| WUSS |
2026 |
A Flexible Metadata-Driven and Modular Approach to SDTM Automation [presentation] |
Ruili Shi,
Jiaying Zhang,
Charles Chen |
source |
15 |
| WUSS |
2026 |
Automating SDTM Subject Visits (SV) Derivation A Configuration-Driven, Meta-Programming Approach in SAS [presentation] |
Huiqing Chen |
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 |
| WUSS |
2026 |
The Agent That Asks the Questions: Autonomous Hypothesis Generation Over CDISC Trial Data with SAS |
Mehdi Hajmollaahmad Naraghi,
Lida Gharibvand |
source |
14 |
| PharmaSUG CN |
2026 |
A Desktop Application for Automating PDT Management, SAS Execution, and Report Assembly |
Mingjie Fu |
source |
5 |
| PharmaSUG CN |
2026 |
A Dual-Harness Workflow to Wrap AI into Observable, Reusable Clinical Table Delivery: From SAP Intent to Shell-Aligned Execution |
Wenjun Zhu |
source |
14 |
| PharmaSUG CN |
2026 |
A Practical Framework for Applying Generative AI in Clinical SAS Programming: A Human-in-the-Loop Approach for Chinese Clinical Studies |
Siyu Yu |
source |
12 |
| 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 |
A Traceable and Reproducible Framework for Oncology Efficacy Data Review Using IMWG Criteria: A BCMA Case Study |
Yun Jiang,
Yingying Deng,
Manman Lu,
Longhui Li |
source |
6 |
| PharmaSUG CN |
2026 |
ADICE: A Proposed ADaM Dataset Structure for Intercurrent Events in the Estimand Framework |
Lijie Zhu |
source |
11 |
| PharmaSUG CN |
2026 |
AI-Augmented SDTM Workflow: A Methodological Framework |
Yuqi Chen,
Muqu Lv,
Zhuozhao Zhan |
source |
16 |
| 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 Interactive Shiny Application for Streamlined ADaM Specification Integration and Compliant Define-XML v2.1 Generation |
Dongxu Liu |
source |
11 |
| 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 |
Automated Clinical Text Classification with Robust Machine Learning for Pharmaceutical Data Curation |
Weineng Zhou |
source |
11 |
| PharmaSUG CN |
2026 |
Automating ADaM Specification with AI: Intelligent Generation, Risk Assessment, and Human-in-the-Loop Review |
Shuang Gao,
Yaohui Zhu,
Tingting Zeng,
Jinling Li,
Wei Wang |
source |
11 |
| PharmaSUG CN |
2026 |
Automating SDTM Programming with a Human-in-the-Loop Multi-Agent System |
Wenqiang Chu |
source |
7 |
| PharmaSUG CN |
2026 |
Clarity: An AI-Powered Shiny Application for Natural Language-Driven Clinical Data Analysis |
Jinzhi Zhou,
Yusi Liu,
Dan Su,
Jie Liu |
source |
14 |
| PharmaSUG CN |
2026 |
CodeGenius 2026: Connecting Enterprise Metadata, Standards, Interactive Execution, and AI Coding Agents for Statistical Programming |
Jing Wang,
Yaohui Zhu,
Xuejie Zhou,
Jinling Li,
You Li |
source |
8 |
| PharmaSUG CN |
2026 |
Designing an ADaM Dataset for Streamlined Drug-Induced Liver Injury Screening Analyses |
Ben Gao,
Danfeng Fu,
Guowei Wu |
source |
16 |
| 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 |
DQO: A Rule Engineering and AI-Driven Platform for Assessing Source Data Quality from SDTM Perspective |
Nana Yang,
Huan Song,
Zhouhao Pan,
Chunpeng CZ Zhao |
source |
11 |
| PharmaSUG CN |
2026 |
DualBookmarker: A Python Tool to Create Dual Bookmarks for Annotated CRF |
Xianhua Zeng |
source |
4 |
| PharmaSUG CN |
2026 |
Efficient Strategies for Handling Data Issues in Clinical Trial Submissions |
Kate Sun |
source |
7 |
| 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 |
From Spreadsheets to Smart Platforms: A Framework for Modernizing SDTM Specification Management Using the Microsoft 365 Ecosystem |
Shuting Lou |
source |
14 |
| PharmaSUG CN |
2026 |
Making Composite Endpoints Work: An ADaM Programming Approach to Sustained Remission |
Qing Xue,
Fen Wu,
Shuo Zhang,
Peixuan Wang |
source |
15 |
| 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 |
Safety Estimands and Analysis Dataset Design: Advancing Safety Evaluation in Clinical Trials |
Kun Ren,
Zeyu Guang |
source |
11 |
| PharmaSUG CN |
2026 |
ShellPainter & CDARS: An AI-Powered Digital Framework for Integrated shell-TFL Automation |
Jiapeng He,
Mingliang Fan,
Yanan Sui,
Lin Jiang,
Mingfeng Zhou,
Xuejie Zhou |
source |
7 |
| PharmaSUG CN |
2026 |
Trace Data Framework for Metadata Network, Impact Analysis, and Visualization Across RAW, SDTM, ADaM, and TFL |
Nana Yang,
Tingting Zeng,
Yaohui Zhu,
Yanan Sui,
Mingliang Fan |
source |
7 |
| PharmaSUG CN |
2026 |
When Data Capture Becomes Data: How ePRO and e-Diary Systems Reshape CDISC Standards, Statistical Programming, and Endpoint Analysis in Vaccine Studies |
Jialiang Liu,
Lin Chen |
source |
16 |
| PharmaSUG |
2026 |
%Compare_counts: A Macro for Speeding Up the QC Process When Proc Compare Slows it Down |
Michael Garside |
source |
6 |
| PharmaSUG |
2026 |
A Human-in-the-Loop AI-Assisted Framework for ADaM Standardization |
Chunqiu Xia,
Feiyang Du |
source |
12 |
| PharmaSUG |
2026 |
A specification-driven approach to improve the reliability of AI-generated SDTM transformation programs |
Rostislav Markov |
source |
6 |
| PharmaSUG |
2026 |
Accelerating CDISC SEND Conversion with AI: From Raw Preclinical Data to Regulatory-Ready Datasets |
Nattawit Pewngam,
Chotika Chatgasem,
Titipat Achakulvisut |
source |
10 |
| PharmaSUG |
2026 |
aCRF In Full: A Complete Solution for Relatively Little Work |
Carlo Radovsky |
source |
4 |
| 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 |
AI-Augmented SDTM Review: A Practical Framework Enhanced by a Structured Prompt Library |
Vihar Patel |
source |
10 |
| PharmaSUG |
2026 |
AI-Driven Intelligent Platforms for ADaM Specification and Code: Empowering Clinical Data Analysis |
Tingting Zeng,
Jia He,
Yaohui Zhu,
Shuang Gao,
Jinling Li,
Nana Yang |
source |
11 |
| PharmaSUG |
2026 |
AI-First Leadership in Biometrics: Redefining Strategy, Teams and Execution in the Agentic AI Era |
Kevin Lee |
source |
7 |
| PharmaSUG |
2026 |
AI-Powered Multiple-Agent Pipeline for Automating ADaM Dataset Generation |
Lucas Liu,
Bo Ci |
source |
5 |
| PharmaSUG |
2026 |
An Alternative Option to Create XPT Files with a SAS Function |
Jose Hernandez Rivero,
Ruth Marisol Rivera Barragan |
source |
5 |
| PharmaSUG |
2026 |
An Approach for Generating Tumor Biopsy Datasets for Drug Development |
Ryan Hernandez-Cancela,
Jeff Cheng,
Sandeep Meesala |
source |
10 |
| 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 |
Analysis Concepts role within the CDISC 360i vision |
Alyssa M. Wittle,
Brian Harris |
source |
5 |
| PharmaSUG |
2026 |
Approaches Integrating SAS LSAF and Pinnacle 21 Enterprise for SDTM/ADaM Dataset Validation |
James Zhao,
Joshua Lin |
source |
8 |
| 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 |
Automating Bioresearch Monitoring (BIMO) Listings Using R |
Weishan Song,
Wanting Jin,
Weiyu Zhou,
Margaret Huang |
source |
15 |
| 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 |
Case Study: Integrating ADPPK CDISC Standards into Pharmacometric Programming and Analysis Workflows |
Praseeda Rajan,
Renuka Hegde,
Erin Dombrowsky,
Neelima Thanneer,
Yue Zhao |
source |
6 |
| PharmaSUG |
2026 |
Closing the Expectation Gap: A Leadership Framework for Clinical Programming Success |
Yuka Tanaka-Chambers |
source |
14 |
| 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 |
Data Without Borders: CDISC Data Hub for Multi-Language Clinical Analytics & AI |
Mayank Singh |
source |
11 |
| PharmaSUG |
2026 |
DefinePageChecker: A Python Tool for Verifying Page Number Hyperlinks in Define.xml |
Xianhua Zeng |
source |
4 |
| PharmaSUG |
2026 |
Do One Task, Get Another Done for Free: Use DEFX Tags in Comments to Fill Out Your define.xml |
Brendan Bartley,
Megan Hinger |
source |
21 |
| 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 Patient Profile Plot Development with SAS Graph Template Language |
Raghava Pamulapati,
Guowei Wu,
Danfeng Fu |
source |
13 |
| PharmaSUG |
2026 |
Early Restricted Unblinded PK Data Access (ERUPA): Framework to Accelerate PopPK and ERES Deliverables Through Data-Centric, Firewalled Workflows |
Dheeraj Rupani,
Srinivas Bachina,
Kiran Kumar Kode |
source |
7 |
| PharmaSUG |
2026 |
Early Unblinding to Pharmacometrics (PMx) Data: Challenges, Practices, and Benefits |
Shweta Vadhavkar,
Jing Su |
source |
6 |
| PharmaSUG |
2026 |
Enhancing ADaM PK Datasets to Automate PK TFLs Generation |
Jianli Ping,
Karthik Sankepelli |
source |
12 |
| 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 |
Following Your Footsteps: Maintaining Traceability in ADaM Datasets [presentation] |
Nancy Brucken,
Karl Miller |
source |
59 |
| PharmaSUG |
2026 |
Friction to Flow: LLM-Based Automation of Clinical Data Workflows |
Pankaj Attri,
Matthew J. Becker |
source |
8 |
| PharmaSUG |
2026 |
From Chaos to Clarity: A Programmer-s Perspective on Standardizing Population Pharmacokinetic (PopPK) Data for Regulatory Success |
Naveen Muppalla,
Shibani Harite |
source |
7 |
| PharmaSUG |
2026 |
From Data Flood to Insight: Efficient SDTM Validation for High-Frequency Sources |
Seiko Yamazaki |
source |
6 |
| 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 SAP to CSR: A Metadata-Driven TFL Workflow |
Bhavin Busa |
source |
7 |
| PharmaSUG |
2026 |
From SAS Servers to AI Agentic SCEs: Integrating Agentic AI into GxP-Compliant Biometrics Workflows |
Kevin Lee |
source |
5 |
| PharmaSUG |
2026 |
From Specification to SDTM at Speed: Deploying the SDTM Engine in Production |
Lynn Xiuling Zhang,
Jacques Lanoue,
Ulf Nielsen |
source |
11 |
| PharmaSUG |
2026 |
From Static to Dynamic: Leveraging R Shiny for Tumor Response Data Review |
Reneta Hermiz,
Jing Ji,
Amrit Pradhan,
Martin Sandel |
source |
10 |
| 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 |
Has your SAS being 'MEAN' to your data yet? |
Ruth Marisol Rivera Barragan,
Isaac Vazquez |
source |
8 |
| PharmaSUG |
2026 |
Hero-in-the-Loop: A Super Squad Approach to SDTM Creation & Validation |
Julie Ann Hood |
source |
7 |
| PharmaSUG |
2026 |
Human Beings Still Needed: Manual ADaM Checks that AI Can-t Do |
Sandra Minjoe,
Mario Widel |
source |
9 |
| PharmaSUG |
2026 |
Improving Risk-Based QA in Outsourced Studies Using Cross-Domain ADaM Derivation Comparisons |
Pallavi Sadhab |
source |
10 |
| PharmaSUG |
2026 |
Investigator-Initiated Trials: Navigating Statistical Programming Challenges with Practical Solutions |
Vikas Patil,
Ramesh Sundaram |
source |
6 |
| PharmaSUG |
2026 |
It-s a Wonderful Lifecycle: Translating Statistical Programming into Modern Analytics Development |
Steve Nicholas |
source |
3 |
| PharmaSUG |
2026 |
Lessons to Guardrails: Operationalizing Early Checks for FDA Submission Readiness |
Jeff Xia |
source |
6 |
| PharmaSUG |
2026 |
Navigating Early Career Challenges in PK/ADA Statistical Programming |
Diyu Yang,
Sandeep Meesala |
source |
11 |
| PharmaSUG |
2026 |
Oncology Solid Tumor Subcutaneous vs Intravenous Late-stage Study Analysis |
Sumanjali Mangalarapu,
Chuqing Chen,
Anilkumar Anksapur |
source |
11 |
| PharmaSUG |
2026 |
