industry - From a SAS Programmer's Point of View [presentation] |
Wenyun Ji |
|
19 |
| NESUG |
2008 |
Analysis of Correlated Recurrent and Terminal Events Data in SAS |
Li Lu,
Chenwei Liu |
|
8 |
| NESUG |
2008 |
Box Plots in SAS: UNIVARIATE, BOXPLOT, or GPLOT? |
Robert Adams |
|
11 |
| NESUG |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
|
15 |
| NESUG |
2008 |
Motivating Clinical SAS Programmers |
Daniel J. Boisvert,
Andy Illidge |
|
8 |
| NESUG |
2008 |
SAS Macro for Calculating Sample Size and Power on GLM Models with Correlated Binary Outcomes |
Qianyu Dang,
Patricia R. Houck,
Sati Mazumdar |
|
5 |
| PharmaSUG |
2008 |
%YAMGAST: Yet Another Macro to Generate a Summary Table |
Zang Xiong,
St. Jude Children's |
|
10 |
| PharmaSUG |
2008 |
Automate Compiling Clinical Appendix Tables and Listings into a Review Package with a Hyper-Linked Table of Contents |
Xiangchen (Bob) Cui,
Wei Zhang |
|
20 |
| PharmaSUG |
2008 |
Automated Drug Safety Signal Detection with Guided Analysis |
Eric C. Brinsfield,
David Olaleye |
|
5 |
| PharmaSUG |
2008 |
Automatic Creation of a Makefile for Clinical Trial |
Vikas Gaddu |
|
8 |
| PharmaSUG |
2008 |
Case Report Form Auto-Annotation in PDF Files with a Metadata Database and SAS ODS XML Tagsets in a Data Management Unit |
David M. Escobar,
Ann Fowler,
Barbara Mathewson |
|
5 |
| PharmaSUG |
2008 |
CHECKERS, We are Keeping the Table |
Joseph J. Hantsch |
|
7 |
| PharmaSUG |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
|
15 |
| PharmaSUG |
2008 |
Empowering SAS Programmers to Meet Deadlines |
Carey G. Smoak |
|
3 |
| PharmaSUG |
2008 |
EZTABLE Macros |
Daniel Huang |
|
12 |
| PharmaSUG |
2008 |
Identifying and Surfacing Data Changes for Effective Quality Management |
W. Stetson Line,
Scott A. Bahlavooni |
|
9 |
| PharmaSUG |
2008 |
Performance Evaluation of Clinical SAS Programmer |
Parag Shiralkar |
|
6 |
| PharmaSUG |
2008 |
Programming Tips and Examples for Your Toolkit, IV |
John Morrill |
|
12 |
| PharmaSUG |
2008 |
Sample Size Estimation for Trials of Recurrent Events |
Kuolung Hu |
|
8 |
| PharmaSUG |
2008 |
Sample Size Estimation Through Simulation of a Random Coefficient Model by Using SAS |
Junliang Chen,
Shannon Stock,
Chunqin Deng |
|
8 |
| PharmaSUG |
2008 |
SDTM, Plus or Minus |
Barry R. Cohen |
|
6 |
| PharmaSUG |
2008 |
Simple and Quick Methods to Verify Subjects' Scheduled Visits Compliance |
Xinping Cindy Wu |
|
6 |
| PharmaSUG |
2008 |
So Much Data, So Little Time: Splitting Datasets For More Efficient Run Times and Meeting FDA Submission Guidelines |
Anthony Harris,
Robby A. Diseker |
|
9 |
| PharmaSUG |
2008 |
The CDISC Study Data Tabulation Model (SDTM): History, Perspective, and Basics |
Fred Wood |
|
8 |
| PharmaSUG |
2008 |
The Power of PROC GPLOT in Statistical Analysis of Clinical Studies |
Aiming Yang |
|
13 |
| PharmaSUG |
2008 |
Utilizing the SAS Business Intelligence Platform in a Clinical Trial Environment |
Brian K. Varney,
Mindy Kiss |
|
5 |
| SGF |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
source |
15 |
| SGF |
2008 |
CSI: San Antonio - Common SAS Issues in Our Programs and Tips for Better Investigation of Your SAS Code |
Rachel Brown,
Jennifer K. Fulton |
source |
9 |
| SGF |
2008 |
Dynamic Decimal Precision and Alignment in Clinical Trial Laboratory Summary Tables and Patient Data Listings |
Stephen Hunt,
Brian P. Fairfield-Carter |
source |
8 |
| SGF |
2008 |
Practical Methods for Creating CDISC SDTM Data Sets from Existing Data |
Robert W. Graebner |
source |
11 |
| SGF |
2008 |
The Evolution of SAS in Life Sciences Research and Development |
David Handelsman |
source |
10 |
| NESUG |
2007 |
Common Pitfalls in SAS Statistical Analysis Macros in a Mass Production Environment |
Huei-Ling Chen,
Aiming Yang |
|
9 |
| NESUG |
2007 |
Conquering the Fear of Shift Tables |
Monal Kohli |
|
11 |
| NESUG |
2007 |
How to QC Your Own Programs |
Kevin Lee |
|
6 |
| NESUG |
2007 |
Presentation and Handling of Clinical Laboratory Data -- From Test Tube to Table |
Randall Carlson,
Nate Freimark |
|
13 |
| NESUG |
2007 |
Unleashing the Power of SPDE Under Windows |
Haibin Shu |
|
4 |
| NESUG |
2007 |
What's a "Senior" SAS Position? |
Deb Cassidy |
|
7 |
| SESUG |
2007 |
Selection Bias Adjustment: Root Canal Therapy and Self-reported Oral Health |
Mark S. Litaker,
Sandre F. McNeal,
Gregg H. Gilbert |
source |
9 |
| MWSUG |
2007 |
RANDOM and REPEATED statements - How to Use Them to Model the Covariance Structure in Proc Mixed |
Charlie Liu |
|
11 |
| MWSUG |
2007 |
Using the WHO Drug Dictionary for Reporting Clinical Trials |
Thomas E Peppard |
|
6 |
| WUSS |
2007 |
A SAS Algorithm for Block Randomization |
Jimmy Thomas Efird,
Miki Hong,
Pollie Bith-Melander,
Chieko Kimata,
Caroline Jiang,
Kathleen Baker |
source |
4 |
| WUSS |
2007 |
Clinical Data Repository and SAS |
Karthikeyan Chidambaram |
source |
8 |
| PHUSE EU |
2007 |
All roads lead to SDTM - which one shall we take? |
Ian Fisher,
Donna Thompson |
source |
9 |
| PHUSE EU |
2007 |
ARROW statistical graphical system |
Ann Cuijpers,
Raphael Noirfalise |
source |
6 |
| PHUSE EU |
2007 |
Bayesian Modelling with SPLUS and the S+flex Bayes library |
Andrew Jack,
Dawn Woodard |
source |
11 |
| PHUSE EU |
2007 |
Clinical Research Information Management... |
David Handelsman |
source |
8 |
| PHUSE EU |
2007 |
From local lab to standards and beyond |
Angelo Tinazzi,
Irene Corradino |
source |
10 |
| PHUSE EU |
2007 |
Graph automation using integrated SAS/S-PLUS solution |
Qian Wang,
Carl Herremans |
source |
7 |
| PHUSE EU |
2007 |
Integrating data transformations using DI Studio and SAS DD |
Alistair Dootson |
source |
15 |
| PHUSE EU |
2007 |
LSLV to Final CSR Tables in 24 hours - Dream or Reality? |
Stinder Fowler |
source |
10 |
| PHUSE EU |
2007 |
MAKS: A validated SAS Macro Library for data in SDTM structure |
Rolf Meinert,
Katrin Bhalla-Muller |
source |
3 |
| PHUSE EU |
2007 |
MDMAP: An application utilized in the mgmt of trial metadata |
Herve Guimard,
Eric Sorel |
source |
5 |
| PHUSE EU |
2007 |
PK data file(s) creation process |
Ann Cuijpers,
Hilde Wuyts |
source |
3 |
| PHUSE EU |
2007 |
SAS Indexes: Benefits, Limits and Applications |
Carole Beaugendre |
source |
5 |
| PHUSE EU |
2007 |
Standardizing FDA data to improve success in pediatric drug development |
Julie A. Maddox,
Chris Decker |
source |
12 |
| PHUSE EU |
2007 |
WEB-TRIAGE: Application for patient registration in ph I studies |
Angelo Tinazzi,
Lucio Ferraresi |
source |
10 |
| SCSUG |
2007 |
The Impact of Data Visualization in a Study of Chronic Disease |
Gabe Cano,
Brad Smith,
Paul Cuddihy |
|
17 |
| PharmaSUG |
2007 |
A Macro Solution for Updating Report Titles and Footnotes |
Hong Qi |
|
5 |
| PharmaSUG |
2007 |
A Review of Propensity Score Application in Healthcare Outcome and Epidemiology |
Guiping Yang |
|
24 |
| PharmaSUG |
2007 |
A Scalable Platform For Clinical Trials - Interoperability And Automation In A Web-Based Environment |
John R. Gerlach,
Maulik Shah |
|
11 |
| PharmaSUG |
2007 |
A Software Development Life Cycle Infrastructure Based upon SAS and Visual Basic |
Wayne F. Woo,
Novartis Vaccines |
|
10 |
| PharmaSUG |
2007 |
A Unified SAS Macro for Generating Randomisation Schedule |
Madan G. Kundu,
Arjun Roy |
|
12 |
| PharmaSUG |
2007 |
An Application of ODS Tagset to Produce HTML Files for Clinical Study Reports |
Li Luo |
|
10 |
| PharmaSUG |
2007 |
Automatic Creation of Analysis Datasets for Clinical Trials - A Macro Program |
John H. Adams |
|
17 |
| PharmaSUG |
2007 |
CDISC for the Medical Device and Diagnostic Industry |
Carey G. Smoak |
|
4 |
| PharmaSUG |
2007 |
Challenge the Specs |
Catherine Edwards |
|
7 |
| PharmaSUG |
2007 |
Clinical Adverse Events Data Analysis and Visualization |
Shi-Tao Yeh |
|
12 |
| PharmaSUG |
2007 |
Combining RTFs While Retaining Each Original Document's Page Numbering |
Jim Worley |
|
3 |
| PharmaSUG |
2007 |
CSI - Denver: Common SAS Issues in Our Programs and Tips for Better Investigation of Your SAS Code |
Rachel Brown |
|
9 |
| PharmaSUG |
2007 |
Designing and Building an Administrative Model for SAS Drug Development |
Margaret M. Coughlin |
|
6 |
| PharmaSUG |
2007 |
Dynamic Decimal Precision and Alignment in Clinical Trial Laboratory Summary Tables and Patient Data Listings |
Stephen Hunt,
Brian P. Fairfield-Carter |
|
8 |
| PharmaSUG |
2007 |
Evolution and Implementation of the CDISC Study Data Tabulation Model (SDTM) |
PharmaSUG Annual Meeting,
Fred Wood,
Tom Guinter |
|
47 |
| PharmaSUG |
2007 |
Evolution and Implementation of the CDISC Study Data Tabulation Model (SDTM) |
Fred Wood,
Tom Guinter |
|
7 |
| PharmaSUG |
2007 |
Implementing Worst Rank Imputation Using SAS |
Qian Wang,
Eric Qi |
|
10 |
| PharmaSUG |
2007 |
Leveraging Base SAS for Constructing a Low-Cost, Data Clarification Request Generation and Tracking System Independent of a Clinical Data Management System |
David M. Escobar,
Barbara Mathewson,
George Strang |
|
7 |
| PharmaSUG |
2007 |
Managing the CRO Relationship to Effectively Request and Receive CDISC STDM and ADaM Deliverables |
Kenneth Eng,
David C. Izard,
Terek J. Peterson |
|
8 |
| PharmaSUG |
2007 |
PROC REPORT or DATA _NULL_: Which to Use and How to Make it Easier |
David W. Carr |
|
11 |
| PharmaSUG |
2007 |
Promotion Response Analysis in the Pharmaceutical Industry - Lessons to be Learned From Clinical Trials Methodologies |
Alejandro Jaramillo |
|
12 |
| PharmaSUG |
2007 |
SAS & Clinical Data Repository |
Karthikeyan Chidambaram |
|
8 |
| PharmaSUG |
2007 |
SAS Markov Chain Monte Carlo (MCMC) Simulation in Practice |
Shi-Tao Yeh,
Scott D Patterson |
|
20 |
| PharmaSUG |
2007 |
SDTM, Plus or Minus |
Barry R. Cohen |
|
6 |
| PharmaSUG |
2007 |
Several Graph Types in Clinical Studies |
Long Zheng,
Suriani Pokta,
Pan-Yu Lai |
|
8 |
| PharmaSUG |
2007 |
Strategies and Practical Considerations for Creating CDISC SDTM Domain Data Sets from Existing CDM Data Sets |
Robert W. Graebner |
|
12 |
| PharmaSUG |
2007 |
Taking a Walk on the Wildside: Use of the PROC CDISC-SDTM 3.1 Format |
William C. Csont,
Howard M. Proskin |
|
6 |
| PharmaSUG |
2007 |
The Submission Data File System Automating the Creation of CDISC SDTM and ADaM Datasets |
Marcus Bloom,
David Edwards |
|
15 |
| PharmaSUG |
2007 |
The Use of CDISC Standards in SAS from Data Capture to Reporting |
Andrew T. Fagan |
|
21 |
| PharmaSUG |
2007 |
Using SAS 9 in Clinical Research |
Gregory S. Barnes Nelson |
|
11 |
| PharmaSUG |
2007 |
Using the SAS Information Delivery Portal in the Pharmaceutical Sector |
Raymond Ebben |
|
12 |
| SGF |
2007 |
Automatically Incorporating Repeated Changes in SAS Programming Codes in Clinical Trial Reporting |
James David Moore,
John G. Rayamajhi,
Jyoti N. Barfield |
source |
4 |
| SGF |
2007 |
Data Mining Physician Decisions for MRSA |
Hamed Zahedi |
source |
8 |
| SGF |
2007 |
Know Your AREA! Creating Professional SAS Graphics in Clinical Safety Data by Using the AREAS Option in PROC GPLOT |
Rita Tsang |
source |
15 |
| SGF |
2007 |
Navigating a Major Regulatory Submission Project to Success |
Alan Meier |
source |
6 |
| SGF |
2007 |
Perl Regular Expressions 102 |
Kenneth W. Borowiak |
source |
11 |
| SGF |
2007 |
Regression Splines with Longitudinal DATA |
Chan-Hee Gossett,
Jeff M. Simpson,
Pippa M. Jo |
source |
6 |
| SGF |
2007 |
Saving Trees with Output Delivery System (ODS) |
Angelina D. Diehl,
Nancy Mandrekar,
Jayawant N. Tan |
source |
9 |
| SGF |
2007 |
Using SAS PROC NLMIXED for Robust Regression |
Steven A. Chen,
Lingyun Gilbert |
source |
9 |
| SGF |