One Study, Many Regulators: Submission-Ready Data Package for Multi-Region Filings |
Himanshu Patel,
Chintan Pandya |
source |
10 |
| PharmaSUG |
2026 |
Operationalizing Real World Data for External Control Arms: An End to End Framework for Rare Disease and Oncology Trials |
Anbu Damodaran |
source |
7 |
| 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 |
Picking Up the Pieces: Implementation of (the forgotten) ADaM Naming Fragments |
Richann J. Watson,
Karl Miller |
source |
7 |
| PharmaSUG |
2026 |
Post-DBL Programming Update Tracker: Automating Revision Capture to Strengthen Audit Readiness, Oversight, and Compliance Across Programs and ADaM Specifications |
Yunyi Jiang,
Christine S Teng |
source |
8 |
| PharmaSUG |
2026 |
Practical Lessons in AI-Assisted Metadata Conversion: From Database Specs to EDC and SDTM - Successes, Pitfalls, and Practical Implementation |
Jianlin Li,
Andy Shen |
source |
11 |
| PharmaSUG |
2026 |
Programming Challenges in Developing PRO Analysis Datasets Under FDA's New Submission Guidance |
Weiwei Guo,
Caizhi Huang |
source |
10 |
| 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 |
Real World Data and CDISC - An Evolving Journey |
Shuo Cao,
Venkat Rajagopal |
source |
4 |
| PharmaSUG |
2026 |
SAS and R for Expanding Data for Pharmacometrics Analysis (PMx) Analysis Data Sets |
Jeffrey Rathbun,
Rebecca Humphrey |
source |
8 |
| PharmaSUG |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source |
12 |
| PharmaSUG |
2026 |
SUPP to NSV: Transforming Data Representation for Improved Reviewer Utility |
Soumya Rajesh |
source |
10 |
| 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 |
TOON Format: A Token-Efficient Data Exchange Solution for AI-Enhanced Clinical Programming |
Saikrishnareddy Yengannagari |
source |
4 |
| PharmaSUG |
2026 |
Traceability in Real World trials - just an aERD away. |
Ashwini Yermal Shanbhogue |
source |
7 |
| PharmaSUG |
2026 |
Trust but Verify: How ChatGPT and SAS Can Be Comrades! |
Steven C. Black |
source |
3 |
| PharmaSUG |
2026 |
Two Paths, One PK Journey: The Art of Balancing ADPC and ADNCA |
Ashok Abburi,
Rakhe Jacob,
Shibani Harite |
source |
7 |
| PharmaSUG |
2026 |
User-defined Functions for Programming Population PK and PKPD Datasets |
Zhongqing He,
Man Li,
Hong Yan |
source |
7 |
| PharmaSUG |
2026 |
Virtual Data, Real Standards: Leveraging Data Simulation for Smarter Clinical Trials |
Sangeeta Shabadi,
Nitesh Patil,
Jonathan Henshaw |
source |
16 |
| PharmaSUG |
2026 |
Why Standards Matter More Than Code in the Age of GenAI |
Bhavin Busa |
source |
6 |
| 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 |
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 |
AI + Metadata : An Agentic Approach to Standards-Based Automation |
Kevin Burges |
source
presentation source |
10 |
| PHUSE US |
2026 |
AI Code Generator: Automating TFL Programming with ARS Metadata |
Bhavin Busa,
Navin Dedhia |
source
presentation source |
5 |
| PHUSE US |
2026 |
AI-Optimised AESI Flagging: Streamlined SAS Hash Table Logic with Dynamic CALL EXECUTE and Metadata-Driven Specifications |
Hang Zhong,
Rashad Rasul,
Jiaqi Hu |
source
presentation source |
12 |
| PHUSE US |
2026 |
AI-Powered Multiple-Agent Pipeline for Automating ADaM Dataset Generation |
Bo Ci |
source
presentation source |
4 |
| PHUSE US |
2026 |
Analysis Concepts Definition: Initial Perspectives from the CDISC Working Group |
Stuart Malcolm |
source
presentation source |
4 |
| 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 |
AUTOCODE: Metadata-Driven Automation for Faster, Traceable SDTM and ADaM Programming |
Matthew Finnemeyer |
source
presentation source |
6 |
| PHUSE US |
2026 |
Automated Code Generation: Evaluating Deterministic and Probabilistic Approaches |
Malan Bosman |
source
presentation source |
6 |
| 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 |
AutoProgramming: Agents Are All Y ou Need |
Chengxin Li |
source
presentation source |
11 |
| PHUSE US |
2026 |
Beyond Box-Checking: Five Best Practices for Embedding QC in Modern SCEs |
Chris McSpiritt |
source
presentation source |
6 |
| PHUSE US |
2026 |
Beyond the Hype: Practical Guidance for LLM Adoption in Statistical Programming |
Michael Goedde |
source
presentation source |
9 |
| PHUSE US |
2026 |
Breaking Free from the xpt: Exploration of Dataset-JSON as an Alternative Transport File to Regulatory Agencies |
Benjamin Straub,
Samir Parmar |
source
presentation source |
8 |
| PHUSE US |
2026 |
Building Cross-Functional Regulatory and Programming Alignment for Successful Submissions |
Ben Kaspar,
Stephine Keeton |
source
presentation source |
6 |
| 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 |
Case Study: Leveraging CDISC CORE for Proactive SDTM Compliance and Submission Readiness |
Shivani Gupta |
source
presentation source |
6 |
| PHUSE US |
2026 |
CDISC 360i Demo: Automating from Study Design to Submission |
Darren Moreland |
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 |
CDISC ARS Template Code: Gearing Up with Automation in TFL Programming |
Malan Bosman,
Anna Yaggi |
source
presentation source |
7 |
| PHUSE US |
2026 |
CDISC Biomedical Concepts for Breast Cancer: A CDISC 360i Perspective |
Bess LeRoy,
Brian Harris |
source
presentation source |
2 |
| PHUSE US |
2026 |
Challenges and Solutions for Generating Synthetic CDISC Data |
Sundaresh Sankaran,
Catherine Briggs |
source
presentation source |
6 |
| PHUSE US |
2026 |
CLIQ: An AI-Native Framework for Unified Clinical Trial Data Quality Assurance |
Gopinath Viswanathan |
source
presentation source |
5 |
| PHUSE US |
2026 |
Common Issues in BIMO Clinical Site Dataset Packages |
Michael Beers |
source
presentation source |
7 |
| 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 Harmonisation for ISS and ISE: A Practical Checklist for Integration Success |
Qiong Wei,
Lily Cheng |
source
presentation source |
10 |
| PHUSE US |
2026 |
Democratising SDTM Transformations: AI-Assisted Function Development with Business-Driven Governance |
Ulf Nielsen,
Rostislav Markov |
source
presentation source |
11 |
| PHUSE US |
2026 |
Demonstrations of AutoTable |
Chengxin Li |
source
presentation source |
11 |
| PHUSE US |
2026 |
Deriving Phantom Records in BDS Datasets To Support the FDA's Standard Safety Figures for Missing Data Analysis |
Guowei Wu,
Ruchitbhai Patel |
source
presentation source |
6 |
| 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 |
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 |
Enabling Innovation: Lessons from the CDISC AI Innovation Challenge |
Julie Smiley |
source
presentation source |
10 |
| PHUSE US |
2026 |
End-to-End Workflow for CDISC Estimand Framework in Clinical Trials |
Hiral Raval,
Simon Luo |
source
poster source |
12 |
| PHUSE US |
2026 |
Enhancing Clinical Study Processes Through AI-Driven Documentation Automation |
Pinku Hooda |
source
presentation source |
3 |
| 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 |
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 Black Box to Glass Box: A Context-Aware Approach to SDTM Mapping Automation with Interactive Visual Validation |
Rostislav Markov,
Jacques Lanoue |
source
presentation source |
12 |
| 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 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 |
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 |
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 LLM-Augmented Automation for ADaM Dataset Generation |
Anil Mogha,
Ghourav Garg |
source
presentation source |
9 |
| PHUSE US |
2026 |
Incorporating Digital Health Technology (DHT) Data in SDTM - Challenges and Examples |
Swarupa Sudini,
Sandra VanPelt Nguyen |
source
poster source |
7 |
| PHUSE US |
2026 |
Interactive and Instant: GenAI-Driven Creation of Clinical Trial Applications |
Marcin Dubel |
source
presentation source |
12 |
| PHUSE US |
2026 |
Interactive Patient Profiles in R Shiny: Enhancing Narrative Review in Clinical Studies |
Danny Hsu,
Tzu-Chien Chuang |
source
poster source |
4 |
| PHUSE US |
2026 |
Introduction of PharmaForest - Forest of SAS packages |
Ryo Nakaya,
Hiroki Yamanobe,
Yutaka Morioka |
source
presentation source |
7 |
| 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 |
LLM-Powered Clinical Data Flow with Traceability - From Siloed Pipelines to a Semantic Fabric |
Pankaj Attri,
Matthew J. Becker |
source
presentation source |
8 |
| 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 |
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 |
Not Another Other: Bridging Data Collection with SDTM Mapping Without Open Text Fields |
Aminta Jimenez |
source
presentation source |
6 |
| PHUSE US |
2026 |
One eye open, one eye closed: How to approach masking in open-label oncology study |
Abhay Kumar |
source
presentation source |
8 |
| PHUSE US |
2026 |
Open Source as a Strategic Enabler for EMA Submissions: An R Shiny Approach |
Marckenley Mercie |
source
presentation source |
5 |
| PHUSE US |
2026 |
Open Source Pavilion: Metadata-driven Automation Interactive [presentation] |
Orla Doyle,
Rammprasad Ganapathy |
source |
28 |
| 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 Efficiency: Symphony and Composer in Clinical Reporting |
Margaret Wishart,
Karma Tarap |
source
presentation source |
6 |
| PHUSE US |
2026 |
QC Without Code: ChatGPT Enterprise for Sponsor Oversight of Outsourced TFLs |
Jenny Price,
Brad Moore |
source
presentation source |
9 |
| 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-World Evidence Pavilion: Interactive Workshop: Bridging Estimands & Target Trial Emulation [presentation] |
Lauren Dang,
Matt Baldwin |
source |
6 |
| PHUSE US |
2026 |
Reimagining SDTM Mapping with Agentic AI and Automation |
Nathan Johnson |
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 |
Rule-Based Auto-SDTM Mapping Software in Python, Which Automatically Generates Executable SAS or R Programs |
Carrie Zhang,
Bill Zhang |
source
presentation source |
9 |
| 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 |
SDTM Navigator: An Agent-Based LLM Framework for Automated Specification and Programming |
Benzi Alex Mathew |
source
presentation source |
3 |
| PHUSE US |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source
presentation source |
10 |
| PHUSE US |
2026 |
Semi-automating Case Report Form Annotations Using Python and a Metadata Repository |
Alvin Mathew |
source
presentation source |
8 |
| PHUSE US |
2026 |
SpecToSAS: AI-Powered SAS Code Generation from Study Specs |
Gargee Vaidya,
Lluis Gimenez |
source
presentation source |
12 |
| PHUSE US |
2026 |
Standardising Exposure-Response Data for Modelling and Simulation Using CDISC Principles and {admiral} |
Jeffrey Dickinson |
source
presentation source |
12 |
| PHUSE US |
2026 |
Statistical Programming Methods for Evaluating the Impact of Immunogenicity on Safety and Efficacy Outcomes |
Dinesh Putluri,
Rakesh Padigala |
source
presentation source |
10 |
| PHUSE US |
2026 |
Submitting eCRT SDTM Data for ISS |
Aida Swierk |
source
presentation source |
10 |
| 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 |
The AI Reckoning: Why Statistical Programmers Must Evolve Now |
Bhavin Busa |
source
presentation source |
6 |
| PHUSE US |
2026 |
The Curious Case of External Controlled Arms (ECAs): Practical Solutions for External and RWD Integration |
Manish Deole,
Preethi Samala |
source
presentation source |
6 |
| PHUSE US |
2026 |
Time to Roclet! admiral's use of custom roclets to enhance and extend examples in function documentation |
Benjamin Straub |
source
presentation source |
9 |
| 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 |
Utilizing AI for Automated Conversion of ADaM Specifications to R Code |
Alice Ehmann,
Kjersten Offenbecker |
source
presentation source |
9 |
| PHUSE US |
2026 |
Validating AI in GxP: Test Harnesses, Guardrails and Compliance Controls |
Bill Qubeck |
source
presentation source |
14 |
| PHUSE US |
2026 |
Visualising Essential Metrics for Assessing Disease Dynamics in Hematologic Oncology Trials: A SAS Graphic Approach |
Jiashan Li |
source
presentation source |
8 |
| PHUSE US |
2026 |
What Pharma Can Learn from Data Science Outside the Industry |
Kris Wenzel,
Liz Cole |
source
presentation source |
11 |
| PHUSE EU |
2025 |
A Git-Driven Automated Workflow for Efficient ADaM and TFL Validation and Quality Control Documentation |
Xavier Chenede,
Paulin Charliquart |
source
presentation source |
8 |
| PHUSE EU |
2025 |
ADaM Conformance Rules: Bridging the Gap Between Standards and Practice |
Rafik Ghazaryan |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Advancing Automated Non-Compartmental Analysis with R Shiny |
Jana Spinner,
Gerardo Rodriguez |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Automated QC Framework for Reliable ADNCA Dataset Generation with {admiral} |
Valentin Legras,
Lucy Aspridis |
source
presentation source |
4 |
| PHUSE EU |
2025 |
Bridging the Gap: Translating Intercurrent Events into Analysis-Ready ADaM Datasets |
Meghna Diedrich |
source
poster source |
9 |
| PHUSE EU |
2025 |
But Wait, There's More: When RECIST 1.1 Is Not Enough |
Anny Yamileth Olivares Mundo |
source
poster source |
8 |
| PHUSE EU |
2025 |
CDISCDataset.com: An AI-Powered Platform for Generating Synthetic CDISC-Compliant SDTM and ADaM Datasets, CRFs, Protocols, TFL Shells, and Specs |
Ara Baghumyan |
source
presentation source |
2 |
| PHUSE EU |
2025 |
Close Encounters with Real-World Data |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
21 |
| PHUSE EU |
2025 |
Digital SAP Model Using Biomedical Concepts |
Tom Ratford |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Efficient Conversion of SDTM/ADaM Specifications from Excel to Define-XML v2.1 Using Pinnacle 21 Community |
Hiromi Okada,
Seiko Yamazaki |
source
presentation source |
15 |
| PHUSE EU |
2025 |
End-to-End R: Where To Start? |
Luke Thompson |
source
presentation source |
6 |
| 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 |
Framework for Integrating Omics Data with Other Clinical and NonClinical Data Sources |
Mehdi Harek,
Jonathon Keeney |
source
presentation source |
12 |
| 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 SDTM to a Graph-Based, Multi-Purpose Interface for Data |
Eva Kelty,
Catharina Dahlbo |
source
presentation source |
4 |
| PHUSE EU |
2025 |
From Static Archives to Analytical Intelligence: Transforming Statistical Analysis Value Through Standardization |
Ilan Carmeli |
source
presentation source |
8 |
| PHUSE EU |
2025 |
From XPT to Dataset-JSON: Enabling Real-Time Validation and Streamlined Submissions |
Hugo Signol,
Sebastià Barceló |
source
presentation source |
8 |
| PHUSE EU |
2025 |
How to map lab data into the LB domain and ADLB |
Bert Parmet |
source
poster source |
6 |
| PHUSE EU |
2025 |
IDD'AI: Automating the Tedious So You Can Focus on the Genius |
Lionel Debecq,
Samantha Cambier |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Implementing ADNCA in the PK Process: A Cross-Departmental Approach |
Daphne Vuurstaek,
Frédéric Saad |
source
poster source |
4 |
| 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 |
Launching CDISC CORE v1.0: A New Standard for Automated Study Conformance [presentation] |
Tomás Sabat Stofsel,
Nick De Donder |
source |
44 |
| 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 |
Micro-Decisions, Macro Impact: The Role of Agile Thinking in Every Line of Code |
Eswara Satyanarayana Gunisetti |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Mind the Gap: Imputing Missing Dosing Times in QD & BID Regimens Using ADPPK Guidelines |
Aschwin van der Giesen,
Gerly van der Vleuten |
source
presentation source |
8 |
| 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 |
Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation |
Dmytro Kalinin |
source
presentation source |
13 |
| PHUSE EU |
2025 |
No Patients? No Problem Define Your Study Data with Python at the CORE |
John McDade |
source
presentation source |
11 |
| 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 |
Pooling Studies Through Code Traceability |
Hamdi Chouikha,
Kornelius Neufeld |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Qualitative ADaM Datasets and Define-XML Without Using ADaM Specs |
Pieter Coppens |
source
presentation 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 |
ResponDEX - Response Data Exploration Dashboard |
Sevak Kamalyan |
source |
9 |
| PHUSE EU |
2025 |
Robust Programming Strategies for Exposure to ADaM Datasets |
Susann Grill |
source
poster source |
13 |
| 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 |
Status and Updates of OpenStudyBuilder [poster] |
Mikkel Traun |
source |
1 |
| PHUSE EU |
2025 |
The Art of Timely Deliverables: How We Learned To Stop Worrying and Love the Deadline |
Søren Fjelstrup |
source
presentation source |
12 |
| PHUSE EU |
2025 |
The Chicken, the Egg and the ADaM: Cracking the PRE-ADSL vs ADSL Sequence |
Carla Santillán,
Dubravka Georgijevic |
source
presentation source |
8 |
| 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 |
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 |
Untangling the Dependencies Web |
Rhys McCrosson |
source
presentation source |
12 |
| 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 |
Why I can't see myself coding that much anymore |
Angelo Wibbeler |
source
presentation source |
11 |
| 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 |
Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
source |
15 |
| MWSUG |
2025 |
Last Observation Carried Forward (LOCF) in Longitudinal Clinical Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler |
Troy Martin Hughes |
source |
9 |
| 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 |
| MWSUG |
2025 |
Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates |
Richann J. Watson |
source |
19 |
| SESUG |
2025 |
CDISC Genius AI: PoC on how to interact with CDISC Library API using Natural language |
Saikrishnareddy Yengannagari |
|
9 |
| SESUG |
2025 |
Enhance flexibility and variability by utilizing an Intermediate Dataset when developing the ADaM Efficacy Dataset in Vaccine Studies |
Edward Boykis |
|
6 |
| 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 |
Ensure complete raw data to SDTM mapping: a SAS macro approach for quality control |
Cally Davidson,
Eric Howard |
|
8 |
| SESUG |
2025 |
Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
|
15 |
| SESUG |
2025 |
Obtaining Metadata Information on Data Transfers for Dataset Profiling |
Amy Zhang |
|
7 |
| SESUG |
2025 |
SAS and R in Action: Comparison of XPT File Creation |
Chen Ling |
|
7 |
| SESUG |
2025 |
Title: Optimizing Clinical Research Efficiency through SDTM Dataset Splitting Using SAS: Insights from New SDTM Programmers |
Tiffany Bainter,
Maddie Hays |
|
5 |
| SESUG |
2025 |
Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates |
Richann J. Watson |
|
19 |
| 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 |
Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
source |
15 |
| 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 |
| WUSS |
2025 |
Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates |
Richann J. Watson |
source |
19 |
| PharmaSUG |
2025 |
A codelist generator for define.xml using a SAS Studio macro and RStudio function |
Valerie Cadorett |
source |
7 |
| PharmaSUG |
2025 |
A collaborative and agile approach for end to end Standards Governance and Release |
Kairav Tarmaster,
Pratiksha Wani |
source |
10 |
| PharmaSUG |
2025 |
A Customizable Framework in R for Presenting BICR Data in a User-Friendly Format |
Reneta Hermiz,
Jing Ji |
source |
14 |
| PharmaSUG |
2025 |
A discussion of the new ADaM guidance (ADNCA and ADPPK) for pharmacokinetics. |
Luke Reinbolt |
source |
3 |
| PharmaSUG |
2025 |
A Little Bit of This and That: Use cases, implementation, and documentation when using multiple CDISC standards, CTs, and regulatory guidances in an SDTM study |
Charity Quick |
source |
14 |
| PharmaSUG |
2025 |
A Method to Add Additional Necessary Datasets to Existing Define.XML |
Jeff Xia,
Sandeep Meesala |
source |
5 |
| PharmaSUG |
2025 |
ADaM and TFLs for Drug-induced Liver Injury (DILI) Analysis |
Song Liu,
Rambabu Sura |
source |
7 |
| PharmaSUG |
2025 |
ADaM Fundamental Principles vs. Rules: Which to Follow, When, and Why? |
Sandra Minjoe,
Mario Widel |
source |
6 |
| PharmaSUG |
2025 |
ADaM implementation for Anti-drug Antibody Data |
Jiannan Kang,
Luke Reinbolt |
source |
19 |
| PharmaSUG |
2025 |
ADaM Pet Peeves: Things Programmers Do That Make Us Crazy |
Sandra Minjoe,
Nancy Brucken |
source |
13 |
| 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 Search LOG |
Zhuo Chen,
Martha Cao,
Ted Lystig,
Sateesh Arjula |
source |
8 |
| PharmaSUG |
2025 |
Approaches to Developing Multiple Imputation ADaM Datasets |
Kang Xie |
source |
8 |
| PharmaSUG |
2025 |
Automating Define-XML Updates: A SAS-Based Framework for Submission Readiness |
Qiong Wei,
Lixin Gao |
source |
10 |
| 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 |
BDS Dataset with PARQUAL and PARQTYP Variables for Time-to-Safety Events Analysis |
Kang Xie |
source |
9 |
| PharmaSUG |
2025 |
Better, Faster, Stronger: A Case Study in Updating SAS Macro Code with Run-time Optimization in Mind |
Valerie Finnemeyer |
source |
10 |
| PharmaSUG |
2025 |
Bridging the Gap: Leadership of Statistical Programmers in Clinical Trials |
Allison Covucci,
Xiaohan Zou |
source |
6 |
| PharmaSUG |
2025 |
Change the way you think of Codelist - Optimize managing Organization Controlled Terminology with a meta-model and its features to manage Codelist in MDR |
Kairav Tarmaster |
source |
11 |
| PharmaSUG |
2025 |
Checking Outside the Box: A Framework for Submission Success |
Julie Ann Hood,
Seiko Yamazaki |
source |
13 |
| 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 |
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 |