2007 |
Using SAS to Determine Sample Sizes for Traditional Two-Stage and Adaptive Two-Stage Phase II Cancer Clinical Trial Designs |
St. Clare Groulx,
Adrienne Moon,
Kyung-hee Chung |
source |
9 |
| SGF |
2007 |
What's a "Senior" SAS Position? |
Deb Cassidy |
source |
7 |
| MWSUG |
2006 |
Nonparametric Inference for Ordered Alternatives in a One-Way Layout Using |
Paul Juneau |
|
15 |
| PHUSE EU |
2006 |
(Sample) Size DOES Matter |
John Salter |
source |
10 |
| PHUSE EU |
2006 |
Basic Statistics and Commonly Encountered Statistical Tests for Statistical Programmers |
Maria Efstathiou |
source |
12 |
| PHUSE EU |
2006 |
Contours of a Drug Development Data Warehouse |
Paul Vervuren |
source |
8 |
| PHUSE EU |
2006 |
Global Resource Estimation |
Roy Ward |
source |
12 |
| PHUSE EU |
2006 |
Integrating Specialized Graphics and Analysis into Production Systems |
Joel M. Hoffman,
Michael O'Connell |
source |
18 |
| PHUSE EU |
2006 |
Metrics Unleashed: Measuring Productivity or Inspiring Artisans |
Neil Howard,
Gregory S. Barnes Nelson |
source |
10 |
| PHUSE EU |
2006 |
Mimicking NOSEPS in ODS RTF output created with Proc Report and Proc Tabulate |
Twan van Berkel,
Gertjan van Maaren |
source |
12 |
| PHUSE EU |
2006 |
Much more than TFLs - the evolving role of the Biometrician |
Chris Simmons |
source |
6 |
| PHUSE EU |
2006 |
Partial Dates; decisions and implications of handling partially missing dates |
Rachel Bowman |
source |
6 |
| PHUSE EU |
2006 |
Save Time: Program Your Output Specs |
Hansjörg Frenzel,
James Witt |
source |
11 |
| PHUSE EU |
2006 |
Self-validating data |
Christof Binder |
source |
7 |
| PHUSE EU |
2006 |
Some Basic Statistics for Non-Statisticians |
Gary S. Stevens |
source |
6 |
| PHUSE EU |
2006 |
Statistical Graphics and Reporting in Drug Development |
Michael O'Connell,
Sven Knudsen |
source |
13 |
| PHUSE EU |
2006 |
The Power of RETAIN Statement in Clinical Trial Programming by Examples |
Baoxian Lan |
source |
5 |
| PHUSE EU |
2006 |
The Use of CDISC Standards in SAS from Data Capture to Reporting |
Andrew T. Fagan |
source |
21 |
| PHUSE EU |
2006 |
Using CDISC Models for the Analysis of Safety Data |
Susan J. Kenny,
Edward D. Helton |
source |
10 |
| PHUSE EU |
2006 |
Using the SAS Information Delivery Portal in the Pharmaceutical Sector |
Raymond Ebben |
source |
12 |
| SESUG |
2006 |
A Relational Understanding of SDTM Tables |
John R. Gerlach |
source |
10 |
| WUSS |
2006 |
An Approach Finding the Right Tolerance Level for Clinical Data Acceptance |
Karen Walker |
source |
5 |
| WUSS |
2006 |
Changing Careers to Become a SAS Programmer in the Biotech/Pharmaceutical Industry |
Sy J. Truong |
source |
9 |
| WUSS |
2006 |
Have It Both Ways: Macros that Produce Publication-Quality Tables and Stand-alone Code |
Linda Collins,
Lisa Kaye Brooks,
Michael Rea,
Alan Hopkins |
source |
19 |
| NESUG |
2006 |
Designing and Building an Administrative Model for the SAS Drug Development Tool |
Meg Coughlin |
|
6 |
| NESUG |
2006 |
It's About Time! A Primer on Time-Slotting of Data Using SAS |
Maria Y. Reiss |
|
13 |
| NESUG |
2006 |
Know Your AREA! Creating Professional SAS Graphics in Clinical Safety Data, Using the AREAS Option in PROC GPLOT |
Rita Tsang |
|
21 |
| NESUG |
2006 |
Perl Regular Expressions 102 |
Kenneth W. Borowiak |
|
11 |
| NESUG |
2006 |
Using SAS Data Integration Studio to Convert Clinical Trials Data to the CDISC SDTM Standard |
Barry R. Cohen |
|
8 |
| PharmaSUG |
2006 |
%SummaryTable: A SAS Macro to Produce a Summary Table in Clinical Trial |
Yinmei Zhou,
St. Jude Children's |
|
7 |
| PharmaSUG |
2006 |
A Case of Online Data Processing and Statistical Analysis via SAS/IntrNet |
Sijian Zhang |
|
8 |
| PharmaSUG |
2006 |
A Comparison Between SQL and Data Step and Some SAS Procedures |
LaTonya Murphy |
|
6 |
| PharmaSUG |
2006 |
CFB: A Programming Pattern for Creating "Change from Baseline" Datasets |
Lei Zhang |
|
12 |
| PharmaSUG |
2006 |
De-Identification of Clinical Trials Data Demystified |
Jack Shostak |
|
12 |
| PharmaSUG |
2006 |
Estimate Carryover Effect in Clinical Trial Crossover Designs |
David Shen,
Zaizai Lu |
|
7 |
| PharmaSUG |
2006 |
Evolution and Implementation of the CDISC Study Data Tabulation Model (SDTM) |
Tom Guinter,
Fred Wood |
|
6 |
| PharmaSUG |
2006 |
Good Programming Practices in Clinical Trial - a Check Program |
John H. Adams |
|
12 |
| PharmaSUG |
2006 |
Longitudinal Graphs with Annotate |
Jasmin Fredette |
|
11 |
| PharmaSUG |
2006 |
Managing Clinical Trials Data using SAS Software |
Martin J. Rosenberg |
|
7 |
| PharmaSUG |
2006 |
MDMAP - An innovative application utilized in the management of clinical trial metadata |
Gregory Ridge,
Neeru Bhardwaj |
|
9 |
| PharmaSUG |
2006 |
Murphy was an optimist: a realistic approach to clinical trial data |
Pamela L. Reading |
|
4 |
| PharmaSUG |
2006 |
Preparing CTD (Common Technical Document) for FDA Submission |
Charlie Xu |
|
7 |
| PharmaSUG |
2006 |
Randomization in Clinical Trial Studies |
David Shen,
Zaizai Lu |
|
8 |
| PharmaSUG |
2006 |
Sample Size Calculation and Timeline Estimate for Progression-Free Survival |
Chung-Kuei Chang |
|
10 |
| PharmaSUG |
2006 |
SAS & Safety Signal Detection and Analysis |
Karthikeyan Chidambaram,
Sunandan Banerjee |
|
8 |
| PharmaSUG |
2006 |
SAS Drug Development: Bringing Innovation to Life Sciences |
David Handelsman |
|
12 |
| PharmaSUG |
2006 |
Streamlining Specimen/Label Shipment Process |
Christina Carty,
Elizabeth R. Spence |
|
7 |
| PharmaSUG |
2006 |
Systematic Inductive Method for Imputing Partial Missing Dates in Clinical Trials |
Ping Liu |
|
8 |
| PharmaSUG |
2006 |
Transforming Business Requirements into System Solutions |
Yongcun Zhang |
|
10 |
| PharmaSUG |
2006 |
Using SAS ETL Studio to Convert Clinical Trials Data to the CDISC SDTM |
Barry R. Cohen |
|
10 |
| SUGI |
2006 |
A System of SAS Macros for Producing Statistical Reports |
Greg A. Grandits |
source |
7 |
| SUGI |
2006 |
Assessing Within- and Between-Individual Effects Using Correlated Data from an HIV Clinical Trial |
Marla J. Husnik,
Grant Colfax,
Eugene Huang |
source |
10 |
| SUGI |
2006 |
Developing, Managing, and Evaluating a Standard Macro System |
Albert Mo |
source |
10 |
| SUGI |
2006 |
Duration Calculation from a Clinical Programmer's Perspective |
Alice M. Cheng |
source |
10 |
| SUGI |
2006 |
Finding a Duplicate in a Haystack |
Brett J. Peterson |
source |
10 |
| SUGI |
2006 |
Moving from Programmer to Statistician - A Statistical Mentoring Program |
Emily Anne James |
source |
3 |
| SUGI |
2006 |
Save Those Eyes: A Quality-Control Utility for Checking RTF Output Immediately and Accurately |
Michael Hagendoorn,
Jonathan M. Squire,
Johnny Tai |
source |
10 |
| SUGI |
2006 |
Using the SAS System for Experimental Designs for Multi-Component Interventions in Medicine |
Heather G. Allore,
Peter Peduzzi,
Ling Han,
Mary Tinetti |
source |
7 |
| SUGI |
2006 |
Version Control on the Cheap. A User-Friendly, Cost-Effective Revision Control System for SAS |
Tim P. Williams |
source |
10 |
| PHUSE EU |
2005 |
An Introduction to CDISC - Available CDISC Standards and Models and How SAS Supports These |
Laurie Rose |
source |
43 |
| PHUSE EU |
2005 |
An Introduction to CDISC - CDISC Collaborations and Standards in Progress |
Becky Kush |
source |
46 |
| PHUSE EU |
2005 |
An Introduction to CDISC - What is CDISC and Why Standards? |
Laurie Rose,
Becky Kush |
source |
41 |
| PHUSE EU |
2005 |
Data Mining in a Pharmaceutical Environment |
Franky De Cooman |
source |
4 |
| PHUSE EU |
2005 |
Designing a Global SAS9 Architecture for Clinical Trials Analysis and Reporting |
Gregory S. Barnes Nelson,
Michael Walega |
source |
12 |
| PHUSE EU |
2005 |
How can you make the entire clinical trial process easy and fun for the users and also reduce your costs? |
Carl-Olow Magnusson,
Ann-Sofie Bergstrom |
source |
1 |
| PHUSE EU |
2005 |
Kisses, Nakedness and Love Or What makes a good clinical trials programmer ? |
Josephine Duvoid |
source |
5 |
| PHUSE EU |
2005 |
Macro MDU: a flowchart of used programs, datasets and TLF's based upon the Final Run |
Herman Ament |
source |
10 |
| PHUSE EU |
2005 |
Managing Clinical Trials Data using SAS |
Martin J. Rosenberg |
source |
7 |
| PHUSE EU |
2005 |
Mapping Corporate Data Standards to the CDISC Model |
David Parker |
source |
7 |
| PHUSE EU |
2005 |
ODM & define.xml |
David Iberson-Hurst |
source |
58 |
| PHUSE EU |
2005 |
Only Interactive Graphics Will Do |
Nelson Kinnersley |
source |
4 |
| PHUSE EU |
2005 |
SAS Dataset Content Conversion to CDISC Data Standards |
Anthony L. Friebel |
source |
9 |
| PHUSE EU |
2005 |
Software Tools for working with CDISC ODM, SDTM, LAB and define.xml |
Jozef Aerts |
source |
2 |
| PHUSE EU |
2005 |
Technical application of SAS ETL Studio in the clinical reporting process |
David Smith |
source |
8 |
| PHUSE EU |
2005 |
The European System for Monitoring Drug Safety, EudraVigilance |
Hans-Georg Wagner,
Olivier Simoen |
source |
13 |
| PHUSE EU |
2005 |
The Future of CDISC |
Becky Kush |
source |
50 |
| PHUSE EU |
2005 |
Understanding the Japanese culture and approval process |
Richard Harvey |
source |
10 |
| PHUSE EU |
2005 |
Visions of a Drug Development Data Warehouse |
Paul Vervuren |
source |
7 |
| MWSUG |
2005 |
SAS Enterprise Guide in Pharmaceutical Applications: Automated Analysis And Reporting |
Alex Dmitrienko |
|
9 |
| WUSS |
2005 |
A Macro Mapping Date and Time Variable to CDISC Date and Time Variable |
Song Liu,
Brett Sellars |
source |
5 |
| WUSS |
2005 |
A Programmer's Guide to Statistical Procedures |
Jim Edgington |
source |
4 |
| WUSS |
2005 |
Duration Calculation from a Clinical Programmer's Perspective |
Alice M. Cheng |
source |
9 |
| WUSS |
2005 |
How to Get Promoted: Planning for Career Growth |
Sandra Minjoe |
source |
8 |
| WUSS |
2005 |
Transforming Data for CDISC and ISS |
Sy J. Truong |
source |
11 |
| NESUG |
2005 |
MDMAP - An innovative application utilized in the management of clinical trial metadata |
Gregory Ridge,
Neeru Bhardwaj |
|
9 |
| NESUG |
2005 |
Taking Almost Raw Lab Data and Turning it into Data Fit to be Analyzed |
Jeff Magouirk |
|
7 |
| NESUG |
2005 |
Using DS2TREE Macro to Create Interactive Treeview Diagrams for Clinical Adverse Experiences Records |
Shi-Tao Yeh |
|
17 |
| NESUG |
2005 |
Using GRADAR Procedure to Display Clinical Data |
Shi-Tao Yeh |
|
13 |
| PharmaSUG |
2005 |
%KMPlot - An Enhancement of SAS PROC LIFETEST |
Weifeng Xu,
William W.B. Wang |
|
8 |
| PharmaSUG |
2005 |
A Dynamic SAS/IntrNet Example with Help of ASP and JavaScript: Online Clinical Trial Randomization List Generator |
Sijian Zhang,
Mark Carpenter,
Michael Windle |
|
6 |
| PharmaSUG |
2005 |
A SAS Application for Analyzing Quality of Life data: NCIC-CTG Standard Method |
Don (Dongguang) Li |
|
5 |
| PharmaSUG |
2005 |
A Simple Solution for Managing the Validation of SAS Programs That Support Regulatory Submissions |
Tony Chang,
Dana Soloff |
|
6 |
| PharmaSUG |
2005 |
An Approach Finding the Right Tolerance Level for Clinical Data Acceptance |
Karen Walker |
|
6 |
| PharmaSUG |
2005 |
Analyzing and Displaying Study Data in Clinical Trials Made Easy |
Denise J. Smith |
|
15 |
| PharmaSUG |
2005 |
Assigning Treatment Group in Cross-over Studies: A Practical Approach |
Charles Ling,
Shulin Yuan |
|
3 |
| PharmaSUG |
2005 |
Calculating Posterior Probability of the Maximum Contrast Using PROC IML |
Akira Wakana,
Isao Yoshimura,
Chikuma Hamada |
|
6 |
| PharmaSUG |
2005 |
Comparison of Techniques for XML and RTF Tables |