Controlling attributes of .xpt files generated by R |
Yachen Wang,
Chen Ling |
source |
13 |
| PharmaSUG |
2025 |
Creating JSON Transport Data for Regulatory Life Sciences |
Mary Dolegowski,
Matthew J. Becker |
source |
6 |
| 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 |
Deciphering Exposure-Response Analysis Datasets: A Programmer-s Perspective for Oncology Studies |
Sabarinath Sundaram |
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 |
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 CDISC Controlled Terminology Mapping: An R-Based Automation Solution |
Yunsheng Wang |
source |
8 |
| PharmaSUG |
2025 |
Elevating Clinical Research: Strategic Implementation of CDASH and SDTM Standards |
Hayden Patel |
source |
4 |
| PharmaSUG |
2025 |
Embracing an Extra Step as the Ultimate Shortcut: Leveraging ADDATES for Enhanced Efficiency and Traceability in Oncology Studies |
Chia-Lu Lee,
Wanchian Chen,
Anna Chen |
source |
6 |
| PharmaSUG |
2025 |
Enhancing Dictionary Management and Automation with NCI EVS: A Deeper Dive for the CDISC Community |
Anthony Chow |
source |
6 |
| PharmaSUG |
2025 |
Ensuring Data Integrity: Techniques for Validating SDTM Datasets in Clinical Research |
Amy Welsh |
source |
8 |
| PharmaSUG |
2025 |
Evaluation of the Process to Create CLINSITE define.xml: Macro Approach vs. ADCLIN Spec |
Yizhuo Zhong,
Yunyi Jiang,
Christine S Teng |
source |
8 |
| 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 |
Getting under the "umbrella" of Specimen-based Findings Domains! |
Soumya Rajesh,
Kapila Patel |
source |
11 |
| 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 |
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 |
Identification of Domains Containing Screen Failure Participants in SDTMs and ADaMs for Reviewer-s Guides |
Sumanjali Mangalarapu |
source |
5 |
| PharmaSUG |
2025 |
Improve Your CRF Review Process: A Python-Based Approach to Capturing CRFs via Browser Automation |
Andrew Herndon |
source |
8 |
| PharmaSUG |
2025 |
Integrating SAS DDE to Automate Excel Task Tracking in Pharmaceutical Statistical Programming |
Amy Zhang,
Huei-Ling Chen |
source |
8 |
| PharmaSUG |
2025 |
Integration Contemplation: Considerations for a Successful ISS/ISE from Planning to Execution |
Jennifer McGrogan,
Mario Widel |
source |
8 |
| PharmaSUG |
2025 |
Key guidelines, Tricks and Experiences for PMDA and comparison with FDA and CDE submission |
Ramesh Potluri |
source |
6 |
| 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 |
Macro to Compare ADaM Spec Derivations Against Available SDTM Data |
Ingrid Shu,
Kexin Guan,
Jeff Xia |
source |
9 |
| PharmaSUG |
2025 |
Multiple Imputation Techniques in the Context of ADaM Datasets |
Shunbing Zhao,
Linping Li |
source |
11 |
| PharmaSUG |
2025 |
Name That ADaM Dataset Structure |
Nancy Brucken |
source |
8 |
| PharmaSUG |
2025 |
Navigating the transition of legacy processes for SDTM creation |
Jyothi Ketavarapu |
source |
5 |
| PharmaSUG |
2025 |
PDFs Done Right: The Statistical Programmer-s Guide to Flawless Regulatory Submissions |
Srivathsa Ravikiran,
Sri Raghunadh Kakani |
source |
12 |
| PharmaSUG |
2025 |
Programming Perspectives for Efficient and Accurate C-QTc Analysis |
Lingjie Zhang,
Lata Maganti,
Richard Moreton,
Runcheng Li |
source |
11 |
| PharmaSUG |
2025 |
Reach for R Low Hanging Fruit for Faster Results |
Sunil Kumar Gupta |
source |
4 |
| PharmaSUG |
2025 |
Roadmap to Efficacy Analysis for Early Phase Oncology studies |
Dhruv Bansal,
Christiana Hawn,
Chris Kelly |
source |
23 |
| PharmaSUG |
2025 |
Running the CDISC Open Rules Engine (CORE) in BASE SAS |
Lex Jansen |
source
presentation |
40 |
| 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 |
Stop Making More Physical Copies of Your Data: A Modern Approach to Traceability and Fidelity |
Anthony Chow,
Robert Garelick |
source |
8 |
| PharmaSUG |
2025 |
Streamlining Validation Review and SAS Program Management with R |
Huei-Ling Chen |
source |
11 |
| PharmaSUG |
2025 |
The Many Use Cases of Standardized Data and Metadata |
Sanjiv Ramalingam |
source |
4 |
| PharmaSUG |
2025 |
The Model Maketh the Metadata |
Carlo Radovsky |
source |
19 |
| PharmaSUG |
2025 |
The Show Must Go On: Best Practices for Submitting SDTM Data for Ongoing Studies |
Kristin Kelly |
source |
9 |
| PharmaSUG |
2025 |
The Winding Road to ADSL |
Elizabeth Dennis,
Grace Fawcett |
source |
6 |
| PharmaSUG |
2025 |
The {teal} Adoption Playbook: Strategies, Tools, and Learning Paths for Open Source |
Vedha Viyash |
source |
8 |
| PharmaSUG |
2025 |
Time-to-Deterioration for Patients Reported Outcomes |
Christine S Teng |
source |
11 |
| PharmaSUG |
2025 |
TLFQC: A High-compatible R Shiny based Platform for Automated and Codeless TLFs Generation and Validation |
Chen Ling,
Yachen Wang |
source |
18 |
| PharmaSUG |
2025 |
Towards an Integrated Submission-Ready Data Pipeline: Unifying Compliance, Automation, and Open-Source Innovation |
Shivani Gupta,
Bhavin Busa |
source |
5 |
| 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 |
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 |
What comes first, the chicken (ADSL) or the egg (ADNCA)? Modularize your covariate creation to support flexible analysis dataset implementation! |
David C. Izard |
source |
6 |
| PharmaSUG |
2025 |
When PROC SORT Isn-t Enough: Implementing Horizontal Sorting in SAS |
Krutika Parvatikar,
Jeff Xia |
source |
5 |
| PharmaSUG |
2025 |
Which ADaM Data Structure Is Most Appropriate? Gray Areas in BDS and OCCDS. |
Veronica Gonzalez |
source |
15 |
| PharmaSUG |
2025 |
Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates |
Richann J. Watson |
source |
19 |
| PharmaSUG |
2025 |
{sdtm.oak} V0.1 on CRAN, sponsored by CDISC COSA, part of Pharmaverse, is an EDC and Data Standard agnostic solution for developing SDTM datasets in R. |
Rammprasad Ganapathy |
source |
5 |
| PHUSE US |
2025 |
A Guided User Experience for Automated Mapping |
Nathan Johnson |
source
presentation source |
9 |
| 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 Data Integration: Utilizing Python Scripts and Semantic Search for Variable Mapping in Multiple Studies |
Xiaopeng Li |
source
presentation source |
6 |
| PHUSE US |
2025 |
Advancing TFL Automation: R-Based Meta-Programming Powered by ARS |
Malan Bosman |
source
presentation source |
7 |
| PHUSE US |
2025 |
An End-to-End Approach to Fine-Tuning Small LLMs for Generating Admiral R Code in Statistical Programming |
Tingting Tian,
Jaime Yan |
source
presentation source |
15 |
| 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 |
Automating Preliminary CDISC SDTM Compliance Checks with a Customised SAS Macro |
Wei Qian,
Danny (Shih-Che) Hsu |
source
poster source |
3 |
| PHUSE US |
2025 |
Automating SDTM Annotated CRF (aCRF) Creation |
David Postma,
Christine Rossin |
source
presentation source |
6 |
| PHUSE US |
2025 |
Automating your safety data reconciliation: An approach towards reliable and efficient SAE reconciliation process |
Ritu Dogra |
source
presentation source |
11 |
| PHUSE US |
2025 |
Biomedical Concepts: What Are They and Why Should I Care? |
Stuart Malcolm |
source
presentation source |
7 |
| PHUSE US |
2025 |
CDISC 360i: Implementing the CDISC Roadmap Connecting Standards from Design to Analysis |
Chris Decker,
Peter Van Reusel |
source
presentation source |
4 |
| PHUSE US |
2025 |
CDISC Open Rules: A Deep Dive into Custom Rule Creation |
Roman Radelicki |
source
presentation source |
12 |
| PHUSE US |
2025 |
Clinical Trial Reporting Automation Based on Knowledge Graph |
Jaya Simha Inampudi |
source
poster source |
5 |
| PHUSE US |
2025 |
Collaborating on Standards: An Approach to Harmonizing Vaccine Regulatory Submissions |
Fred Bermont,
Médéric Celle,
Estella Sani,
Erin Gnas,
Jennifer Mastri,
Leslie Morgan,
Naila Musani,
Ramana Setty,
Sandra VanPelt Nguyen,
Yun Zhang |
source
presentation source |
8 |
| 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 Quality in Pooled Studies: Overcoming Challenges and Ensuring Accuracy |
Monika Ludwinska |
source
presentation source |
11 |
| 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 |
Double Trouble: Essential Insights from Successful Dual sBLA Submissions for a Drug-Device Combo |
Elma Ferdousy,
Aldrich Salva |
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 |
Effortless SDTM Upversioning: Leveraging Open-Source R for Efficient Data Standardisation |
Ramya Gangadi |
source
presentation source |
7 |
| 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 |
Enable and Automate: A Technical Roadmap Defining CDISC's Path to End-to-End Automation |
Samuel Hume |
source
presentation source |
8 |
| 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 |
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 |
Expediting the Regulatory Submission Process Through Automated Tools |
Manish Deole,
Gautham Selvaraj |
source
poster source |
4 |
| PHUSE US |
2025 |
From Roadblocks to Roadmaps: Overcoming Challenges in Registry Data Reporting |
Sivasankar Konda,
Neha Srivastava |
source
presentation source |
4 |
| 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 for Statistical Reporting and Clinical Study Report (CSR) Writing |
Leveraging CDISC |
source
presentation source |
10 |
| 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 Storage of SDTM Mappings as JSON: Boosting Efficiency and Data Consistency |
Rohan Parmar,
Edgar Manukyan |
source
presentation source |
5 |
| PHUSE US |
2025 |
Interactive Visualisation of Pooled Clinical Trial Safety Data |
Sara Bodach,
Ling Zhang |
source
presentation source |
7 |
| 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 |
Let the Machine Do the Coding: A SAS-Based Framework for Automating TFL Generation with ARS Metadata |
Julie Wachara |
source
presentation source |
9 |
| 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 |
Management of Regulatory Submissions Using eCTD Sequences and Life Cycle Operators: Lessons from Real-Time Oncology Review (RTOR) and Regular Submissions |
Madhusudhan Reddy Papasani,
Elisabeth Pyle,
Mary N. Varughese |
source
presentation source |
8 |
| PHUSE US |
2025 |
Mapping OMAP Data to SDTM - Use Case for RWD in CAR-T Registry Studies |
Kai Deng,
Joe Xi |
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 |
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 |
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 |
Redefining FDA Submissions: The Future of Interactive R Shiny Dashboards |
André Veríssimo,
Vedha Viyash |
source
presentation source |
5 |
| PHUSE US |
2025 |
SAS Programming approach for adjustment of treatment switching using Two-Stage Method |
Mani Mudumba |
source
presentation source |
13 |
| PHUSE US |
2025 |
SDTM Automation by Using Metadata to Drive R Functions for Data Transformation |
Krishna Gopal,
Jaya Simha Inampudi |
source
presentation source |
3 |
| 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 |
Selecting GeARS: Analysis Results Standard Implementation Options for Accelerated Analysis and TFL Automation |
Bhavin Busa,
Richard Marshall |
source
presentation source |
10 |
| PHUSE US |
2025 |
Standardised and Automated Template for Dose Escalation Decision-Making |
Jasmina Uzunovic,
Aditi Qamra |
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 Future of Data Surveillance in Clinical Studies: A Comprehensive Approach to Data Monitoring Using an R Shiny Application for Study Health |
Jacky Jin,
Ruchitbhai Patel |
source
presentation source |
5 |
| PHUSE US |
2025 |
The Implementation of {teal} Shiny Apps for DMC Activities |
Zhen Wu,
Peng Zhang |
source
presentation source |
7 |
| 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 |
Transforming Clinical Trials with AI-Driven Protocol Optimization and Next-Gen Statistical Programming |
Ravindra Shukla |
source
presentation source |
8 |
| 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 |
Unlocking the Secrets of Health: A Unified Approach to Biomarker and Clinical Data Integration |
Pavan Kumar Tatikonda |
source
presentation source |
8 |
| PHUSE US |
2025 |
Unravelling the Complexity: Efficacy Datasets in Oncology Basket Trials Across Multiple Diseases |
Venkatesh Burla,
Manasa Ravi |
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 |
What's Up with icSDRG? Navigating Through an Example [poster] |
Srinivas Kovvuri,
Bidhya Basnet |
source |
1 |
| PHUSE US |
2025 |
When and Why You Should Deviate from CDASH Standards |
Agnes Nkenglefac Akawung,
Trevano Dean |
source
poster source |
2 |
| PHUSE US |
2025 |
Write Concise ADaM Programs with If-less Programming Techniques |
Wei Shao,
Lei Zhang |
source
presentation source |
17 |
| PHUSE US |
2025 |
{sdtm.oak} - SDTM Programming in R |
Rammprasad Ganapathy,
Shiyu Chen |
source
poster source |
5 |
| PHUSE EU |
2024 |
A Guided User Experience for Automated Mapping |
Achilleas Zaras |
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 |
ADRG Builder Python Application |
Pierre Dostie |
source
presentation source |
16 |
| PHUSE EU |
2024 |
Anatomy of a Table - Our Continued Journey to Automating Output Delivery Through Metadata |
Edwin van Stein |
source
poster source |
10 |
| PHUSE EU |
2024 |
Associated Patient Mapping in SDTM |
Sadiya Ait M'Bark |
source
poster source |
2 |
| 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 |
Building CORE Strength: An Implementation Exercise |
Addie Nina Olsen,
Stine Winkler Bertelsen |
source
poster source |
3 |
| PHUSE EU |
2024 |
CDISC SDTM/SEND Generation Without Statistical Software: A Software Demonstration |
Jozef Aerts |
source |
3 |
| PHUSE EU |
2024 |
Challenges Faced When Creating Dosing Records for a Population PK Dataset |
Marianne van Vugt,
Gerly van der Vleuten |
source
presentation source |
3 |
| PHUSE EU |
2024 |
Connecting Standard from Design to Analysis to Submission: Finishing the CDISC 360 Vision [presentation] |
Peter Van Reusel |
source |
25 |
| 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 integration on CDISC ADaM Level: Multi-purpose Structures of ADSL and BDS Datasets |
Renate Scheiner-Sparna |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Data Traceability Map with R Shiny |
Alexander Mkrtchyan,
Sevak Kamalyan |
source
presentation source |
8 |
| 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 |
Estimands: How to Make ADaM Implementation Your Friend |
Jaclyn Amberg |
source
presentation source |
10 |
| PHUSE EU |
2024 |
FAIRification of preclinical data in radiation oncology through data standardization and formalized representation |
Olga Giraldo,
German Cancer |
source
presentation source |
5 |
| PHUSE EU |
2024 |
FDA Business Rules and CDISC Open Rules: The Road to Adoption |
Nick De Donder |
source
presentation source |
4 |
| 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 |
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 |
Harmonization and Interoperability between OMOP CDM and CDISC SDTM |
Dhruba Sikdar |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Hi. I Am a Chatbot. How Can I Help You? Enhancing the Reliability and Traceability of Large Language Models |
Vicky Poulsen,
Anja Vrecer |
source
presentation source |
9 |
| 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 |
ICH M11 Clinical Electronic Structure Harmonised Protocol (CeSHarP) and CDISC: Making the Electronic Protocol a Reality [presentation] |
Peter Van Reusel |
source |
29 |
| PHUSE EU |
2024 |
ID-SPECTACKLE: Making ADaM specifications "Fun" |
Sophie Dekeyser |
source
presentation source |
11 |
| PHUSE EU |
2024 |
Implementing CDISC CORE in a Cloud-Native, Regulated Environment to Support Rare Diseases Submissions |
Stijn Rogiers,
Emmy V Pahmer |
source
presentation source |
4 |
| 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 reporting using FDA Standard Safety Shells and CDISC Analysis Results Standard |
Megan Harries |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Introduction to the ADNCA ADaM |
Charlotte Hampson,
Florence Horspole |
source
poster source |
4 |
| PHUSE EU |
2024 |
Lessons Learned From the ADaM Data Development Using ADMIRAL [poster] |
Katarzyna Golasa,
Tomasz Lebitko |
source |
1 |
| 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 |
Making SDTM/ADaM CRT Packages Submission Ready |
Phillip Spowart |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Mapping a Veeva SDS Specification to ODM-XML |
Jørgen Mangor Iversen |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Mastering Pinnacle 21 for Oncology SDTM |
Daryna Khololovych |
source
presentation source |
7 |
| 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 |
OAK Productivity Experiment - How We Made SDTM Programming 5x Faster |
Amy Franklin,
Magdalena Krochmal |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Optimising Workflow and Collaboration in a Pooled Coding Environment for Clinical Development |
Louise Noergaard |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Our Road to Adopting CORE: an Implementation Journey in SDTM Dataset Validation |
Marisa Wyckmans |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Pre ADSL - Revolutionise Your ADaM Workflow |
Korak Datta,
Taniya Chatterjee |
source
presentation source |
8 |
| 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 |
Synthesised Real-world Data: JSON and the Argonauts |
Anil Sekhari |
source
presentation source |
10 |
| PHUSE EU |
2024 |
The Challenges of Using Parent Study Data in a Long-Term Extension Study |
Kirsty Wall |
source
presentation source |
9 |
| 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 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 |
Theory to Practice: Harnessing R to Enhance Workflows |
Joana Marques Barros,
Matthew Brierley |
source
presentation source |
11 |
| PHUSE EU |
2024 |
Tips and Tricks: From Specification to Define.xml v2.1 using SAS |
Caroline Pelckmans |
source
presentation source |
18 |
| PHUSE EU |
2024 |
Verify: Facilitating End-to-End Automation of Clinical Validation Processes Using AI Algorithms and Dynamic Collaboration |
Ilan Carmeli |
source
presentation source |
3 |
| 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 |
| PHUSE EU |
2024 |
{admiralvaccine} Project JouRney |
Federico Baratin,
Michael S Rimler |
source
presentation source |
8 |
| SESUG |
2024 |
Applying Different Data Cutoff Dates for the Analysis of a Study Milestone |
Guowei Zhao,
Hong Qi |
source |
7 |
| SESUG |
2024 |
C-SSRS Questionnaire Dataset Design for Assessing Suicide Risk in Neuroscience Studies |
Anupriya Lakshmipathy |
source |
6 |
| WUSS |
2024 |
Automation of Submission of Programs in Analysis Data Reviewer's Guide for FDA and PMDA Submissions |
Junying Zhang |
source |
14 |
| WUSS |
2024 |
iCSR: A Wormhole to Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade |
source |
7 |
| WUSS |
2024 |
Interactive Data Analysis and Exploration with composR: See the Forest AND the Trees |
Steve Wade,
Sudhir Kedare |
source |
6 |
| 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 |
| PharmaSUG CN |
2024 |
A metadata-driven system to generate annotated CRF automatically |
Guojun Liufu,
Jun Wu,
Li Chen,
Zhen Peng,
Fushan Lai,
Hanjia Zheng |
source |
7 |
| PharmaSUG CN |
2024 |
An Automatic SDTM Platform: Create Your SDTM Since Case Report Form is Ready! |
Mingyue Zhu,
Wei Wang,
Mingfeng Zhou |
source |
12 |
| PharmaSUG CN |
2024 |
An end-to-end Digital Platform for TFL Automation - From Metadata to TFL Outputs |
Yanan Sui,
Jiapeng He,
Mingliang Fan,
Xuejie Zhou,
Lin Jiang,
Tingting Zeng,
Jinling Li |
source |
8 |
| PharmaSUG CN |
2024 |
An R Function to Split Text Strings Exceeding 200 Characters into Multiple Variables |
Longfei Li |
source |
7 |
| PharmaSUG CN |
2024 |
Auto-annotation CRF per SDTM-MSG 2.0 by R |
Qi Luo |
source |
9 |
| PharmaSUG CN |
2024 |
Automatic ADaM Network Analysis Extracting from Metadata/Define/Log with R Shiny |
Jun Zhai |
source |
10 |
| PharmaSUG CN |
2024 |
CDASH-SDTM Combo Model in SDTM Automation |
Chunpeng CZ Zhao |
source |
11 |
| 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 |
Extracting Useful Information from XFDF Format of aCRF Annotations |
Tingting Zhang,
Yuan Sun |
source |
13 |
| PharmaSUG CN |
2024 |
Fighting with Special Characters in Data Management Programmer's Daily Work |
Fei Guo |
source |
20 |
| PharmaSUG CN |
2024 |
General Considerations for Integrating ADaM Data and Special Handling of One Complex Case in ISS |
Niandong Yang |
source |
7 |
| 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 |
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 |
Metadata-Driven Programming Using R: A Case Study in BDS |
Qian Su,
Renxiang Wang |
source |
13 |
| PharmaSUG CN |
2024 |
MetaTFL - A Dynamic Configuration Application for a Centralized Clinical Analysis Platform |
Cheng Zhang |
source |
8 |
| PharmaSUG CN |
2024 |
Navigating Statistical Programming Challenges in Early Phase Oncology Trials |
Dandan Du |
source |
13 |
| PharmaSUG CN |
2024 |
Programming Activities of Conducting Data Masking in Open-Label Study |
Xinyun Gao |
source |
6 |
| PharmaSUG CN |
2024 |
Programming Perspective: Streamline Estimands, Strategies, and Design ADaM for Estimand |
Yuqin Wu |
source |
10 |
| 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 |
Validation result checking and tracking by X command |
Fangrun He |
source |
6 |
| PharmaSUG |
2024 |
A New Approach to Automating the Creation of the Subject Visits (SV) Domain |
Xiangchen (Bob) Cui,
Jessie Wang,
Min Chen |
source |
24 |
| PharmaSUG |
2024 |
A New Way to Automate Data Validation with Pinnacle 21 Enterprise CLI in LSAF |
Crystal Cheng |
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 |
A Tool for Automated Comparison of Core Variables Across ADaM Specifications Files |
Amy Zhang,
Huei-Ling Chen |
source |
6 |
| 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 |
ADaM Design for Prostate Cancer Efficacy Endpoints Based on PCWG3 |
Lihui Deng,
Kylie Fan,
Jia Li |
source |