Linda Collins |
|
15 |
| PharmaSUG |
2005 |
Constructing Stack Tables With Proc Report and ODS RTF |
Lei Zhang |
|
11 |
| PharmaSUG |
2005 |
Developing Varargs Macros For Integrated Clinical Study Analysis and Reporting |
Lei Zhang,
George Li |
|
10 |
| PharmaSUG |
2005 |
Extending the SAS Environment with Trellis Graphics |
Chris Thornton |
|
7 |
| PharmaSUG |
2005 |
Implementation of the CDISC SDTM at the Duke Clinical Research Institute |
Jack Shostak |
|
12 |
| PharmaSUG |
2005 |
Independent Data Reviews |
Ananth Kumar |
|
3 |
| PharmaSUG |
2005 |
Lab Unit Conversions: Taking Advantage of "Expert" External Resources |
Sandra Minjoe |
|
7 |
| PharmaSUG |
2005 |
Pharmaceutical Programming: From CRFs to Tables, Listings and Graphs, a process overview with real world examples |
Mark Penniston |
|
8 |
| PharmaSUG |
2005 |
Power Analysis and Sample Size Estimation using Bootstrap |
Xiaomei Peng,
Guangbin Peng,
Celedon Gonzales |
|
7 |
| PharmaSUG |
2005 |
Prepare Data Listings with SAS Software for Database Audit |
Jay Zhou,
Larry Shen |
|
8 |
| PharmaSUG |
2005 |
Programming and Data Differences Between Clinical Trials and Observational Studies |
Margaret M. Coughlin |
|
6 |
| PharmaSUG |
2005 |
Risk-Based Approach to SAS Program Validation |
Keith C. Benze |
|
7 |
| PharmaSUG |
2005 |
SAS Dataset Content Conversion to CDISC Data Standards |
Anthony L. Friebel,
Thomas Cox,
Edward D. Helton |
|
10 |
| PharmaSUG |
2005 |
Smoothing Techniques for Pharmacokinetic and Pharmacodynamic Profiles |
Naum M. Khutoryansky |
|
5 |
| PharmaSUG |
2005 |
Statistical Table Specifications and Automatic Code Generation using XML |
Alan Hopkins,
Linda Collins |
|
7 |
| PharmaSUG |
2005 |
Strategies for Implementing SDTM and ADaM Standards |
Susan J. Kenny,
Michael A. Litzsinger |
|
8 |
| PharmaSUG |
2005 |
The Role of Analysis Datasets in Successful FDA Advisory Meetings |
Sandy Chang |
|
9 |
| PharmaSUG |
2005 |
To Macro or Not To Macro? |
Amy Gillespie,
Blue Bell |
|
8 |
| PharmaSUG |
2005 |
Using V9 ODS LAYOUT to Simplify Generation of Individual Case Summaries |
Ling Y. Chen |
|
8 |
| PharmaSUG |
2005 |
Utility Macros Used in the Process for Database Translations |
Yuguang Zhao,
Jingchun Yu |
|
3 |
| PharmaSUG |
2005 |
Validating Data Using SAS Formats as a Programming Tool |
John R. Gerlach |
|
11 |
| PharmaSUG |
2005 |
XML Basics for SAS Programmers |
Yong Li |
|
5 |
| SUGI |
2005 |
A Macro for Importing Multiple Excel Worksheets into SAS Data Sets |
Helen C. Sun,
Cindy Wong |
source |
9 |
| SUGI |
2005 |
An Easy-to-Use SAS Table Formatting Macro: Stand-Alone, Flexible, and Quick |
Zbigniew A. Kadziola |
source |
8 |
| SUGI |
2005 |
Analyzing Incomplete Binary Repeated Measures Data Using SAS |
Bin Yang |
source |
8 |
| SUGI |
2005 |
Automation of Clinical Trial Laboratory Data Acquisition Using SAS and DDE |
Balakrishna Dandamudi |
source |
12 |
| SUGI |
2005 |
Designing a Global SAS9 Architecture for Clinical Trials Analysis and Reporting |
Gregory S. Barnes Nelson,
Michael Walega |
source |
12 |
| SUGI |
2005 |
Empirical Power for Higher-Order Crossover Designs in Comparative Bioavailability Clinical Trials |
Jihao Zhou,
Bruce Coate |
source |
10 |
| SUGI |
2005 |
Standardization through Macros: The Possibilities of Using Indirect Referencing to Macro Variables |
Britta Kelsey |
source |
8 |
| NESUG |
2004 |
Clinical Trial Data Validation: Using PROC SQL Effectively |
Balakrishna Dandamudi |
|
20 |
| NESUG |
2004 |
Clinical Trials Online - Running SAS on the Web Without SAS/IntrNet |
Quan Ren |
|
15 |
| NESUG |
2004 |
Minimization: Testing a Dynamic Randomizaton Algorithm |
Donna E. Levy,
Emily Blood |
|
15 |
| SESUG |
2004 |
A Text Miner Analysis to Compare Internet and Medline Information about Allergy Medications |
Chakib Battioui |
source |
6 |
| SESUG |
2004 |
Spatial Statistics Using the SAS Bridge for ESRI |
Patricia B. Cerrito,
Carol Hanchette,
William Dakan,
George R. Barnes,
Robert Forbes |
source |
15 |
| SESUG |
2004 |
Using PROC COMPARE in a SAS/AF Application for Tracking Corrections made to SAS Datasets for a Clinical Trial |
Emily A. Mixon |
source |
6 |
| WUSS |
2004 |
Constructing Analysis Files: A Multi-Tiered Approach |
Tyler Cole |
source |
7 |
| WUSS |
2004 |
Reading and Writing XML Files from SAS |
Miriam Cisternas,
Ricardo A. Cisternas |
source |
18 |
| WUSS |
2004 |
SAS/AF: A Hands-On Introductory Workshop |
Deborah A. Testa |
source |
11 |
| WUSS |
2004 |
Using SAS IOM With A Java Client Application |
Valerie Williams,
Brian Chan |
source |
12 |
| MWSUG |
2004 |
A System of SAS Macros for Producing Statistical Reports |
Greg A. Grandits,
Ken Svendsen |
|
8 |
| MWSUG |
2004 |
Calculation and Assessment of Inferential Test Statistics for Meta Analysis of Cross-Over Clinical Trials |
Hurley |
|
8 |
| MWSUG |
2004 |
Using SAS Enterprise Guide to Automate and Customize Statistical Analyses for Pharmaceutical Data |
Alex Dmitrienko,
Cindy Lee |
|
6 |
| PNWSUG |
2004 |
Reading and Writing XML Files from SAS |
Peter J. Lund |
|
|
| PharmaSUG |
2004 |
%Cox_PH - An enhancement of SAS PROC PHREG |
Hong (Lily) Zhang,
Robin Mogg |
|
8 |
| PharmaSUG |
2004 |
An FDA-Requested XML Replacement for SAS Version 5 Transport Files in U.S. Regulatory Submissions |
Michael C. Palmer |
|
5 |
| PharmaSUG |
2004 |
Apply Response Surface Analysis for Interaction of Dose Response Combine Treatment Drug Study |
Tung-Yi (Tony) Wu |
|
8 |
| PharmaSUG |
2004 |
Automating the Documentation of Oracle Clinical Database Specifications |
Kyle McBride |
|
9 |
| PharmaSUG |
2004 |
Automation of Patient Narratives Using SAS and Analysis Datasets |
David C. Izard |
|
6 |
| PharmaSUG |
2004 |
CDX - clinical data management and report programming environment |
Gunilla Sköllermo,
Pål Edman |
|
7 |
| PharmaSUG |
2004 |
Clinical Trial Randomization Design: Blocked Randomized Response Adaptive Method |
K.Y. Trudy Poon |
|
4 |
| PharmaSUG |
2004 |
Clinical Trials Terminology for SAS Programmers |
Sy J. Truong |
|
6 |
| PharmaSUG |
2004 |
COMPAREXLS - A Powerful Comparison Tool for Spreadsheet Difference Resolution |
Difference Resolution |
|
11 |
| PharmaSUG |
2004 |
Constructing Analysis Files: A Multi-Tiered Approach |
Tyler Cole |
|
7 |
| PharmaSUG |
2004 |
Defining and Validating CDISC Data Standards to XML in SAS Technology |
Anthony L. Friebel |
|
6 |
| PharmaSUG |
2004 |
Generating N Shell Programs for N Reports in a Clinical Trial |
John R. Gerlach |
|
8 |
| PharmaSUG |
2004 |
Incremental Methods of Imputation for Longitudinal Data with Informative Missingness |
Naum M. Khutoryansky |
|
4 |
| PharmaSUG |
2004 |
Mergers, Consolidations and Proc Compare |
Fang Dong |
|
8 |
| PharmaSUG |
2004 |
MULTILABEL - A useful addition to the FORMAT procedure |
Venky Chakravarthy |
|
9 |
| PharmaSUG |
2004 |
Processing Large Lists of Parameters and Variables With Macro Techniques |
Eugene Tsykalov |
|
6 |
| PharmaSUG |
2004 |
Producing Data-Driven Plots for Microsoft Word Using SAS/GRAPH and the SAS Macro Language |
Robert W. Graebner |
|
7 |
| PharmaSUG |
2004 |
Reading and Writing XML Files from SAS |
Miriam G. Cisternas |
|
18 |
| PharmaSUG |
2004 |
SAS and Microsoft Excel for Tracking and Managing Clinical Trial Data: Methods and Applications for Information Delivery |
Na Li |
|
11 |
| PharmaSUG |
2004 |
SAS Application in 2x2 Crossover Clinical Trial |
Wuwei Wayne Feng |
|
10 |
| PharmaSUG |
2004 |
The Meta-Analysis (PROC MIXED) of Two Pilot Clinical Studies with a Novel Antidepressant |
Lev Sverdlov,
Park Ridge |
|
6 |
| PharmaSUG |
2004 |
Tools to Facilitate the Creation of Pooled Clinical Trials Databases |
Patricia Majcher |
|
8 |
| PharmaSUG |
2004 |
Use Regression Algorithm Identifying Repeated Use Patients |
Haibin Shu,
Bala Cynwyd |
|
4 |
| PharmaSUG |
2004 |
Why SAS is the Best Place to Put Your Clinical Data |
Steven A. Wilson |
|
12 |
| SUGI |
2004 |
A Lightweight HTML Codebook Generator for Clinical Trial Data |
Lei Zhang |
source |
11 |
| SUGI |
2004 |
A SAS Macro for Generating Randomization Lists in Clinical Trials Using Permuted Blocks Randomization |
Mazen Abdellatif |
source |
12 |
| SUGI |
2004 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
source |
16 |
| SUGI |
2004 |
Data Management in Analyzing Clinic Trial Data - Metadata Application |
Julia Z. Zhang,
David C. Chen |
source |
6 |
| SUGI |
2004 |
Reading and Writing XML Files from SAS |
Miriam G. Cisternas,
Ricardo A. Cisternas |
source |
19 |
| SUGI |
2004 |
Sample-Size Analysis in Study Planning: Concepts and Issues, with Examples Using PROCs POWER and GLMPOWER |
Ralph G. O'Brien,
John M. Castelloe |
source |
12 |
| SUGI |
2004 |
Some Statistical Strategies for Analyzing Confirmatory Studies Involving One or More Occurrences of Primary Events |
Gary G. Koch,
Maura E. Stokes |
source |
21 |
| SUGI |
2004 |
Two Approaches to the Summarization of Data |
Huijuan Xu,
John Hotaling |
source |
5 |
| SUGI |
2004 |
Why SAS is the Best Place to Put Your Clinical Data |
Steven A. Wilson |
source |
13 |
| WUSS |
2003 |
A Macro To Display The Kaplan-Meier Curve With An Annotated Failure Table |
Kristie Kooken,
Colin Kuang |
source |
5 |
| WUSS |
2003 |
Clinical Trial Randomization Design: Blocked Randomized Response Adaptive Method |
K.Y. Trudy Poon,
Che-Chin Lie |
source |
4 |
| WUSS |
2003 |
MedDRA Made Easy with SAS/IntrNet |
Sy J. Truong |
source |
9 |
| WUSS |
2003 |
Reading and Writing XML Files from SAS |
Miriam Cisternas,
Ricardo A. Cisternas |
source |
7 |
| WUSS |
2003 |
Two Approaches to Presenting Hierarchical Clinical Trials Data through SAS/IntrNet Using SAS/GRAPH DSGI and SAS Treeview Applet |
Nick Pászty |
source |
6 |
| WUSS |
2003 |
Why SAS is the Best Place to Put Your Clinical Data |
Steven A. Wilson |
source |
10 |
| SESUG |
2003 |
A SAS Macro to Design Phase II Clinical Trials |
Alan B. Cantor,
Moffitt Cancer |
source |
2 |
| SESUG |
2003 |
Data Acquisition Portal (DAP) Web: Web Based Data Collection Application |
Christina Carty,
Elizabeth R. Spence,
Norman Oals,
Linda Linzy,
Reuben Richards |
source |
4 |
| NESUG |
2003 |
"ACROSS" in PROC REPORT |
Jiang Jin |
|
2 |
| NESUG |
2003 |
Date/Time Stamped Files and Audit Trails: What Part 11 Compliant SAS Systems are Made Of |
Carolyn Dougherty |
|
11 |
| NESUG |
2003 |
Practical SAS Methods to Safeguard the SAS Clinical Trial Data |
Tianshu Li |
|
4 |
| NESUG |
2003 |
Run All Your SAS Programs in One Program: Automatically |
Ling Y. Chen,
Steven Gilbert |
|
4 |
| SEUGI |
2003 |
Drug Approval, making the best treatments available safely, but quickly - using SAS at the heart of generic reporting systems. [presentation] |
Jonathan Chainey,
Rob Horton |
source |
25 |
| VIEWS |
2003 |
Analysing Binary Outcome Data from a Crossover Design Study using the SAS System |
Anna Pictor |
presentation |
8 |
| PharmaSUG |
2003 |
A SAS Macro for Producing Clinical Laboratory Shift Table |
Shi-Tao Yeh,
Glaxo Smith Kline |
|
6 |
| PharmaSUG |
2003 |
A SAS Macro to Automate The Covariance Structure Determination in Repeated Measures Data Analysis with Mixed Procedure |
Don (Dongguang) Li |
|
4 |
| PharmaSUG |
2003 |
An Application of Dummy Variable and Placeholder Macro Parameter in Programming for Clinical Trial Data Quality Monitoring |
Sijian Zhang,
Mark Carpenter |
|
4 |
| PharmaSUG |
2003 |
Application of Some Advanced PROC SQL Features in Clinical Trial Programming |
Changhong Shi |
|
6 |
| PharmaSUG |
2003 |
Automating the Creation of Data Definition Tables (Define.pdf) Using SAS Version 8.2 |
Eugene Yeh |
|
8 |
| PharmaSUG |
2003 |