10 |
| PharmaSUG |
2024 |
ADaM Discussion Topics: PARQUAL, ADPL, Nadir |
Sandra Minjoe |
source |
7 |
| PharmaSUG |
2024 |
Advancing the Maturation of Standardized CRF Design |
Sugumaran Muthuraj,
Rubha Raghu |
source |
9 |
| 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 |
Automated Harmonization: Unifying ADaM Generation and Define.xml through ADaM Specifications |
Wei Shao,
Xiaohan Zou |
source |
10 |
| PharmaSUG |
2024 |
Automating the annotation of TLF mocks Using Generative AI |
Vidya Gopal |
source |
6 |
| PharmaSUG |
2024 |
AutoSDTM Design and Implementation With SAS Macros |
Chengxin Li |
source |
10 |
| PharmaSUG |
2024 |
AutoVis Oncology Presenter: Automated Python-Driven Statistical Analysis and Visualizations for Powerful Presentations |
Indraneel Narisetty |
source |
12 |
| PharmaSUG |
2024 |
CDISC Therapeutic Area User Guides and ADaM Standards Guidance |
Karin LaPann |
source |
6 |
| 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 |
Cultivating Success with Non-standard Investigator-sponsored Trial Data for FDA Submissions |
Jai Deep Mittapalli,
Jinit Mistry,
Venkatesulu Salla |
source |
9 |
| PharmaSUG |
2024 |
Define-XML Conversion: A General Approach on Content Extraction Using Python |
Danfeng Fu,
Dickson Wanjau,
Ben Gao |
source |
15 |
| 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 |
Enhanced Spider Plot in Oncology |
Ilya Krivelevich,
Cixin He,
Binbin Zhang-Wiener,
Wenyin Lin |
source |
14 |
| PharmaSUG |
2024 |
Enhancing Define-XML Generation: Based on SAS Programming and Pinnacle 21 Community |
Kevin Sun |
source |
11 |
| PharmaSUG |
2024 |
Experimenting with Containers and webR for Submissions to FDA in the Pilot 4 |
André Veríssimo,
Ismael Rodriguez |
source |
8 |
| PharmaSUG |
2024 |
Exploit the Window of Opportunity: Exploring the Use of Analysis Windowing Variables |
Richann J. Watson,
Elizabeth Dennis,
Karl Miller |
source |
4 |
| PharmaSUG |
2024 |
Externally Yours - Adeptly Managing Data Outside Your EDC System |
Frank Canale |
source |
38 |
| PharmaSUG |
2024 |
Game changer! The new CDISC ADaM domain ADNCA for PK/PD data analysis |
Santosh Ranjan |
source |
7 |
| 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 |
How to generate a submission ready ADaM for complex data |
Yilan Xu,
Hu Qu,
Tina Wu |
source |
8 |
| 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 |
Interactive Data Analysis and Exploration with composR: See the Forest AND the Trees |
Steve Wade,
Sudhir Kedare,
Matthew Travell,
Chen Yang,
Jagan Mohan Achi |
source |
7 |
| PharmaSUG |
2024 |
Is a Participation-Level ADaM Dataset a Solution for Submitting Integration Data to FDA? |
Sandra Minjoe |
source |
7 |
| PharmaSUG |
2024 |
Lead-in and extension trials, how we documented datapoint traceability |
Hanne Ellehoj,
Veeresh Namburi |
source |
5 |
| PharmaSUG |
2024 |
Leveraging SAS and Adobe Plug-in for CRF Bookmark Generation (Rave studies) |
Swaroop Neelapu |
source |
12 |
| PharmaSUG |
2024 |
LLM-Enhanced Training Agent for Statistical Programming |
Jason Zhang,
Jaime Yan |
source |
8 |
| PharmaSUG |
2024 |
Managing a Single Set of SDTM and ADaM Specifications across All Your Phase 1 Trials |
Avani Kaja |
source |
5 |
| PharmaSUG |
2024 |
Oncology ADaM Datasets Creation Using R Programming: A Comprehensive Approach |
Ishwar Chouhan |
source |
29 |
| PharmaSUG |
2024 |
Ongoing Trends and Strategies to Fine-tune the CRO/Sponsor Partnership - Perspectives from Statistical Programming |
Mathura P. Ramanathan |
source |
10 |
| PharmaSUG |
2024 |
Periodic safety reports of clinical trials |
Murali Kanakenahalli,
Annette Bove,
Smita Sehgal |
source |
8 |
| PharmaSUG |
2024 |
Piloting into the Future: Publicly available R-based Submissions to the FDA |
Benjamin Straub |
source |
9 |
| PharmaSUG |
2024 |
Programming Considerations in Deriving Progression-Free Survival on Next-Line Therapy (PFS2) |
Alec McConnell,
Yun Peng |
source |
5 |
| 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 |
Relax with Pinnacle 21-s RESTful API |
Trevor Mankus |
source |
8 |
| PharmaSUG |
2024 |
SDTM Specifications and Datasets Review Tips |
Wanchian Chen |
source |
7 |
| PharmaSUG |
2024 |
Simplifying Edit Check Configuration |
Vandita Tripathi,
Manas Saha |
source |
7 |
| PharmaSUG |
2024 |
Source Data Quality Issues in PopPK/PD Dataset Programming: a Systematic Approach to Handle Duplicates |
Ibrahim Priyana,
Ellen Winckelmans |
source |
10 |
| PharmaSUG |
2024 |
Splashy Graphics Suitable for Publication? ODS LAYOUT Can Do It! |
Dave Hall |
source |
6 |
| PharmaSUG |
2024 |
Streamlined EDC data to SDTM Mapping with Medidata RAVE ALS |
Yunsheng Wang,
Erik Hansen,
Chao Wang,
Tina Wu |
source |
12 |
| 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 |
Transitioning from SAS to R |
Ashley Tarasiewicz,
Chelsea Dickens |
source |
83 |
| 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 |
Variable Subset Codelist |
Kang Xie |
source |
7 |
| 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 Programmer's Perspective on Navigating the Hurdles of Investigator-Sponsored Research (ISR) Trials |
Jyotsna Lakshmikumar |
source
presentation source |
6 |
| PHUSE US |
2024 |
Addressing Challenges in Structuring CDISC SDTM and ADaM Datasets to Report Adverse Events Spanning Two Treatment Periods |
Madhusudhan Reddy Papasani |
source
presentation source |
4 |
| PHUSE US |
2024 |
AI-Enhanced Chatbot for Streamlined Clinical Trial Analysis and Document Management |
Jaime Yan |
source
presentation source |
7 |
| PHUSE US |
2024 |
An Efficient Way of Managing the Execution and QC of SAS Programs in Multiple Folders |
Wei Qian,
Danny Hsu |
source
poster source |
2 |
| PHUSE US |
2024 |
Automating ADaM Creation in Clinical Trials Part 2 |
Rie Ichihashi,
Lyubov Sushchenko |
source
presentation source |
7 |
| PHUSE US |
2024 |
Beyond Outliers: Unsupervised Anomaly Detection in Clinical Trial Data |
Helena Yaben,
Kian Norouzi |
source
presentation source |
9 |
| PHUSE US |
2024 |
Bridging the Gap Between the pharmaverse and Company Internal Resources |
Kangjie Zhang |
source
presentation source |
8 |
| 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 |
Data Handling through CDISC Standards in Master Protocols: A Focus on Rescreened and Re-Enrolled Subjects |
Swathi Kotla,
Madhusudhan Reddy Papasani |
source
presentation source |
7 |
| PHUSE US |
2024 |
Demystifying Submissions to NMPA China [presentation] |
Hiral Raval,
Dyuthi Yellamraju |
source |
19 |
| PHUSE US |
2024 |
Digitisation of Specifications - Brave New World for Analysis Definitions |
Rebecca Bates,
Krishna Gopal |
source
presentation source |
6 |
| PHUSE US |
2024 |
Does One Size Fit All? |
Bidhya Basnet |
source
poster source |
4 |
| PHUSE US |
2024 |
Effective Workflow Process: Rapid SDTMs and Compliance Dashboards |
Sunil Kumar Gupta,
Harinarayan Gopichandra |
source
poster source |
5 |
| PHUSE US |
2024 |
Effortless Table Generation: A SAS Macro for Streamlining Your Workflow |
Zhen (Laura) Li |
source
presentation source |
12 |
| PHUSE US |
2024 |
Electronic Clinical Outcome Assessment (eCOA) in SDTM: Challenges and Solution |
Shivam Kumar |
source
presentation source |
5 |
| 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 |
Enabling the Interoperable Data Ecosystem with the elluminate Clinical Data Cloud [presentation] |
Nathan Johnson |
source |
15 |
| PHUSE US |
2024 |
From Missing to Meaningful: Tackling Partial Dates in Clinical Trials |
Bhargav Koduru |
source
poster source |
4 |
| PHUSE US |
2024 |
From stowaway to admiral, a R-iveting tale of a hierarchical composite endpoint's journey from idea to dataset |
Nicole Major,
Otto Magnusson |
source
presentation source |
16 |
| 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 |
Getting More Efficiency from your Instruments Using CDISC |
Franklin E. Menius |
source
presentation source |
5 |
| PHUSE US |
2024 |
Getting Started with the New CDISC Analysis Results Standard |
Bess LeRoy,
Bhavin Busa,
Richard Marshall |
source
presentation source |
4 |
| 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 |
How to Monitor SDTM Data Health |
Amanda Cross |
source
presentation source |
8 |
| 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 |
Incorporating Real-World Data in a Low-Interventional Study: Challenges and Considerations |
Sandra VanPelt Nguyen |
source
presentation source |
8 |
| PHUSE US |
2024 |
Ingenious Raw Data Tracking in SDTM Programs: A New Perspective |
Bhanojinaidu Duppada,
Sumanth Goud Bheemagani |
source
presentation source |
7 |
| 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 |
Leveraging APIs in a Multilingual World: Run SAS Jobs from Your R Program |
Samiul Haque |
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 |
Navigating the Safe Integration of AI (ChatGPT) into Clinical Trials Programming Workflow |
Mykyta Vysotskyi |
source
presentation source |
10 |
| 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 |
Population Pharmacokinetic Analysis Data (ADPPK) Programming in {admiral} and the pharmaverse |
Jeffrey Dickinson |
source
poster source |
9 |
| 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 |
Revolutionising SDTM Transformation in Pharma: Introducing {oak} - An Open-Source R Package Sponsored by CDISC COSA |
Rammprasad Ganapathy |
source
presentation source |
5 |
| PHUSE US |
2024 |
SAS ODS Package for Efficient Creation of Zip File for P21 Validation |
Venkatesh Burla |
source
presentation source |
8 |
| PHUSE US |
2024 |
Scaling ECAs from Projects to the Enterprise: Multicentre, Multisource Infrastructure for External Control Arms |
Jussi Leinonen,
Mayur Saxena |
source
presentation source |
4 |
| 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 |
Standards Library: Getting started - A Medical Device Case Study |
Amy Booth |
source
presentation source |
6 |
| PHUSE US |
2024 |
Streamlining the Integration of SDTM Datasets from Multiple Studies: A Macro Approach |
Santosh Reddy Lekkala |
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 |
TFL Designer: Automating Tables, Figures and Listings Design and Generation for Analysis Results [presentation] |
Navin Dedhia,
Bhavin Busa |
source |
10 |
| PHUSE US |
2024 |
The Data Review Model - Recognising the Benefits of a Single Source of Truth Model for Data Review |
Priyank Patel |
source
presentation source |
8 |
| 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 Many Use Cases of Standardized Data and Metadata |
Sanjiv Ramalingam |
source
presentation source |
4 |
| 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 |
Unveiling the Potential of ADNCA via the CDISC ADaM IG: Revolutionising Pharmacokinetic Non-Compartmental Analysis Input Data Standardisation |
Saumilkumar Tripathi |
source
presentation source |
10 |
| 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 |
Using R for QC of Tables |
Marcus Trincia |
source
poster source |
3 |
| PHUSE US |
2024 |
USUBJID Challenges: Representing Multiple Participations for Analysis and Reporting |
Emily Bernstein-Hanlon,
Sirisha Davuluri |
source
presentation source |
9 |
| PHUSE US |
2024 |
{admiral} - From Open Source Through to Company Implementation |
Ross Farrugia |
source
presentation source |
4 |
| PHUSE EU |
2023 |
"It's ARM, Jim, But Not As We Know It" - Our Journey to Automating Output Delivery Through Metadata |
Edwin van Stein,
Warwick Benger |
source
presentation source |
11 |
| PHUSE EU |
2023 |
'Beep Beep': A Metadata Code Writer to Generate SAS Programs |
Giuseppe Di Monaco |
source
presentation source |
10 |
| 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 Robust Framework to Provide and Validate Real-Time SDTM Data |
Bremer Louw |
source
presentation source |
11 |
| PHUSE EU |
2023 |
An Agile Approach to Onboarding |
Ben White |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Analysis and Reporting of Immunogenicity Anti-drug Antibody Data |
Nicola Perry |
source
poster source |
6 |
| 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 |
Automating ADaM Dataset Generation via Definitive Specification Writing with A Domain-Specific Language |
Kang Zhao |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Boosting SAS Programming Efficiency with ChatGPT: A Clinical Trials Perspective |
Illia Skliar |
source
presentation source |
11 |
| 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 |
Creating CORE Rules from Biomedical Concepts |
Johannes Ulander |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Customisable Smart Search Tool for Project Leads |
Bibas Timilsina |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Dataset-JSON [presentation] |
Samuel Hume,
Jesse Anderson |
source |
26 |
| PHUSE EU |
2023 |
Developing and Implementing CDISC CORE rules: from zero to hero |
Marisa Wyckmans |
source
presentation source |
8 |
| 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 |
Enhancing the Quality of Data Harmonisation - a Customisable Tool for Validation of Bespoke SDTM Implementation at the Infectious Diseases Data Observatory (IDDO) [poster] |
Sadie Kelly,
Dick Hung |
source |
1 |
| PHUSE EU |
2023 |
Experiencing the FDA CBER |
Merve Akram,
Angelo Tinazzi |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Eyes On the Prize - The Development of {admiralophtha}, an R Package for Ophthalmology ADaMs |
Edoardo Mancini |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Further Adventures in SCE Alchemy |
Eleanor Sparling |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Gear Up SDTM with Digital Health Devices |
Vicky Poulsen |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Handling Multiple Screenings Using the New Domain DC (Demographics for Multiple Participations) at Merck - Implementation of a New Mapping Process [presentation] |
Kristina Zweier |
source |
21 |
| 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 |
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 |
Implementation of Estimands Using Data Standards [presentation] |
Chris Price,
Alexandra Cochinaire |
source |
26 |
| PHUSE EU |
2023 |
Implementation of MedDRA upgrade in SDTM: a SAS-based approach |
Mahmoud Abu Azoum |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Interaction with the FDA During and After a Type C Meeting, From the Perspective of a Statistical Programmer |
Dieter Hartz |
source
presentation source |
5 |
| PHUSE EU |
2023 |
It's Easy Peasy Submitting Data to the China NMPA - Really? |
Nigel Montgomery,
Chenkai Lv |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Leveraging the Analysis Results Standard (ARS): The Cytel PRISM Experience |
Nicolas Rouillé,
Sebastià Barceló |
source
presentation source |
8 |
| 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 |
Open-Source MDR and SDR - Managing Your Standards with the OpenStudyBuilder |
Nicolas De Saint Jorre,
Mikkel Traun |
source
presentation source |
13 |
| PHUSE EU |
2023 |
Open-Source Protocol Automation with the OpenStudyBuilder |
Nicolas De Saint Jorre,
Mikkel Traun |
source
presentation source |
9 |
| 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 |
Practical Operations of Electronic Study Data Submissions |
Priyanka Pujari |
source
presentation source |
9 |
| 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 |
SDTM CRT Packages and the Submission Space |
Joshua Glaser,
Charlotte Prior-Chappell |
source
poster source |
7 |
| PHUSE EU |
2023 |
Slicing Codes: A Modular approach to ADaM programming |
Mahendran Venkatachalam |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Standardisation in a fast growing environment; MDR, EDC and other abbreviations |
Louella Schoemacher,
Jasmine Kestemont |
source
presentation source |
6 |
| 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 Automation the CDISC 360 Way |
Alison Macnab,
John McDade |
source
presentation source |
12 |
| 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 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 |
Transparent is the New Black - Improving Data Findability Through Better Clinical Metadata |
Lukas Kniola |
source
presentation source |
16 |
| PHUSE EU |
2023 |
Unleashing the Role of a Statistical Programmer in Expediting a Submission, Novartis |
Sowmya Singuluri |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Validating Outsourced Programming Tasks by Comparing SAS Datasets Without PROC COMPARE |
Herman Ament |
source
presentation source |
5 |
| WUSS |
2023 |
Demystifying the define.xml: Overcoming the challenges of CRT Package. |
Yoganand Budumuru |
source |
10 |
| 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 |
| 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 |
| PharmaSUG |
2023 |
'TUFF' LOVE: SDTM Pain Points Explained! |
Kristin Kelly,
Michael Beers |
source |
12 |
| PharmaSUG |
2023 |
A case study of a successful RTOR submission and approval for Rylaze |
Sudhir Kedare,
Dilip Nalla,
Kumud Kanneganti,
Jagan Mohan Achi |
source |
6 |
| PharmaSUG |
2023 |
A Light-Weight Framework to Manage Programs and Run All the TLFs in R |
Chi-Hua Huang |
source |
27 |
| PharmaSUG |
2023 |
A Macro Utility for CDISC Datasets Cross Checking |
Chao Su,
Jaime Yan,
Changhong Shi |
source |
9 |
| PharmaSUG |
2023 |
A utility to combine study outputs into all-in-one PDF for DSUR |
Wei Shao |
source |
8 |
| PharmaSUG |
2023 |
ADaM Datasets with Multiple Participations per Subject |
Grace Fawcett,
Sandra Minjoe,
Elizabeth Dennis |
source |
7 |
| 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 |
All You Need to Know about the New CDISC Analysis Results Standards! |
Bhavin Busa,
Richard Marshall,
Bess LeRoy |
source |
7 |
| PharmaSUG |
2023 |
Are you planning to create/validate CDISC data set in R? Here is a step-by-step guide! |
Ganeshchandra Gupta |
source |
8 |
| PharmaSUG |
2023 |
As Simple as Falling Off a Log?: An Unusual Case Study of Mapping Data into the SDTM DA (Drug Accountability) Domain |
Susan Mutter |
source |
9 |
| PharmaSUG |
2023 |
Automating Data Validations with Pinnacle 21 Command Line Interface |
Philipp Strigunov |
source |
13 |
| PharmaSUG |
2023 |
Automating SDTM: A metadata-driven journey. |
Keith Hibbetts |
source |
11 |
| PharmaSUG |
2023 |
Automation of Dataset Programming Based on Dataset Specification |
Liqiang He |
source |
7 |
| PharmaSUG |
2023 |
Automation of the SDSP CBER Appendix for Vaccine Studies |
Nicole Jones,
Pritesh Solanki |
source |
6 |
| PharmaSUG |
2023 |
Better CDISC Standards with Metadata Programming |
Sunil Kumar Gupta,
Abhishek Dabral |
source |
14 |
| 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 |
CDISC SDTM IG v3.4: Subject Visits |
Ajay Gupta |
source |
7 |
| PharmaSUG |
2023 |
Consistency Checks Automation across Regulatory Submission Documents in the eCTD M5 folder |
Majdoub Haloui,
Loganathan Ramasamy,
Hemu Shere |
source |
8 |
| PharmaSUG |
2023 |
Creating a Centralized Controlled Terminology Mapping Repository |
Danny Hsu,
Shreya Chakraborty |
source |
4 |
| PharmaSUG |
2023 |
Digital Data Flow (DDF) and Technological Solution Providers |
Prasoon Sangwan,
Piyush K. Singh |
source |
8 |
| PharmaSUG |
2023 |
Display Layout Specifications to Flexibly Design and Generate Tables |
Songgu Xie,
Michael Pannucci,
Toshio Kimura |
source |
11 |
| PharmaSUG |
2023 |
F2: FAIR and Filing - Assessing Data Fitness for FAIR and Filing |
Bidhya Basnet,
Dyuthi Yellamraju |
source |
7 |
| PharmaSUG |
2023 |
FDA's Study Data Policy Framework and How CDISC Properties Are Evaluated for Inclusion |
Helena Sviglin |
source |
20 |
| PharmaSUG |
2023 |
From FDA to PMDA submission: How to resolve CDISC non-compliance issues |
Karin Steffensen,
Carina Brixval |
source |
16 |
| 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 |
Handling CRS/NT Data in CAR-T Studies and Submission |
Joe Xi,
Yuanyuan Liu,
Lorraine Fang |
source |
7 |
| PharmaSUG |
2023 |
Handling of Vaccine SDTM Data for FDA CBER/OVRR Submission Compliance |
Pragathi Mudundi,
Zhaoyu Xie |
source |
5 |
| 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 a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
source |
15 |
| 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 |
Integrated Trial Design Model Datasets? |
Christine McNichol |
source |
9 |
| PharmaSUG |
2023 |
Integrating Practices: How Statistical Programmers Differ and Align Within User Groups |
Valeria Duran,
Radhika Etikala,
Haimavati Rammohan |
source |
15 |
| PharmaSUG |
2023 |
Introduction of Developing Resistance Dataset |
Jenny H. Zhang,
Shunbing Zhao |
source |
6 |
| PharmaSUG |
2023 |
Key Statistical Programming Considerations in External Collaborative Clinical Trials |
James Zhao,
Hong Qi,
Mary N. Varughese |
source |
4 |
| 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 |
Leverage and Enhance CDISC TAUGs to Build More Traceability for and Streamline Development of Efficacy ADaM in Oncology Studies |
Xiangchen (Bob) Cui |
source |
29 |
| PharmaSUG |
2023 |
OCS Update: OCS Clinical Services & the Traceability Assessment |
Jesse Anderson |
source |
25 |
| PharmaSUG |
2023 |
Proposal for New ADaM Paired Variables: PARQUAL/PARTYPE |
Elizabeth Dennis,
Monika Kawohl,
Paul K. Slagle |
source |
7 |
| PharmaSUG |
2023 |
Questionnaires in ADaM: ADSF36 |
Keith Shusterman,
Megan O'Grady,
Mario Widel |
source |
13 |
| PharmaSUG |
2023 |
Real Projects, Real Transition, Really Revolutionary - Transitioning to R for Biometrics Work |
Danielle Stephenson,
Rebekah Oster,
Alyssa M. Wittle |
source |
11 |
| 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 |
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 |
Sound SDTM, Sound ADaM - Orchestrating SDTM and ADaM Harmonization |
Nancy Brucken,
David Neubauer,
Soumya Rajesh |
source |
8 |
| 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 |
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 Phantom of the ADaM: adding missing records to BDS datasets |
Anastasiia Drach |
source |
10 |
| PharmaSUG |
2023 |
Traceability: Not just about Data |