CDISC, ADaM, and TTE: What Are These Acronyms and How Can They Help Me with My Filing? |
Sandra Minjoe,
Judy Phelps |
|
4 |
| PharmaSUG |
2003 |
Clinical Data Model and FDA/CDISC Submissions |
Mark Edwards,
Gajanan Bhat |
|
10 |
| PharmaSUG |
2003 |
Clinical Data Standards - An eSubmissions Perspective |
Shy Kumar |
|
6 |
| PharmaSUG |
2003 |
Confidence Intervals in Analysis and Reporting of Clinical Trials |
Guangbin Peng |
|
8 |
| PharmaSUG |
2003 |
Datamapper: A Documentation Generator for SAS Metadata |
Lei Zhang |
|
8 |
| PharmaSUG |
2003 |
Implementing a Quarterly Contract Payments System for Clinical Trials |
Mark McLaughlin,
Independent Contractor |
|
6 |
| PharmaSUG |
2003 |
Likelihood Approach in Estimation and Testing Problems Involving Grouped Data |
Daniel Bonzo,
InfoVision Consultants |
|
8 |
| PharmaSUG |
2003 |
Parameter estimation for incomplete bivariate longitudinal data in clinical trials |
Naum M. Khutoryansky |
|
6 |
| PharmaSUG |
2003 |
Producing Structured Reports in a Regulated Environment Using SAS - Meeting 21 CFR Part 11 |
Andrew Lawton,
Michael Pearce |
|
6 |
| PharmaSUG |
2003 |
Sensitivity of DISCRIM PROC for Different List of Variables to Separate a Study Population by Treatment Subgroups in Clinical Trial with a New Antidepressant |
Treatment Subgroups |
|
6 |
| PharmaSUG |
2003 |
Standardizing Data Processing and e-Publishing for the Pharmaceutical Industry |
Shawn Wang |
|
6 |
| PharmaSUG |
2003 |
StARScope: A Web-Based SAS Prototype for Clinical Data Visualization |
Fang Dong,
Subrahmanyam Pilli,
Scott Pivirotto,
Jeff Van Domelen |
|
6 |
| PharmaSUG |
2003 |
Testing CDISC's Operational Data Model in SAS |
Michael C. Palmer |
|
4 |
| PharmaSUG |
2003 |
The behind the Scenes of Extracting SAS Data Sets from Oracle Clinical |
Angela S. Ringelberg |
|
6 |
| PharmaSUG |
2003 |
Web-based Information Management for Data Monitoring Committees |
Mike Bodenstab |
|
4 |
| PharmaSUG |
2003 |
Why SAS is the Best Place to Put Your Clinical Data |
Steven A. Wilson |
|
10 |
| SUGI |
2003 |
A Table-Driven Solution for Clinical Data Submission |
Jim Sattler |
source |
6 |
| SUGI |
2003 |
Beyond PROC LIFETEST: Alternative Linear Rank Tests for Comparing Survival Distribution |
Alan B. Cantor |
source |
4 |
| SUGI |
2003 |
Creating Tables or Listings with a Zero-Record SAS Data Set -- Basic Program Structure and Three Simple Techniques |
Rubin Nan,
Victor Loher |
source |
3 |
| SUGI |
2003 |
Hot Links: Creating Embedded URLs Using ODS |
Jonathan M. Squire |
source |
|
| SUGI |
2003 |
Managing Clinical Trials Data with a SAS-Based Web Portal |
J. Philip Miller,
James Schauer,
Jack D. Baty,
Sarah Littlewood,
Robert M. Lill,
Reuben Richards,
Kathryn Trinkaus |
source |
|
| SUGI |
2003 |
Metadata Application on Clinical Trial Data in Drug Development |
Julia Z. Zhang,
David C. Chen,
Tor-lai Wong |
source |
3 |
| SUGI |
2003 |
P-Value Generation Simplified with a Single SAS Macro |
Christopher S. Hord,
Peter J. Anderson |
source |
3 |
| SUGI |
2003 |
Smoothing with SAS PROC MIXED |
Alexander Pedan |
source |
5 |
| SUGI |
2003 |
StARScope: A Web-Based SAS Prototype for Clinical Data Visualization |
Fang Dong,
Thomas Pivirotto,
Subrahmanyam Pilli,
Jeffrey L. Van Domelen |
source |
|
| MWSUG |
2002 |
Using SAS System to Geneerate Customized Kaplan-Meieer Curves and its Applciation to Presentation in Clinical Research |
Daojun Mo,
Yiyong Fu |
|
14 |
| NESUG |
2002 |
A Practical Approach to Create Clinical Summary Tables |
Jiang Jin |
|
2 |
| NESUG |
2002 |
Calling External Compiled Code into SAS with Application to Clinical Trial Safety Analyses |
Eric Qi,
A. Lawrence Gould,
Liping Zhang,
Weifeng Xu |
|
3 |
| NESUG |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
|
7 |
| NESUG |
2002 |
Efficiency and Quality Control in the Preparation of a Preparing Statistical Review Aid in FDA e-Submissions |
James Wu,
Frederick A. Cieri,
Amy Gillespie |
|
4 |
| NESUG |
2002 |
Integration of SAS and NONMEM for Automation of Population Pharmacokinetic/Pharmacodynamic Modeling on UNIX systems |
Alan Xiao,
Jill Fiedler-Kelly |
|
5 |
| NESUG |
2002 |
User-Interface Tool Choice and Audit Trail Tool Choice for a SAS Based Data Entry/Verify System for Clinical Trials Data |
Barry R. Cohen |
|
6 |
| SESUG |
2002 |
A GUI System for the Generation of Clinical Trial Randomization Plans for Collaborative Multi-institutional Clinical Trials |
Sijian Zhang,
Mark Carpenter,
John W. Gnann |
source |
3 |
| WUSS |
2002 |
Perform Survival Analysis for Clinical Trials Using ODS |
Wei Cheng |
source |
5 |
| WUSS |
2002 |
Utilizing Clinical SAS Report Templates with ODS |
Sunil Kumar Gupta |
source |
6 |
| SEUGI |
2002 |
A data warehouse and data exploitation solution in clinical trials [presentation] |
F. Patarnello,
V. Frizzo |
source |
24 |
| SEUGI |
2002 |
A SAS and Java Application for Reporting Clinical Trial Data [presentation] |
Kevin Kane |
source |
31 |
| SEUGI |
2002 |
A www psychological quest using SAS [presentation] |
Bernard Pirali,
Michel Lehon,
Olivier Lebon,
Samuel Dupont,
Serge Roberfroid,
Sylvie Linotte |
source |
21 |
| SEUGI |
2002 |
Computer management of Human Immunodeficiency Virus Epidemiological Cohorts [presentation] |
Anne Peroz,
Faroudy Boufassa |
source |
39 |
| SEUGI |
2002 |
GAMBRO - A Leading Global Medical Technology and Healthcare Company [presentation] |
Catherine Collier |
source |
10 |
| SEUGI |
2002 |
Moving from PC SAS 6.12 to SAS 8.2 on a Terminal Server [presentation] |
Monika Kawohl |
source |
22 |
| SEUGI |
2002 |
SAS application: PEST 4 for sequential clinical trials [presentation] |
Tatsuru Matsushita |
source |
19 |
| SEUGI |
2002 |
SAS Drug Development: Intelligent Research Management [presentation] |
Andrew T. Fagan |
source |
18 |
| PharmaSUG |
2002 |
A Web Based Clinical Data Browser |
Eric Grelak,
Chester Springs |
|
6 |
| PharmaSUG |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
|
8 |
| PharmaSUG |
2002 |
Data Exploration in the Pharmaceutical Industry |
Andrew T. Fagan |
|
8 |
| PharmaSUG |
2002 |
Date and Time Values in Clinical Trial Data |
George Li |
|
4 |
| PharmaSUG |
2002 |
Discriminant Analysis (PROC DISCRIM) to Separate a Study Population by Treatment Subgroups in a Clinical Trial with a New Antidepressant |
Lev Sverdlov,
Park Ridge |
|
6 |
| PharmaSUG |
2002 |
Imputation of Longitudinal Incomplete Data in Clinical Trials |
Naum M. Khutoryansky |
|
4 |
| PharmaSUG |
2002 |
IND Annual Reporting at a Glance |
Kristi Wiser |
|
6 |
| PharmaSUG |
2002 |
Let ODS in SAS V8 Help to Speed Up Your Electronic Clinical Study Report (e-CSR) |
Jim J. Wang,
Sherry L. Pinnell,
Tikiri B. Karunasundera |
|
4 |
| PharmaSUG |
2002 |
Pitfalls and Successes of Automating In-Text Tables for a Clinical Study Report: A Case Study |
Matthew J. Becker |
|
6 |
| PharmaSUG |
2002 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
|
10 |
| PharmaSUG |
2002 |
Serology Inventory System |
Mariya Charny |
|
8 |
| PharmaSUG |
2002 |
The 800-Pound Gorilla: Taking on the Challenge of Globally Standardizing Adverse Event and Medication Reporting |
Deborah Harper,
Jennifer Tjernagel |
|
4 |
| PharmaSUG |
2002 |
The CDISC Laboratory Data Interchange Standard: Using SAS To Read and Write CDISC Compliant Data Sets and Files |
Margaret Hung |
|
8 |
| PharmaSUG |
2002 |
Two Step Approach to Automatically Generate ESTIMATE Statements for Pair-wise Treatment Comparisons |
Eric Qi,
Guanghan (Frank) Liu |
|
4 |
| PharmaSUG |
2002 |
Web-Based Code Generation for Derived Data Using SAS/Intrnet |
Luai R. Alzoubi,
Kent Nassen,
Subrahmanyam Pilli |
|
10 |
| SUGI |
2002 |
An Useful Chart to Display Adverse Event Occurrences in Clinical Trials |
Chuanchieh Hsu,
Zhongwei Zhou,
James M. Hardin |
source |
4 |
| SUGI |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
source |
7 |
| SUGI |
2002 |
Dynamic Data Matching in Clinical Trial Research |
Zaizai Lu,
David Shen |
source |
4 |
| SUGI |
2002 |
Generating Randomization Schedules Using SAS Programming |
Chunqin Deng,
Julia C. Graz |
source |
6 |
| SUGI |
2002 |
How ODS Simplified Our Web-based Clinical Trial Reports |
Julie A. Inglish |
source |
3 |
| SUGI |
2002 |
Run All Your SAS Programs in One Program: Automatically |
Lingyun Chen,
Steven A. Gilbert |
source |
2 |
| SUGI |
2002 |
SAS Tools for Meta-analysis |
Robert M. Hamer,
Pippa M. Simpson |
source |
6 |
| SUGI |
2002 |
Unit-of-Analysis Programming |
Vanessa C. Hayden |
source |
6 |
| SUGI |
2002 |
User-Interface Tool Choice and Audit Trail Tool Choice for a SAS Based Data Entry/Verify System for Clinical Trials Data |
Barry R. Cohen |
source |
6 |
| MWSUG |
2001 |
Date & Time Values in Clinical Trial Data |
George Li,
John Morrill |
|
4 |
| NESUG |
2001 |
A Novel Approach to Developing a Patient Profile Reporting Application |
Curtis Wolf,
Steven Light |
|
6 |
| NESUG |
2001 |
REx: An Automated System for Extracting Clinical Trial Data from Oracle to SAS |
Edward McCaney |
|
5 |
| NESUG |
2001 |
Using SAS/Warehouse Administrator., Enterprise Guide., and Enterprise Reporter. to Manage and Access a Clinical Data Warehouse |
Theresa J. Kelso |
|
3 |
| VIEWS |
2001 |
Processing Free Text With SAS Version 8 [presentation] |
Jeremy Gurney |
|
31 |
| VIEWS |
2001 |
SAS/AF Application in Sequential Clinical Trials |
Tatsuru Matsushita |
|
5 |
| VIEWS |
2001 |
Software Validation in Clinical Trial Reporting: Experiences from the Biostatistics & Data Sciences Department |
Andrea Baker |
presentation |
5 |
| VIEWS |
2001 |
Speeding Up the Validation Process of Clinical Trials Data [presentation] |
Ali Dootson |
|
23 |
| VIEWS |
2001 |
Your Clinical Trials Data Entry and Management Solution - The SAS UK Clinical Data Management Knowledge Solution [presentation] |
Jane Powell |
|
19 |
| WUSS |
2001 |
Clean Your Data with PROC SQL |
Ann Olmsted |
source |
5 |
| SEUGI |
2001 |
Delivering Clinical Study Data Using SAS/IntrNet [presentation] |
Barrie Nelson,
Robert Davis |
source |
28 |
| SEUGI |
2001 |
Software Validation in Clinical Trial Reporting: Experiences from the Biostatistical & Data Sciences Department [presentation] |
Andrea Baker |
source |
25 |
| SEUGI |
2001 |
The SAS/UK Clinical Data Management Knowledge Solution [presentation] |
Ian Pimblett |
source |
23 |
| SEUGI |
2001 |
Web and Data Warehouse technology combined in a pharmaceutical decision support system [presentation] |
Christine Vander Vorst |
source |
29 |
| PharmaSUG |
2001 |
An Analysis Programming Process Focused on Data Derivation |
Lee Walke |
|
4 |
| PharmaSUG |
2001 |
An Application of Continual Reassessment Method Using SAS System |
Naoki Ishizuka |
|
4 |
| PharmaSUG |
2001 |
Applying Statistical Sampling Plans To Data Entry Procedures To Increase Data Quality |
Roderick Lashley |
|
4 |
| PharmaSUG |
2001 |
Clinical Data Warehouse Development with Base SAS Software and Common Desktop Tools |
Patricia L. Gerend |
|
10 |
| PharmaSUG |
2001 |
Compass: a web interface to a Data Warehouse for Pharmaceutical Decision Support |
Christine Vander Vorst |
|
2 |
| PharmaSUG |
2001 |
Converting CP World Application to SAS V8: A Discussion of Issues and Hurdles Encountered |
Fang Dong |
|
4 |
| PharmaSUG |
2001 |
Data Visualization of Phase 1 Clinical Studies - "Big Al's World" or Using SAS Version 8 to Acquire Quality Ice Cream |
Richard F. Synowiec |
|
8 |
| PharmaSUG |
2001 |
Developing Clinical Data Management Systems using Version 8.1 of SAS/AF |
Steven A. Wilson |
|
10 |
| PharmaSUG |
2001 |
Digging for Gold: SAS Tools for Extracting Clinical Study Information from Oracle Clinical |
Nancy Brucken |
|
4 |
| PharmaSUG |
2001 |
Electronic Clinical Study Reports (e-CSR) using ODS in SAS V8e |
Hiroshi Otsu,
Tadayuki Kitagawa |
|
4 |
| PharmaSUG |
2001 |
FDA Reviewers as Ultimate End Users: Using the SAS System to Construct e-Submissions that Actually Facilitate the NDA / BLA Review Process |
Rich Vachal |
|
6 |
| PharmaSUG |
2001 |
From SAS ASCII Output to Word Document - A SAS Macro Approach |
Jianlin (Jay) Zhou |
|
4 |
| PharmaSUG |
2001 |
Imputation Techniques Using SAS Software For Incomplete Data In Diabetes Clinical Trials |
Naum M. Khutoryansky,
Won-Chin Huang |
|
4 |
| PharmaSUG |
2001 |
Leveraging Existing SAS Programs for Wireless Delivery |
Deborah A. Testa,
Russell Holmes |
|
3 |
| PharmaSUG |
2001 |
Pre-requisite to Effective Validation: Evaluating Your Clinical Trials Software Development Environment Using SEI's Capability Maturity Model for Software |
David C. Izard |
|
8 |
| PharmaSUG |
2001 |
Unit-of-Analysis Programming |
Vanessa C. Hayden,
Fidelity Investments |
|
6 |
| PharmaSUG |
2001 |
Use of statistical techniques for tracking patients |
Franky De Cooman |
|
2 |
| PharmaSUG |
2001 |
Using SAS to Create a Centralized Parameter File for Analysis and Reporting |
Phebe Joseph |
|
4 |
| PharmaSUG |
2001 |
Warehousing Clinical Pharmacogenomics Data |
Philip M. Pochon |
|
6 |
| SUGI |
2001 |
%ToC: A Macro for Generating Table of Contents from SAS Output |
Hong Chen |
source |
4 |
| SUGI |
2001 |
A SAS Program to Perform Adaptive Randomization |
Carey G. Smoak,
Jin-Sying Lin |
source |
2 |
| SUGI |
2001 |
Clinical Trial System - A Front End SAS/AF Application |
Quan Ren |
source |
7 |
| SUGI |
2001 |
Converting CP World Application to SAS V8: A Discussion of Issues and Hurdles Encountered |
Fang Dong |
source |
4 |
| SUGI |
2001 |
Data Visualization of Phase 1 Clinical Studies - by "Big Al's Worlds " |
Richard F. Synowiec |
source |
6 |
| SUGI |
2001 |
Digging for Gold: SAS Tools for Extracting Clinical Study Information from Oracle Clinical |
Nancy Brucken |
source |
3 |
| SUGI |
2001 |
Internet and Web Resources for SAS Programmers and Statisticians |
Wei Cheng |
source |
6 |
| SUGI |
2001 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
9 |
| SUGI |
2001 |
The FASTCLUS Procedure as an Effective Way to Analyze Clinical Data |
Lev Sverdlov |
source |
7 |
| SUGI |
2001 |
Using SAS/IML Software for Solving Non-Standard Optimization Problems in Growth Modeling and Optimal Design |
Inna Perevozskaya |
source |
6 |
| SUGI |
2001 |
Wireless SAS Applications for Tracking Clinical Research |
Deborah A. Testa,
Russell Holmes |
source |
3 |
| SESUG |
2000 |
A High-Level Summary Table Generation Language Supplying the Missing Link between PROC MEANS using a CLASS Statement and PROC TABULATE |
Dorothy E. Pugh |
source |
9 |
| SESUG |
2000 |
Performing Exact Logistic Regression with the SAS R /AD System |
Robert E. Derr |
source |
10 |
| SESUG |
2000 |
Using SAS/AF to Create Applications for Looking Up and Coding Adverse Events and Generic Drug Names in Clinical Trials |
Karen B. Fowler,
Emily A. Mixon |
source |
3 |
| NESUG |
2000 |
A Pragmatic Intent-to-Treat Analysis Using SAS |
Patricia R. Houck,
Sati Mazumdar,
Kenneth S. Liu,
Charles F. Reynolds III |
|
5 |
| NESUG |
2000 |
Clinical Trial Laboratory Data Management using the SAS System |
Marianne Hack |
|
5 |
| NESUG |
2000 |
Programming Data Displays Using SAS Software: Meeting Regulatory Requirements for Quality |
Michael A. Walega |
|
11 |
| NESUG |
2000 |
Source Code Revision Control Systems and Auto-Documenting Headers for SAS Programs on a UNIX or PC Multiuser Environment |
Terek J. Peterson,
Max Cherny |
|
5 |
| NESUG |
2000 |
Think Outside the Box: Analysis of Categorical Data |
Margaret Ann Goetz |
|
5 |
| WUSS |
2000 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
5 |
| WUSS |
2000 |
SAS, Trialex, an Intranet, and Adobe Acrobat 4.0: Could This Be an FDA Electronic Submission? |
David Eber |
source |
4 |
| WUSS |
2000 |
Using of SAS Software to Develop an Electronic Events Review Process for Outcomes Adjudication by an Events Review Committee with an Electronic Data Transfer |
David Eber,
See Phan |
source |
6 |
| MWSUG |
2000 |
SAS MACRO Basics and Fundamentals |
Timothy J. Harrington |
|
10 |
| SEUGI |
2000 |
Building an Integrated Clinical Trial Data Management System With SAS Using OLE Automation and ODBC Technology [presentation] |
Alexandre Peregoudov |
source |
9 |
| SEUGI |
2000 |
Clinical Data Warehousing Functionality [presentation] |
Michael Roberson |
source |
39 |
| SEUGI |
2000 |
Coil Coating quality on the Web [presentation] |
Jeroen Liefhebber |
source |
17 |
| SEUGI |
2000 |
Creating validated standard output using the System Development Life Cycle (SDLC): A practical approach with the Biometrics Department of Solvay Pharmaceuticals [presentation] |
Saskia Janssen |
source |
37 |
| SEUGI |
2000 |
From Infancy to Maturity: SAS/PH-Clinical Introduction at Fujisawa [presentation] |
Soren Kristiansen |
source |
40 |
| SEUGI |
2000 |
Genetic Data Analysis with Enterprise Mineer [presentation] |
John C. Brocklebank,
Wayne Thompson |
source |
24 |
| SEUGI |
2000 |
Implementation of an International SAS Programming Environment for Clinical Trials [presentation] |
Adrienne M. Jenn |
source |
24 |
| SEUGI |
2000 |
MDS GLARIF: On-line access to clinical laboratory data from all over the world [presentation] |
Jean Yves Gouriou |
source |
18 |
| SEUGI |
2000 |
Successful and Faster Drug Development through Data Mining [presentation] |
Dirk Belmans |
source |
15 |
| SEUGI |
2000 |
Targeted Drug Discovery through Data Mining [presentation] |
John C. Brocklebank,
Wayne Thompson |
source |
28 |
| SEUGI |
2000 |
The New SAS Macro POSET for Evaluating Coherent Alternatives in Nonrandomized Studies [presentation] |
Anette Pfahlberg,
Beate Himmler,
Olaf Gefeller |
source |
6 |
| PharmaSUG |
2000 |
%RPT_UTIL: A SAS Macro for Enhancing Reports in Clinical Trials |
Wei Cheng |
|
6 |
| PharmaSUG |
2000 |
A Nonparametric Approach for the Statistical Analysis of Time to First Event in Censored Paired Data |
Roderick Lashley,
Dennis W. King,
Pam Marks |
|
3 |
| PharmaSUG |
2000 |
A Standard Reporting System for Phase 1 Clinical Trials A SAS Based Application "Clin Pharm World" |
Fang Dong,
Lorraine Dunn,
Brian Rosson,
Richard F. Synowiec |
|
4 |
| PharmaSUG |
2000 |
An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome |
P. Chris Holland |
|
5 |
| PharmaSUG |
2000 |
An Integrated Review Tool: Using the SAS SQL Library for C to Access SAS Data |
Andrea L. Contino |
|
1 |
| PharmaSUG |
2000 |
Calculating a Nonparametric Estimate and Confidence Interval Using SAS Software |
Chris Decker |
|
3 |
| PharmaSUG |
2000 |
Check Digits: Avoiding Errors in Clinical Trials |
Malachy J. Foley |
|
5 |
| PharmaSUG |
2000 |
Collapsing Adverse Experiences Records |
Shi-Tao Yeh |
|
5 |
| PharmaSUG |
2000 |
Compliance Readiness for the New Millennium How does your SAS Environment Measure Up? |
Steven Light |
|
6 |
| PharmaSUG |
2000 |
Data Mining and Statistics in a Pharmaceutical Environment |
Franky De Cooman |
|
3 |
| PharmaSUG |
2000 |
Developing Clinical Data Management Systems using Version 8 of SAS/AF |
Steven A. Wilson |
|
10 |
| PharmaSUG |
2000 |
Using SAS for the Statistical Analysis of a Bivariate Primary Endpoint in a Clinical Trial of Chronic Fatigue Syndrome (CFS) |
Naum M. Khutoryansky,
David R. Strayer,
William A. Carter |
|
3 |
| SUGI |
2000 |
A Robust Generalized Axis-scaling Macro |
Dorothy E. Pugh |
source |
5 |
| SUGI |
2000 |
Automatically Converting Data Set Specifications |
Melanie A. Paules,
Shi-Tao Yeh,
Pilita R. Canete |
source |
6 |
| SUGI |
2000 |
Design and Analysis of Cancer Control Studies via the SAS System |
Jeff A. Sloan,
Charles L. Loprinzi,
Paul J. Novotny |
source |
10 |
| SUGI |
2000 |
Performing Exact Logistic Regression with the SAS System |
Bob Derr |
source |
10 |
| SUGI |
2000 |
SAS Software and Microsoft Visual Basic for Applications Make Beautiful Reports Together |
Aileen L. Yam |
source |
5 |
| SUGI |
2000 |
Standard Reporting System for Phase I Clinical Trials |
Fang Dong,
Brian K. Rosson,
Richard F. Synowiec,
Lorraine Dunn |
source |
4 |
| SESUG |
1999 |
Using SAS/AF to Create Applications for the Administrative Aspects of Data Management in Clinical Trials |
Emily A. Mixon,
Karen B. Fowler,
Felicita David |
source |
4 |
| WUSS |
1999 |
Exploring Enzyme-Linked Immunosorbent Assay (ELISA) Data with the SAS Analyst Application |
Stewart L. Fossceco,
Nathan A. Curtis |
source |
9 |
| WUSS |
1999 |
Quantifying Regression to the Mean Using PROC MIXED |
Thaddeus J. Haight,
Long Ngo,
Ira Tager |
source |
6 |
| NESUG |
1999 |
Data Warehousing in Pharmaceuticals and Healthcare: An Industry Perspective |
M. Kumar Sagar,
Himanshu Raval |
|
10 |
| NESUG |
1999 |
Generalized Report Programming Techniques Using Data-Driven SAS Code |
Kathy Hardis Fraeman,
Karen G. Malley |
|
7 |
| MWSUG |
1999 |
A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System |
Jayawant N. Mandrekar,
Daniel J. Sargent,
Paul J. Novotny,
Jeff A. Sloan |
|
6 |
| MWSUG |
1999 |
Sample Size Determination From A Pilot Bioequivalence Study For A Future Pivotal Bioequivalence Study: A SAS Procedure |
Xiang Gao,
Henry Cheng |
|
7 |
| MWSUG |
1999 |
SAS MACRO Basics and Fundamentals |
Timothy J. Harrington |
|
10 |
| MWSUG |
1999 |
Using Continuous Sampling Plans to Quantify the Effectiveness of Quality Assurance Checks on Data From Clinical Trials |
Dennis W. King,
Roderick Lashley |
|
4 |
| SEUGI |
1999 |
Clinical processes and SAS/PH-Clinical, a good marriage? [presentation] |
Patrick Genyn |
source |
24 |
| SEUGI |
1999 |
Developing a SAS data management system using FRAME technology [presentation] |
David Smith,
Sandy Meek |
source |
33 |
| SEUGI |
1999 |
Experiences when using SAS/PH-Clinical software in clinical trials [presentation] |
Gunnar Magnusson |
source |
28 |
| SEUGI |
1999 |
High-quality SAS reporting: which is the optimal output format? [presentation] |
Mika Leinonen |
source |
39 |
| SEUGI |
1999 |
Using SAS software with other packages to produce faster and more reliable analysis of adverse events in clinical trials [presentation] |
Michael O'Kelly |
source |
34 |
| SUGI |
1999 |
A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System |
Daniel J. Sargent,
Jayawant N. Mandrekar,
Paul J. Novotny,
Jeff A. Sloan |
source |
|
| SUGI |
1999 |
A SAS Module/Macro Program for Computing Statistical Power Curves for Detecting Treatment Effect |
David Olaleye |
source |
6 |
| SUGI |
1999 |
Advances in Multiple Comparisons and Multiple T-Tests Using the SAS System |
Peter H. Westfall,
Randall D. Tobias |
source |
9 |
| SUGI |
1999 |
An Investigation of Quality-of-Life Issues in Patient Treatment Using Enterprise Miner |
Patricia B. Cerrito,
Kelly McMasters,
Vicki Viar |
source |
6 |
| SUGI |
1999 |
Analyzing Oncology Patient Health Care Costs Using the SAS System |
Jeff A. Sloan,
Steven S. Cha,
Judith L. Wagner,
Cristine Allmer,
Steven R. Alberts,
Jed Lindman |
source |
6 |
| SUGI |
1999 |
Automating the Management of a Data Warehouse |
Sy J. Truong,
Kathy R. Boussina |
source |
5 |
| SUGI |
1999 |
Data Warehousing in Pharmaceuticals and Healthcare: An Industry Perspective |
M. Kumar Sagar,
Himanshu Raval |
source |
10 |
| SUGI |
1999 |
Developing Standardized Requirements, Specifications and Programs for Clinical Trials Reports |
Deborah J. Harper,
Nancy Brucken,
Christopher Makowski |
source |
4 |
| SUGI |
1999 |
Exploring Enzyme-Linked Immunosorbent Assay (ELISA) Data with the SAS Analyst Application |
Stewart L. Fossceco,
Nathan A. Curtis |
source |
9 |
| SUGI |
1999 |
TAP into SAS/Frame Technology |
David M. Hartman |
source |
6 |
| SCSUG |
1998 |
Laboratory Data Management and Reporting |
O. M. Little |
|
30 |
| WUSS |
1998 |
Automating a Follow-up Clinical Trial Data Collection System Using HP UNIX SAS/SHARE, SAS/AF Frame Entry, and SAS FSP |
Long Ngo,
Nick Pászty,
Christopher R. Cartwright |
source |
6 |
| WUSS |
1998 |
Building An Online Clinical Evaluation System Using SAS/AF Frame Entry, and SAS/FS{ |
Long Ngo,
Adam Zhang |
source |
6 |
| NESUG |
1998 |
Monitoring Data Discrepancies During Clinical Trials |
Cornelius Chase |
|
4 |
| SESUG |
1998 |
A Simplified Reporting Strategy: "Summary" Data Sets for Reporting on Data from Multiple Source Data Sets |
Steve Ross |
|
6 |
| SESUG |
1998 |
Applying a Robust Generalized Axis-sealing Algorithm to the Use of SAS/GRAPW |
Dorothy E. Pugb. ClinTriais |
|
2 |
| SESUG |
1998 |
Coders Corner |
Yet Another,
Dorothy E. Pugh,
CIiDTriaIs Researcll |
|
4 |
| SESUG |
1998 |
Data Validation Using a SAS Format |
John R. Gerlach |
|
3 |
| SESUG |
1998 |
Software for GEE: PROC GENMOD and SUDAAN |
Babubhai V. Shah |
|
5 |
| SEUGI |
1998 |
Business Intelligence and supply chain management [presentation] |
Sander Piet |
source |
20 |
| SEUGI |
1998 |
Data Warehouse+ |
Willem Wegman |
source |
2 |
| SEUGI |
1998 |
Data warehousing to support commercial reorganisation [presentation] |
Eddy Volcher,
Philippe Colpin |
source |
46 |
| SEUGI |
1998 |
Forecasting Software - A sales planning tool for the Marketing Department [presentation] |
Christophe Bonnart |
source |
11 |
| SEUGI |
1998 |
Getting the most out of SAS/PH-Clinical Software: The future is now |
Patrick O'Donoghue |
source |
49 |
| SEUGI |
1998 |
Unpleasant data? A chance of powerful multi-variant analysis in clinical trials with data not meeting the conditions |
Thomas Bregenzer |
source |
13 |
| PharmaSUG |
1998 |
Comparing Clinical Trials Data Using Population Trees |
Lisa McNamara Hlina |
|
7 |
| PharmaSUG |
1998 |
Designing Edit Check Subsystem in SAS/IntrNet |
James Sun,
Monmouth Junction |
|
5 |
| PharmaSUG |
1998 |
Development of Global Reporting Systems for the Hoechst Marion Roussel Inc. |
Dorothy Hu Huang,
I. Outline |
|
7 |
| PharmaSUG |
1998 |
Managing SAS/PH-Clinical in a Multiple Instance Environment |
Steven Light,
Paul M. Gilbert |
|
3 |
| PharmaSUG |
1998 |
Serving Up Clinical Information Globally to your Web Browser from MVS |
Don Johns |
|
5 |
| PharmaSUG |
1998 |
Supporting the "Program-Analyze-Write-Review "Process with a Development Environment for Base SAS and the Macro Language |
Barry R. Cohen |
|
6 |
| PharmaSUG |
1998 |
The Causes, Impact and Detection of Duplicate Observations |
Alice M. Cheng |
|
11 |
| SUGI |
1998 |
An Introduction to the Analysis of Repeated Measures for Continuous Response Data using PROC GLM and PROC MIXED |
Robert M. Hamer,
Pippa M. Simpson |
source |
4 |
| SUGI |
1998 |
Application of Maximum Contrast Method to Biomedical Data Using MU L TTEST |
Chikuma Hamada,
Junji Kishimoto |
source |
6 |
| SUGI |
1998 |
Convex Hull Test for Ordinal Categorical Data Using the SAS System |
Dayong Li,
Huanhong Xia |
source |
6 |
| SUGI |
1998 |
Producing Structured Clinical Trial Reports Using SAS: A Company Solution |
Andrew Lawton,
Helen Dewberry,
Michael Pearce |
source |
6 |
| SUGI |
1998 |
Supporting the "Program-Analyze-Write-Review "Process with a Development Environment for Base SAS and the Macro Language |
Barry R. Cohen |
source |
6 |
| SUGI |
1998 |
Using the Data Warehouse Model to Streamline and Accelerate New Drug and Medical Device Development |
Martin J. Rosenberg |
source |
5 |
| SCSUG |
1997 |
Statistical Enhancements in Release 6.12 of the SAS System |
Maura E. Stokes |
|
7 |
| PNWSUG |
1997 |
Developing SAS/AF Class Libraries for Automated Program Generation |
Carl R. Haske |
|
9 |
| WUSS |
1997 |
Desing of the Clinical Data Portion of a CANDA to Facilitate Review by CDER |
Kay Obenshain |
source |
5 |
| WUSS |
1997 |
The Use of Central Analysis File or Patient File in the Analysis and Management of Clinical Trials Data |
Ajit Gemunu de Silva |
source |
3 |
| WUSS |
1997 |
Using SAS as a Clinical Data Repository |
Carl R. Haske |
source |
6 |
| WUSS |
1997 |
Using the Data Warehouse Model is Streamline and Accelerate New Drug and Medical Device Development |
Martin J. Rosenberg |
source |
5 |
| NESUG |
1997 |
An Evaluation of SAS/PH-Clinical Software as a Pharmaceutical Reporting Tool |
Phil Giangiulio |
|
11 |
| NESUG |
1997 |
Paper-less Reporting: Online Data Review and Analysis Using SAS/PH-Clinical Software |
Eileen Ching |
|
5 |
| NESUG |
1997 |
Survival Analysis: Non-Traditional Applications for Non-Statisticians |
Margaret Ann Goetz |
|
5 |
| NESUG |
1997 |
Using PROC SQL to Create Ad Hoc Reports |
Anne Marie Smith |
|
7 |
| SESUG |
1997 |
Comparing Clinical Trials Data Using Population Trees |
Lisa McNamara Hlina |
|
6 |
| SESUG |
1997 |
Developing SAS/AF Class Libraries for Automated Program Generation |
Carl R. Haske |
|
9 |
| SESUG |
1997 |
Learning About Your Data: Tips and Techniques for Looking at Large Files |
Sandra D. Schlotzhauer |
|
10 |
| SEUGI |
1997 |
A data management system for use in the pharmaceutical and biotechnology Industries |
Ellen Krantz |
source |
12 |
| SEUGI |
1997 |
Conventional and unconventional graphs in SAS |
Julian Singer |
source |
8 |
| SEUGI |
1997 |
Do it yourself: tips and tricks in building your own application using SAS macro language |
Angelo Tinazzi |
source |
7 |
| SEUGI |
1997 |
Information delivery techniques used for standard analysis of clinical trials |
Dirk Grosse |
source |
9 |
| PharmaSUG |
1997 |
A SAS/AF Class Library for Automated Generation of Clinical Report Programs |
Carl R. Haske |
|
7 |
| PharmaSUG |
1997 |
ClinAccess: An Integrated Client/Server Approach to Clinical Data Management and Regulatory Approval |
Martin J. Rosenberg |
|
9 |
| PharmaSUG |
1997 |
Clinical Software Systems Development in SAS/AF |
Carl R. Haske |
|
11 |
| PharmaSUG |
1997 |
Controlling for Experimentwise Type II Error: Optimum Patient Allocation for a Three Armed, Parallel, Randomized, Controlled Clinical Trial with Binary Outcomes |
Benjamin Duncan |
|
13 |
| PharmaSUG |
1997 |
Design of the Clinical Data Portion of a CANDA to Facilitate Review by CDER |
Kay Obenshain |
|
5 |
| PharmaSUG |
1997 |
Integration of Oracle Clinical databases with SAS/PH-Clinical |
Daniel Gronell |
|
10 |
| PharmaSUG |
1997 |
New Architecture for Linkage of SAS/PH-Clinical Software with Electronic Document Management Systems |
Peter Villiers |
|
7 |
| PharmaSUG |
1997 |
Obtaining Group Sequential Test Boundaries with SAS |
William J. Stager,
Hoechst Marion Roussel,
Jessie J. Yun,
Hoechst Marion Roussel |
|
4 |
| PharmaSUG |
1997 |
System Development Life Cycle for SAS Applications Development Incorporating a Procedure for As-Built Validation of In-Use Products |
Wayne Lanier |
|
7 |
| PharmaSUG |
1997 |
The Standard Programs Management System (SPMS): A Utility to Manage Report Generation within a SAS/AF Application |
Fern Grillo |
|
2 |
| SUGI |
1997 |
Building an Online Information Processing System Using SAS Software and a UNIX Shell Script |
Annie S. Guo,
Long Ngo |
source |
6 |
| SUGI |
1997 |
Creating Clinical Trial Summary Tables Containing P-Values: A Practical Approach Using Standard SAS Macros |
Jun Zuo,
Carl R. Haske |
source |
6 |
| SUGI |
1997 |
Estimation via EM-Algorithm in a Bivariate Random Effects Model |
Amrik Shah,
Kirk A. Easley |
source |
8 |
| SUGI |
1997 |
Generating Data with the SAS Data Set |
Andrew J. L. Cary |
source |
6 |
| SUGI |
1997 |
Graphical and Analytical Tools for the Analysis of Two-Period Crossover Clinical Trials |
Jeff A. Sloan,
Paul J. Novotny,
Charles L. Loprinzi,
Suresh Nair |
source |
|
| SUGI |
1997 |
Learning About Your Data: Tips and Techniques for Looking at Large Files |
Sandra D. Schlotzhauer,
Bob Anschuetz |
source |
|
| SUGI |
1997 |
Meta Data Designer-A Tool for Setting Up Meta Data for a Data Warehouse |
Sy J. Truong |
source |
5 |
| SUGI |
1997 |
Two Methods to Produce Mean Plots of Clinical Trials Data: Why Simplifying with Annotate is Not an Oxymoron |
Michael A. Riddle |
source |
6 |
| SUGI |
1997 |
Use of PROC MIXED in the Analysis of Repeated Measures Data from a Clinical Trial in Obsessive Compulsive Disorder |
William Bushnell,
Martin Steiner |
source |
6 |
| SESUG |
1996 |
Developing Clinical Software Systems in SAS/AF |
Carl R. Haske |
|
10 |
| SESUG |
1996 |
Mission Impossible: The Trials of SAS Support in a Health Care Research Group |
Miriam W. Rosenblatt |
|
6 |
| SESUG |
1996 |
Some Strategies for Efficiently Producing Graphs of Clinical Trials Data |
Michael A. Riddle |
|
6 |
| NESUG |
1996 |
A Simple Way to Create a Clinical Trial Study Data Dictionary |
Frank Liu |
|
3 |
| NESUG |
1996 |
Macros Developed for Statistical Summary and Tabulation of Clinical Data |
William Sun,
David Lago,
David Handelsman,
Jack Shostak |
|
10 |
| NESUG |
1996 |
Take Your Project Tracking System to a New Level - Using SAS to Manage Your Projects |
Connie X. Li,
James Sun |
|
5 |
| NESUG |
1996 |
The Role of SAS Programmers in Clinical Trial Data Analysis |
Ming Wang |
|
6 |
| NESUG |
1996 |
Visualizing Repeated Measures Data in Clinical Trials Using SAS/INSIGHT |
Jan W. Buzydlowski |
|
3 |
| MWSUG |
1996 |
A Set of SAS Macros for Producing Statistical Reports |
Greg A. Grandits |
|
10 |
| MWSUG |
1996 |
Exact Methods in the NPAR1WAY Procedure |
Anupama Narayanan,
Donna L. Watts |
|
5 |
| WUSS |
1996 |
ClinAccess: An Integrated Client/Server Approach to Clinical Data Management and Regulatory Approval |
Martin J. Rosenberg |
source |
9 |
| WUSS |
1996 |
ClinOS: A Commercially Available Set of Tools for SAS Programmers |
Lindley Frahm |
source |
8 |
| WUSS |
1996 |
Design, Analysis and Review Tools for Clinical Drug Development Using SAS Object-Oriented Products |
David H. Christiansen |
source |
8 |
| WUSS |
1996 |
SAS PROC MIXED to Fit Growth Curve Models: Application to a Longitudinal Group Randomization Study |
Biao Wm. Lu,
Sandra Wilson,
David Latini,
David Dayton |
source |
6 |
| WUSS |
1996 |
System Development Life Cycle for SAS Applications Development Incorporating a Procedure for As-Built Validation of In-Use Products |
Wayne Lanier,
Deb Gilmore |
source |
6 |
| PNWSUG |
1996 |
ClinAccess: An Integrated Client/Server Approach to Clinical Data Management and Regulatory Approval |
Martin J. Rosenberg |
|
9 |
| SEUGI |
1996 |
A Practical Application of a SAS Data Warehouse in Clinical Trial Reporting |
Christine Smith,
David Smith |
source |
6 |
| SEUGI |
1996 |
A SAS Macro to Present a Summary Table of the Number of Patients Having Experienced Adverse Events in a Clinical Trial |
Christoph Gerlinger,
Ursula Franke |
source |
8 |
| SEUGI |
1996 |
Graphical aspect of meta-analysis using SAS/GRAPH software and its specific annotate |
Angelo Tinazzi,
Fabrizio Carinci,
Valter Torri |
source |
15 |
| SEUGI |
1996 |
How can the SAS System add business benefit to the Pharmaceutical Industry in the Electronic Drug Submission Process? |
David J. Shannon |
source |
10 |
| SEUGI |
1996 |
Producing clinical trial reports using SAS software: a company solution |
Helen Dewberry,
Michael Pearce |
source |
6 |
| SEUGI |
1996 |
Re-engineering the CAPLA: integrating electronic submissions into the drug development |
Guy Pawson |
source |
34 |
| SUGI |
1996 |
A Simple Way to Create a Clinical Trial Study Data Dictionary |
Frank Liu |
source |
3 |
| SUGI |
1996 |
A Simplified Approach Using Macro Techniques to Create a Clinical Data Reporting System |
Mark Parra |
source |
6 |
| SUGI |
1996 |
A Statistical Analysis Macro Library in SAS Software |
Vivienne Ward,
Carl R. Haske |
source |
5 |
| SUGI |
1996 |
ClinAccess: An Integrated Client/Server Approach to Clinical Data Management and Regulatory Approval |
Martin J. Rosenberg |
source |
9 |
| SUGI |
1996 |
Computer Validation and the SAS System |
William C. Murphy |
source |
4 |
| SUGI |
1996 |
Data Management in Clinical Trials Made Easy |
Fiona Campbell-Daigle |
source |
4 |
| SUGI |
1996 |
Exact Methods in the NPAR1WAY Procedure |
Anupama Narayanan,
Donna L. Watts |
source |
5 |
| SUGI |
1996 |
Fine-tuning Project Management of Clinical Data Processing with SAS Software |
James Sun,
Connie X. Li |
source |
4 |
| SUGI |
1996 |
Mission Impossible: The Trials of SAS Support in a Health Care Research Group |
Miriam W. Rosenblatt |
source |
6 |
| SCSUG |
1995 |
Nine Cell Laboratory Tables |
O. M. Little |
|
23 |
| MWSUG |
1995 |
A Statistical Analysis Macro Library in SAS |
Carl R. Haske,
Vivienne Ward |
|
5 |
| NESUG |
1995 |
A SAS/AF FRAME Application for Clinical Laboratory Review |
Denis Michel |
|
7 |
| NESUG |
1995 |
A Simple Methodology for Developing Clinical Reporting Macros |
Paul M. Gilbert,
Steven Light |
|
6 |
| NESUG |
1995 |
Create a Permanent View by Querying Data From Two Tables |
Owen Jiang,
Robert Musterer |
|
3 |
| NESUG |
1995 |
SAS Macros for Bootstrap Samples with Stratification and Multiple Observations per Subject |
Terry Hyslop |
|
8 |
| NESUG |
1995 |
SAS, FileMaker Pro, and Microsoft Access for Clinical Study Data Management |
Karen G. Malley |
|
9 |
| NESUG |
1995 |
Using Autocall Macros as a Common Codebase of Data Checks for Clinical Trials: Examples Drawn from the Pharmacetutical Industry |
Michael E. Tomb |
|
10 |
| WUSS |
1995 |
ClinAccess: An Integrated Client/Server Approach to Clinical Data Management and Regulatory Approval |
Martin J. Rosenberg |
source |
9 |
| WUSS |
1995 |
Designing Clinical SAS Service Request Forms |
Sunil Kumar Gupta |
source |
3 |
| SESUG |
1995 |
Designing Clinical SAS Service Request Forms |
Sunil Kumar Gupta |
|
3 |
| SESUG |
1995 |
Information Visualization Hacros, Annotate and BAS Graph the Basy Way |
Michael Keohan,
E. Hanover |
|
8 |
| SEUGI |
1995 |
A Simulation Study Using the SAS System - Stepwise Rejective Stopping Boundaries for Clinical Trials with Multiple Treatments |
Barbara G. Schneider |
source |
11 |
| SEUGI |
1995 |
Adverse Event Surveillance Using the SAS System |
Julian Singer |
source |
12 |
| SEUGI |
1995 |
Macro Procedure for Equivalence Testing |
Francois Montestruc |
source |
16 |
| SEUGI |
1995 |
PQRST, a Clinical Trial |
Inger Malmaeus |
source |
6 |
| SUGI |
1995 |
A SAS Macro for Evaluation of Survival Time Data Involving Treatment Conversion Using the Mantel-Byar Method |
Eric T. Sun,
Ching-Chang Hwang |
source |
6 |
| SUGI |
1995 |
ClinAccess: A Client/Server Approach to Clinical Trials Data Management and Regulatory Approval |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1995 |
Macroitis - A Virus or a Drug |
Margaret K. Schrempf |
source |
5 |
| SUGI |
1995 |
Maintaining Blinding in the Presence of Blocking and Identifiable Treatments |
Sharon Barker |
source |
3 |
| SUGI |
1995 |
The Pediatric Oncology Group Accessing Clinical Trial Data Across the Internet via a Bulletin Board System Using SAS/AF and SAS/FSP Software |
Barbara Blum,
Cynthia Hurle |
source |
6 |
| NESUG |
1994 |
Computer-Aided Software Engineering and SAS in Clinical Trials Reporting |
W. Stetson Line |
|
6 |
| NESUG |
1994 |
Replacement Methodology or Maintaining the Rankings of Treatments in Clinical Trials with Discontinuations |
Maureen Fulcher Mele |
|
6 |
| NESUG |
1994 |
Statistical Methods for Assessing the Safety of Products Evaluated in Human Clinical Trials |
John Sourby |
|
8 |
| NESUG |
1994 |
Use of SAS/INSIGHT to Graphically Display Repeated Measures Data |
Jan W. Buzydlowski |
|
3 |
| MWSUG |
1994 |
SAS Randomization Techniques for Clinical Trials |
Linda M. Quinn |
|
6 |
| SESUG |
1994 |
A PPLICA liONS DEVELOPMENT |
David S. Focht |
|
8 |
| SEUGI |
1994 |
A Unique Application Generator for the Management and Control of Clinical Trials Data |
Chaim Singal |
source |
9 |
| SEUGI |
1994 |
Aiming at More Efficient System Support for the R&D Process |
Mark Crawford,
Winfried Koch |
source |
8 |
| SEUGI |
1994 |
Automatic Generation of Clinical Individual Data Documents, Using Connectively to Access Oracle Data on PC |
Gaetane Van der Borght |
source |
4 |
| SEUGI |
1994 |
Budgeting Clinical Trials Using the SAS System Development Environment |
Patrick Genyn |
source |
10 |
| SEUGI |
1994 |
Data Management of Clinical Studies |
Magdolna Kiss |
source |
6 |
| SEUGI |
1994 |
New Features of SAS/PH-Clinical Software |
Brian Fredric |
source |
6 |
| SEUGI |
1994 |
SAS System Macros for Multi-variate Two-sample Tests in the Case of Incomplete Data |
Thomas Bregenzer |
source |
10 |
| SUGI |
1994 |
A Macro to Associate Time-Oriented Data From Two Independent Sources |
David Arnold |
source |
5 |
| SUGI |
1994 |
A Macro to Facilitate the Visualization of Individual Patient Efficacy and Safety During an Investigational (Phase III) Clinical Trial |
Marjorie Bell,
Marcella D. Stricklin |
source |
5 |
| SUGI |
1994 |
An Automated Approach to Patient Exclusion Accountability: Summaries Using SAS Macro Language |
Carl Arneson,
Randall Austin,
Beth Sherrill,
Cam Huffman,
Greg Silva |
source |
5 |
| SUGI |
1994 |
Application of Random-Effects Model for Categorical Data to Antiemetic Clinical Trials in Cancer Patients |
Regina Louie,
Alex Yaroshinsky |
source |
5 |
| SUGI |
1994 |
Developing Integrated Clinical Trials Systems: The ClinAccess Experience |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1994 |
Using SAS/FSP to Develop an On-line Randomization System for Multicenter Clinical Trials |
Margaret Lee,
Dorothea Collins |
source |
6 |
| NESUG |
1993 |
Using SAS Macros to Generate Patient-Oriented Edit Listing from an Ingres Clinical Trials Database |
Varghese N. Kariakose,
James T. Crowe Jr. |
|
9 |
| WUSS |
1993 |
A SAS Program for Sample Size Determination for Equivalence Trials |
Akiko Tomita,
Chul W. Ahn,
Joyce C. Niland |
source |
6 |
| WUSS |
1993 |
An Integrated Clinical Trials System Utilizing Client Server and Graphical User Interface Technology |
Martin J. Rosenberg |
source |
7 |
| MWSUG |
1993 |
An Extraordinary Reporting System for the Pharmaceutical Industry - the Macro Way |
Judy L. Gilbert |
|
5 |
| MWSUG |
1993 |
Using SAS to Create Statistical CANDA (SCANDA) Datasets |
Rocco L. Brunelle,
Debbie Romjue-Bailey,
Bill Huster,
Michelle McNabb,
Sharon Symanowski,
Ted Shaw,
Linda Bergin,
Kathy Koskowicz |
|
5 |
| SEUGI |
1993 |
Integrated Safety Reporting |
Anemone Thalman |
source |
10 |
| SEUGI |
1993 |
Quality and Security of Clinical Data under the SAS System |
Ketil Eidsaunet |
source |
5 |
| SEUGI |
1993 |
The SAS System in Dental Clinical Trials |
Paul Jones |
source |
10 |
| SEUGI |
1993 |
Using the SAS System for COSINOR Analysis of 24 Hour Ambulatory Blood Pressure Monitoring (ABPM) Data |
Roberto Ferrara |
source |
13 |
| SUGI |
1993 |
A SAS Solution: Building a Flexible/Standard System to Report the Analysis of Efficacy Data for Clinical Trials |
Judy A. Sullivan,
Naitee Ting |
source |
6 |
| SUGI |
1993 |
Administering a Large, Long-Term Clinical Trial Requiring a Hierarchical Database Using the SAS System, Release 6.07 |
Mitchell Snyder,
Mark Goldberg,
Michal Benderly |
source |
6 |
| SUGI |
1993 |
An Extraordinary Reporting System for the Pharmaceutical Industry - the Macro Way |
Judy L. Gilbert |
source |
5 |
| SUGI |
1993 |
An Integrated Clinical Trials System Utilizing Client Server and Graphical User Interface Technology |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1993 |
An Interactive SAS/AF System for Sample Size Calculation |
Deborah J. Matos |
source |
6 |
| SUGI |
1993 |
Biometrics Software: What Tools Have Pharmaceutical Biometricians Got in Their Kits? |
David J. Shannon |
source |
6 |
| SUGI |
1993 |
Effective Use of the MULTTEST Procedure in Japanese Biopharmaceutical Studies for Drug Development |
Masakazu Andoh,
Tohru Uwoi |
source |
5 |
| SUGI |
1993 |
Experiences with a General SAS Macro for the Construction of Classification and Regression Trees |
Roland Brandmaier,
H. Ansari,
D. Dickson |
source |
4 |
| SUGI |
1993 |
Graphical Presentation of Multivariate Longitudinal Data |
Maria L. Shabe |
source |
2 |
| SUGI |
1993 |
SAS/PH-Clinical Software: CANDA Implementation Strategies |
Juliana M. Ma,
Sandra D. Schlotzhauer |
source |
8 |
| SUGI |
1993 |
The Progression and Integration of the CANDA at Merck |
Bruce Binkowitz,
Wanda Bidlack,
Nancy Bauer |
source |
6 |
| SEUGI |
1992 |
Facilitating Standard Jobs in Clinical Trials |
Charlotte Stoltz |
source |
17 |
| SEUGI |
1992 |
Improve Speed and Quality in Clinical Trial Analysis Using SAS Macros |
Mark de Somer |
source |
12 |
| SUGI |
1992 |
A SAS Window Application for Generating Follow-up Clinic Schedules and Monitoring Accrual in a VA Cooperative Study |
Joan Derrico |
source |
6 |
| SUGI |
1992 |
A Simulation Study of Estimators for Rates of Changes in Longitudinal Studies with Attrition |
Fong Wang,
Mary Lange |
source |
6 |
| SUGI |
1992 |
An Integrated Clinical Information System for Pharmaceutical Research |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1992 |
Blocked Randomized Assignment of Treatments to Patients in Clinical Trials |
Maria A. Deloria,
George F. Reed |
source |
6 |
| SUGI |
1992 |
Control of Batch Program Execution with the SAS System |
Tyler Witko,
Thomas R. Hoffman |
source |
5 |
| SUGI |
1992 |
Determination of Response Surface Function Using Repeated Measures |
Denise M. Moyse,
David Henry,
Hong-Jiong Shi,
Robert S. Boger,
Clement Maurath |
source |
6 |
| SUGI |
1992 |
Do We Always Need Clinical Stratification in Multicenter Clinical Trials? Results of a Simulation Study |
Roland Brandmaier,
U. Aydemir,
H. Ansari,
J. Hasford |
source |
6 |
| SUGI |
1992 |
Estimating the Cost and Time for Developing SAS Software Applications |
Joel M. Hoffman,
Judith H. Mopsik,
Jeffrey A. Polzin |
source |
7 |
| SUGI |
1992 |
SAS Classes for Nonprogrammers in the Clinical Data Management World |
Susan V. Hale |
source |
4 |
| SUGI |
1992 |
The Use of SAS/GRAPH Software in the Management of Clinical Trials |
MaryAnne DePesquo Hope |
source |
6 |
| SUGI |
1992 |
Use of SAS/AF and SAS/FSP Software to Integrate a Payment System for Patient Information in a Large Multi-Center Clinical Trial |
Dorothea Collins,
Margaret Lee |
source |
6 |
| SUGI |
1992 |
Using SAS Macros and SAS/GRAPH Software to Produce Data-Driven Laboratory Data Plots |
Paul M. Gilbert |
source |
5 |
| SUGI |
1992 |
Using SAS Software to Evaluate the Imaging Performance of Presurgical Diagnostic Tests in the Detection of Cancer |
Kristin R. Dawson |
source |
7 |
| SUGI |
1992 |
Using SAS/ACCESS Software for Rdb in Clinical Trials Research |
Joseph B. McGlynn |
source |
4 |
| SCSUG |
1991 |
Calculating the Power Function of the Wilcoxon Rank Sum Test in 2xK Tables |
Mark Von Tress |
|
7 |
| NESUG |
1991 |
Job Submission Menu (JSM): A Programming Tool to Standardize Clinical Trial Summarization |
Mark Becker,
Iraj Mohebalian,
Lora H. Schwab |
|
6 |
| NESUG |
1991 |
The Progression and Integration of the CANDA at Merck |
Nancy Bauer,
Wanda Bidlack,
Dan Himmel,
Bruce Binkowitz |
|
6 |
| NESUG |
1991 |
Using SAS Statistical Procedures in Medical Research |
Joe Cholewczynski |
|
7 |
| MWSUG |
1991 |
A Flexible System of Reporting Safety Data in Clinical Trials |
Gregory C. Steffens |
|
6 |
| SEUGI |
1991 |
An Interface Between the SAS System and the INFORMIX Database |
J. B. Brown,
K. A. Kelly,
Kevin Kane |
source |
4 |
| SEUGI |
1991 |
Developing Reporting Systems for Clinical Trials in the Pharmaceutical Industry |
David J. Shannon,
Mark Baillet |
source |
12 |
| SEUGI |
1991 |
Features of SAS/PH-Clinical Software |
Gerhard Held,
Patrick O'Donoghue |
source |
10 |
| SEUGI |
1991 |
STARS: Statistical and Reporting System for Clinical Research Data |
A. Longoni,
G. Marcon,
M. Sanarico,
R. Ferrara |
source |
7 |
| SUGI |
1991 |
A CMS-based, Multi-User Planning System for Clinical Data using SAS/AF and SAS/FSP Software |
Thomas E. Schneider,
Mary Catherine Krug |
source |
8 |
| SUGI |
1991 |
A SAS/AF Application for Developing Project Schedules Using SAS/FSP and SAS/GRAPH Software |
Sharon M. Haney,
Laurie T. Elstun,
Kelly K. Antony |
source |
6 |
| SUGI |
1991 |
Analysis of 2 x 2 Cross-over Trials Using an Integrated Macro Package |
Harvie Chang,
Tamara R. Strang |
source |
6 |
| SUGI |
1991 |
Features of SAS/PH-Clinical Software |
Sandra D. Schlotzhauer |
source |
10 |
| SUGI |
1991 |
Job Submission Menu (JSM): A Programming Tool to Standardize Clinical Trial Summarization |
Iraj Mohebalian,
Mark Becker,
Lora H. Schwab |
source |
5 |
| SUGI |
1991 |
The ETRANK Procedure: Procedures for Analyzing Incomplete Repeated Measures Trials with Treatment Related Withdrawals |
Richard Entsuah,
Edmond Williams |
source |
7 |
| SUGI |
1991 |
Using SAS Software to Develop a Clinical Studies Summarization System |
Mary Anne Nemeth,
Teofil Boata |
source |
4 |
| SUGI |
1991 |
Using the SAS System to Customize Life Table Reports for Clinical Trials |
Margaret Lee,
MaryAnne DePesquo Hope,
Tenya Marie Economou,
Dorothea Collins |
source |
6 |
| NESUG |
1990 |
A SAS Software-based System for Tracking Clinical Study Case Record Forms Utilizing Bar Codes |
Jules Bosch |
|
8 |
| NESUG |
1990 |
Handling Data Exclusions in a Clinical Trials DBMS |
Thomas R. Hoffman |
|
10 |
| SEUGI |
1990 |
A SAS Software Based Clinical Trials Data Management System Used at Hoffmann-La Roche |
Mark Aellen-Rumo,
M. Rainisio |
source |
13 |
| SEUGI |
1990 |
SAS Software Version 6.06, Beta-test under VMS - 4 Months User Experience |
Stephen J. Burman |
source |
6 |
| SEUGI |
1990 |
The Analysis of Multiple Endpoints in Clinical Trials |
Lars Frison |
source |
8 |
| SEUGI |
1990 |
Using SAS/ACCESS Software with Controlled Access Multiple Oracle Instances on DEC VAX/VMS Systems |
Andy Richardson |
source |
13 |
| SUGI |
1990 |
A SAS Software-based System for Tracking Clinical Study Case Record Forms Utilizing Bar Codes |
Jules Bosch |
source |
6 |
| SUGI |
1990 |
Analyzing Balanced or Unbalanced Latin Squares and Other Repeated-Measures Designs for Carryover Effects Using the GLM Procedure |
D. A. Ratkowsky,
J. R. Alldredge,
J. W. Cotton |
source |
6 |
| SUGI |
1990 |
Constructing Integrated Clinical Information Systems for Traditional and Nontraditional Users |
Martin J. Rosenberg |
source |
6 |
| SUGI |
1990 |
Shortcuts to Customize Clinical Trial Reports |
Aileen L. Tsien |
source |
6 |
| SUGI |
1990 |
Using SAS Software to Develop a Clinical Studies Status System |
H. Jean Lieverman |
source |
6 |
| NESUG |
1989 |
Integrated Clinical Information Systems for Traditional and Non-traditional Users |
Martin J. Rosenberg |
|
8 |
| NESUG |
1989 |
Using PROC QPRINT to Create Lists and Tables |
George E. Demuth |
|
4 |
| SEUGI |
1989 |
Design And Implementation Of Clinical Data Management Applications On A PC Network |
Mark Crawford |
source |
12 |
| SEUGI |
1989 |
Graphic And Tabular Representation Of Individual Changes Of Laboratory Values In Clinical Trials |
Susanne Humpel |
source |
1 |
| SEUGI |
1989 |
PROC TABULATE, A Challenge |
Tove Kristoffersen |
source |
12 |
| SEUGI |
1989 |
SAS/AF Software In Clinical Data Applications |
Mark Crawford |
source |
26 |
| SUGI |
1989 |
A Data Management System for Remote Medical Studies Using the SAS System |
Timothy L. Cannon,
Gene O. Nelson,
Dwayne D. Oland,
David M. Warren |
source |
3 |
| SUGI |
1989 |
An Integrated Approach to Computer Systems for NDA Preparation and Presentation |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1989 |
Multivariate Models for the Analysis of Crossover Experiments |
Vernon M. Chinchilli,
Ronald K. Elswick |
source |
5 |
| SUGI |
1989 |
SAS Applications in the Health Care Industry |
William J. McDonald,
J. Jon Veloski |
source |
7 |
| SUGI |
1989 |
The SAS System on the UNIX Operating Systems and Derivatives: The Missing Link |
J. Philip Miller |
source |
5 |
| SUGI |
1989 |
The SAS System: An Aid in Caring for the Pregnant, Diabetic Patient |
Michael Berk,
Vicki S. Hertzberg,
Jane C. Khoury,
Philip R. Khoury,
Menachem Miodovnik |
source |
4 |
| SUGI |
1989 |
The TABSORT Procedure: A REXX and SAS System Application to Collate Statistical Tables |
Bruce Wentworth |
source |
6 |
| SUGI |
1989 |
Using SAS Software for the Analysis of Reliability and Lifetime Data |
Luis A. Escobar |
source |
9 |
| SEUGI |
1988 |
Automatic Analysis of Clinical Trials |
J. C. Peyrieux |
source |
6 |
| SUGI |
1988 |
An Integrated Clinical Data Management System at Allergan, Inc. |
Jeffrey S. Kouba |
source |
4 |
| SUGI |
1988 |
Data Entry in a Clinical Trial Using Windows in the SAS System for Personal Computers |
MaryAnne DePesquo Hope |
source |
4 |
| SUGI |
1988 |
Future Direction of Biomedical Information Systems in the Pharmaceutical Industry Based on the SAS System |
James F. Sattler |
source |
4 |
| SUGI |
1988 |
Integration of ORACLE and the SAS System in the Generation of Adverse Experience Reports |
Chih-Wu Chang,
Edward F.C. Pun |
source |
5 |
| SUGI |
1988 |
To Pool or Not to Pool in a Multicenter Clinical Trial |
Gregory T. Schwemer |
source |
4 |
| SUGI |
1988 |
Transferring a Mainframe Data-checking Application to the SAS System for Personal Computers: The Agony and the Ecstasy |
Dorothea Collins,
Joan Derrico |
source |
3 |
| SUGI |
1988 |
Use of the SAS System, CMS REXX, and ISPF to Generate Standardized Vital Signs Reports for Clinical Studies |
Rong Q. Pan |
source |
6 |
| SUGI |
1988 |
Using SAS Software to Simplify the Display and the Interpretation of Laboratory Data |
Kathleen H. Arthur |
source |
6 |
| SUGI |
1988 |
Using the SAS System to Facilitate Clinical Trials Research and NDA Approval |
Martin J. Rosenberg |
source |
7 |
| SEUGI |
1987 |
A General Application for the Optimisation of Data Analysis |
Gerhard Hugues |
source |
5 |
| SEUGI |
1987 |
A Statistical Look at Risk Factors for Coronary Heart Disease |
David J. Shannon |
source |
15 |
| SUGI |
1987 |
Graphic Display of Data in Clinical Trials |
Walter W. Owen Jr. |
source |
6 |
| SEUGI |
1986 |
The Use of SAS to Display, Plot and Summarise Blood Pressure Data from a Long Term Hypertension Clinical Trial |
David J. Shannon,
P.J.B. Berry |
source |
16 |
| SUGI |
1986 |
A SAS Based System for Calculating and Tracking Data Processing Error Rate Estimates |
Ellen Gilkerson,
Virginia Ozer |
source |
4 |
| SUGI |
1986 |
A Simplistic Approach to Tabulating and Summarizing Clinical Laboratory Data |
Carol A. Bogardus,
Les Pennelly |
source |
3 |
| SUGI |
1986 |
SAS Report Writing: Generation of Statistical Tables Using PROC PRINTTO and the DATA NULL_ Step |
Dorene M. Emmrich |
source |
5 |
| SUGI |
1986 |
Starting to Use Macros-Simple SAS Macro Applications |
Debra L. Bingham-Barnes |
source |
4 |
| SUGI |
1985 |
A Project Management System Written in SAS Software |
Andrew J. L. Cary,
Martin J. Rosenberg |
source |
6 |
| SUGI |
1985 |
A SAS-based LOG System for Keeping Track of Computerized Clinical Trial Data |
Ruth F. Quah |
source |
4 |
| SUGI |
1985 |
An Interactive, Menu-Driven SAS System for Sample Size and Power Computations in Clinical Trial Design |
Gregory G. Enas,
Walter W. Offen,
John D. Taulbee |
source |
6 |
| SUGI |
1985 |
Developing a Standardized SAS Software Library for Analysis of Numerous Large Scale Clinical Trials |
Debra L. Bingham-Barnes,
Betty J. Nelson,
David E. Tappe |
source |
6 |
| SUGI |
1985 |
SURVCOMP-SAS MACRO for Descriptive Survival Analysis |
Jeannette Y. Lee,
J. Michael White |
source |
8 |
| SUGI |
1985 |
The Use of SAS Software as a Data Base for Compiling Safety Data on New Pharmaceuticals |
David E. Tappe |
source |
5 |
| SUGI |
1984 |
A SAS Macro for Performing Repeated Significance Testing in Censored Survival Analyses |
Gordon W. Davis,
James F. Ward |
source |
6 |
| SUGI |
1984 |
Clinical Trial Management Using the SAS System |
Jeffrey S. Kouba,
Gary D. Novack |
source |
2 |
| SUGI |
1984 |
PROC GLM-Rearrangement of Output |
Karen L. Bourn |
source |
6 |
| SUGI |
1984 |
SAS Macros for Sample Size and Power Calculations |
Erik J. Bergstralh |
source |
6 |
| SUGI |
1984 |
SAS Programs for Reporting the Results of Bioequivalence Trials |
James T. Crowe Jr.,
Thaddeus J. Malicz |
source |
3 |
| SUGI |
1984 |
SEQURAN-An Interactive Sequential Randomization System for Clinical Trials |
Estelle M. Fondy,
Jeannette Y. Lee |
source |
6 |
| SUGI |
1984 |
Statistics Automation: Using SAS Macros to Produce Report-Ready Statistical Analysis Tables |
Walter W. Offen |
source |
5 |
| SUGI |
1984 |
THECIS-The Clinical Information System |
Judith A. Burns,
Leon T. Hairie,
Thomas R. Hoffman |
source |
6 |
| SUGI |
1983 |
A Multi-Evaluative Approach to the Analysis of Clinical Laboratory Data |
William A.T. Archambault Jr.,
James J. Tiede |
source |
6 |
| SUGI |
1983 |
A SAS Program for the Extended Mantel-Haenszel Procedure |
Alan C. Fisher,
Daniel M. Wildman |
source |
6 |
| SUGI |
1983 |
Adverse Reaction Incidence Tables for Clinical Trials |
Donna R. Park,
Stephen J. Ruberg |
source |
5 |
| SUGI |
1983 |
PASCAL Speaks to SAS: A Simple Interface |
David I. Hopp,
Robert W. Staley |
source |
6 |
| SUGI |
1983 |
The Use of Rank Analysis of Covariance in Analyzing Censored Survival Data |
Saeid B. Amini,
Peter A. Lachenbruch,
Robert F. Woolson |
source |
7 |
| SUGI |
1982 |
Data Management in Clinical Trials Using VM/SP, CMS, and SAS |
David I. Hopp,
Robert W. Staley |
source |
|
| SUGI |
1982 |
Interactive Graphics for Clinical Trials |
Judith A. Sromovsky |
source |
6 |
| SUGI |
1981 |
A SAS Routine for Modifying the Output of PROC CHART to Meet Special Report Requirements |
William M. Taylor |
source |
4 |
| SUGI |
1981 |
The Effect of Sample Size on the True Alpha Level with FUNCAT: A Simulation Study |
John L. Stedl |
source |
4 |
| SUGI |
1981 |
Using SAS to Manage A Large Clinical Trial Study |
William M. Taylor |
source |
|
| SUGI |
1980 |
SAS as a Clinical Registration System |
Frank J. Potter |
source |
4 |
| SUGI |
1980 |
Scientific Data Management and Analysis |
Steve Dassin,
John J. Frey,
George F. Griffin,
John McKenna |
source |
|
| SUGI |
1979 |
Application of Stepwise MANOVA and MANCOV Using SAS |
Chandu M. Patel |
source |
9 |
| SUGI |
1979 |
Statistical Applications of SAS at the 3M Company |
B. F. McDonagh |
source |
3 |
| SUGI |
1979 |
The Role of SAS in the Support of Clinical Studies in Medicine |
J. Philip Miller |
source |
6 |
| SUGI |
1978 |
SAS as a User Maintained Data Base System |
Frank J. Potter |
source |
5 |
HOME
QUICK SEARCH
AUTHORS
KEYWORDS
HELP
BUGS