Rohit Nagpal,
Kavitha Mullela |
source |
11 |
| PharmaSUG |
2023 |
We Can Work it Out: Dos and Don-ts for Small Biotech and CRO NDA/BLA submission partnership |
Charity Quick,
Jiaan Illidge |
source |
8 |
| PharmaSUG |
2023 |
Working with Biomedical Concepts and SDTM Dataset Specializations for Define-XML using SAS Open CST |
Lex Jansen |
source |
23 |
| PHUSE US |
2023 |
A Standard Data Set Format for the Validation of Tables and Listings in Regulatory Submissions for Clinical Trials |
Kevin R. Viel |
source
poster source |
10 |
| PHUSE US |
2023 |
ADAE Design for Multiple Phase Trial |
Deepak S. Grewal |
source
presentation source |
4 |
| 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 |
Automating SDTM and ADaM Creation in Clinical Trials |
Lyubov Sushchenko,
Rie Ichihashi |
source
presentation source |
9 |
| 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 |
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 |
CDISC CORE - Milestones, Status and Roadmap |
Peter Van Reusel |
source
presentation source |
9 |
| PHUSE US |
2023 |
Challenges Addressing CBER Guidance on Reactogenicity, from Collection to Analysis |
Sandra VanPelt Nguyen,
Emily Bernstein-Hanlon |
source
presentation source |
12 |
| PHUSE US |
2023 |
Computerised Algorithm for Multiple Myeloma Response Assessments |
Mahesh Swaminathan |
source
presentation source |
3 |
| PHUSE US |
2023 |
Custom Domains ... the Gaps in Standardized Data |
Michael Beers |
source
presentation source |
8 |
| PHUSE US |
2023 |
DIY: Building a Raw Metadata Library with Integrated SDTM Annotations [poster] |
Sanjiv Ramalingam,
Shriram Sivaraman |
source |
1 |
| 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 |
Efficient Integration Programming Techniques [poster] |
Vaibhav Sathe,
Aparna Polisetty |
source |
1 |
| PHUSE US |
2023 |
Exploring the Possibility of Automating SDTM Domain Subject Visits (SV) |
Limna Salim |
source
presentation source |
8 |
| PHUSE US |
2023 |
FDA Dataset Walkthrough - Statistical Programming Perspectives |
Ketan Durve,
Rachit Desai |
source
presentation source |
7 |
| PHUSE US |
2023 |
If Data is the New Oil, How Do You Make the Most of Your Reserves? |
Simon Luo,
Ashley Mao |
source
presentation source |
4 |
| PHUSE US |
2023 |
Implementation of Estimands (ICH E9 (R1)) Using Data Standards [presentation] |
Banoo Madhanagopal,
Lori Van Meter |
source
video |
32 |
| PHUSE US |
2023 |
Incremental Automation - Lessons from a Pragmatic and Agile Journey of Improvement [presentation] |
Todd Bazin,
Anuja Das |
source
video |
31 |
| PHUSE US |
2023 |
Innovate Clinical Trial Reporting with Open Source |
Soma Sekhar Sriadibhatla,
Francis Kendall |
source
presentation source |
4 |
| PHUSE US |
2023 |
Managing Deliverables in Oncology Basket Trials |
Hong Qi,
Mary N. Varughese |
source
presentation source |
6 |
| PHUSE US |
2023 |
Practical Application of Multiple Screenings/Enrollments |
Martha O'Brien,
Proma Debnath |
source
presentation source |
4 |
| PHUSE US |
2023 |
Pre-launching CDISC Analysis Results Standards [presentation] |
Bhavin Busa,
Bess LeRoy |
source
video |
23 |
| PHUSE US |
2023 |
Realtime tuning of the ADaM parameters with an example of the big actigraphy dataset |
Mehrnoosh Oghbaie |
source
presentation source |
8 |
| 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 |
Say No to Stale Data!! Implementation of Automated GxP Data Pipelines Using KNIME [presentation] |
Shiva Katepalli,
Jeffrey Xiong |
source
video |
30 |
| 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 |
Technical Rejection Criteria for Study Data (TRC) and Beyond |
Lina Cong,
Jiang Xu |
source
presentation source |
4 |
| PHUSE US |
2023 |
The Role of AI in Handling Clinical Data and Documents (Structured and Unstructured) |
Farha Feroze |
source
presentation source |
6 |
| PHUSE US |
2023 |
The Ultimate Update to ADaM Specification Template that Simplifies ADaM Programming and Creation of Define XML [presentation] |
Yuanyuan Liu,
Xiang Wang |
source
video |
18 |
| PHUSE US |
2023 |
Up-to-Date with Dates - Imputation Rules in R Compared to SAS |
Monika Ludwinska |
source
presentation source |
10 |
| PHUSE US |
2023 |
Using One Specification to Create BIMO clinsite.xpt and its Define-XML [poster] |
Xiang Wang,
Yuanyuan Liu |
source |
1 |
| PHUSE US |
2023 |
What's New in ODM v2.0? [poster] |
Samuel Hume |
source |
1 |
| PHUSE EU |
2022 |
An Approach to Effectively Reproduce TFLs When Performing ADaM Conversion [presentation] |
Amine Khemiri,
Caroline Pelckmans |
source
video |
19 |
| PHUSE EU |
2022 |
Automation of the CDISC Pilot study - a step-by-step guide |
Stuart Malcolm |
source
presentation source |
9 |
| PHUSE EU |
2022 |
Breaking Down the Data Standards Silos - A New Metadata Ontology for Data Analysis Derivations |
Chris Price,
Nelia Lasierra |
source
presentation source |
7 |
| PHUSE EU |
2022 |
CDISC Analysis Results Standard - Update and Progress |
Karl Wallendszus,
Hansjörg Frenzel |
source
presentation source |
7 |
| 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 |
Cross-functional Standardisation of Controlled Terminologies Through Knowledge Graphs [presentation] |
Daniela Bergann,
Ena Kolundzic |
source
video |
15 |
| PHUSE EU |
2022 |
Data Catalogues - The new Showman to organize your data, A CRO perspective |
Limna Salim |
source
presentation source |
8 |
| PHUSE EU |
2022 |
Data From the Clouds ... and Back Again |
John McDade |
source
presentation source |
12 |
| PHUSE EU |
2022 |
Decoding in R |
Himani Narang |
source
presentation source |
5 |
| PHUSE EU |
2022 |
Do It Yourself: Case Report Form (CRF) Annotation |
Caro Sluijter |
source
presentation source |
5 |
| PHUSE EU |
2022 |
DRM Version 2: The Standards Strike Back [poster] |
Marc-Antoine Prodhomme |
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 |
From Silos to Knowledge [presentation] |
David Iberson-Hurst |
source |
16 |
| 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 |
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 |
If you want to deliver standardised clinical data sets quickly, talk to the machine |
Chris Austin,
Michael Phillips |
source
presentation source |
6 |
| PHUSE EU |
2022 |
Leveraging Information from Healthy Volunteers' Placebo Data [presentation] |
Koen Ven |
source
video |
17 |
| PHUSE EU |
2022 |
Maturing standardisation; the switch from spreadsheet-based standards to an MDR |
Louella Schoemacher,
Jasmine Kestemont |
source
presentation source |
5 |
| PHUSE EU |
2022 |
Minimising 'Data Loss' During Mapping of Raw Data to SDTM [presentation] |
John Monaghan |
source
video |
35 |
| PHUSE EU |
2022 |
Modelling Electrocardiogram Waveform Interpretations for SEND Submissions [poster] |
Jack Baker |
source |
1 |
| PHUSE EU |
2022 |
No Compromise on QUALITY: Coding tips and Macros to improve Efficiency |
Akhil Vijayan |
source
presentation source |
10 |
| PHUSE EU |
2022 |
Overcoming Challenges of Your Integrated Summary ISS/ISE Submissions |
Jenet Cp,
Akhil Vijayan |
source
presentation source |
7 |
| PHUSE EU |
2022 |
Protocol Deviation Programming [presentation] |
Oussama Zineddine,
Caroline Pelckmans |
source
video |
25 |
| PHUSE EU |
2022 |
R Shiny Apps: To QC or Not to QC? [presentation] |
Katie Withycombe |
source
video |
19 |
| PHUSE EU |
2022 |
R Shiny to Drive Automation in Clinical Analysis and Reporting [poster] |
Jocelyn Wang,
Goutham Ghanta |
source |
1 |
| PHUSE EU |
2022 |
Release Your Creativity on Your Company Laptop |
Johannes Ulander |
source
presentation source |
10 |
| PHUSE EU |
2022 |
SAS Unit Validation of Your Macros to Upgrade Calibre! |
Roshan Stanly,
Siji Paul |
source
presentation source |
11 |
| PHUSE EU |
2022 |
SDTM Hackathon - To Find a Metadata-driven Software System that will Allow BMS to Automatically Generate Mapped SDTM Datasets [poster] |
Rashad Rasul,
Nicole Thorne |
source |
1 |
| 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 |
Table of Contents (TOC) - An Application of PowerShell |
Sumit Pratap Pradhan,
Navneet Agnihotri |
source
video
presentation source |
6 |
| PHUSE EU |
2022 |
The Development of CDISC Biomedical Concepts: Update and Next Steps [presentation] |
Bess LeRoy |
source
video |
35 |
| PHUSE EU |
2022 |
The Integration Dilemma |
Angelo Tinazzi |
source
video
presentation source |
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 |
Using Janssen's ADaM Submission RPA Bot to Successfully Prepare for Delivery of an ADaM Submission Package [poster] |
Andrew Noller |
source |
1 |
| PHUSE EU |
2022 |
Vision and Demonstration of the OpenStudyBuilder for Supporting Structured Protocol Content and Submission Deliverables Using Concept-based Standards [poster] |
Martin Gram,
Mikkel Traun |
source |
1 |
| SESUG |
2022 |
Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
source |
15 |
| SESUG |
2022 |
One Click Excel Cleanup - Generate High Quality SDTM/ADAM Specification |
Suresh Acharya |
source |
8 |
| SESUG |
2022 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| WUSS |
2022 |
Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 |
Richann J. Watson |
source |
15 |
| WUSS |
2022 |
Quick Jumpstart into Pharmaceutical SAS Programming |
Jim Box,
Matthew J. Becker |
source |
7 |
| 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 Dynamic Data Visualization Report for Efficacy Endpoints of Early Oncology Study |
Hong (Lily) Zhang,
Yixin Ren,
Huei-Ling Chen |
source |
10 |
| PharmaSUG |
2022 |
A SAS Macro to Support the Supplemental Qualifier Section in cSDRG |
Jamuna Purma,
Bindya Bindya Vaswani |
source |
9 |
| PharmaSUG |
2022 |
A Shiny App to Spell Check an ADaM Specification |
Simiao Ye,
Jeff Xia |
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 |
Above and Beyond Lesion Analysis Dataset (ADTL) |
Raghava Pamulapati |
source |
11 |
| PharmaSUG |
2022 |
ADCM Macro Design and Implementation |
Chengxin Li,
Tingting Tian,
Toshio Kimura |
source |
7 |
| PharmaSUG |
2022 |
Applying Agile Methodology to Statistical Programming |
Gina Boccuzzi |
source |
5 |
| PharmaSUG |
2022 |
Automatic CRF Annotations Using Python |
Lijun Chen,
Jin Shi,
Tong Zhao |
source |
12 |
| PharmaSUG |
2022 |
Automation of Clinical Data extracts using Cloud Applications |
Syam Prasad Chandrala,
Madhusudhan Nagaram,
Chaitanya Chowdagam,
Jegan Pillaiyar,
Kunal Chattopadhyay |
source |
9 |
| PharmaSUG |
2022 |
Avoid Common Mistakes in Preparing the BIMO Deliverables |
Chintan Pandya,
Himanshu Patel |
source |
9 |
| PharmaSUG |
2022 |
Bookmarking CRFs More Efficiently |
Noory Y. Kim |
source |
6 |
| 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 |
Clean Messy Clinical Data Using Python |
Abhinav Srivastva |
source |
7 |
| PharmaSUG |
2022 |
Clinical Classifications: Getting to know the new kid on the QRS block! |
Soumya Rajesh,
Michael Wise |
source |
9 |
| PharmaSUG |
2022 |
Damn*t, The Define! |
Julie Ann Hood,
Sarah Angelo |
source |
16 |
| PharmaSUG |
2022 |
Derivation of Efficacy Endpoints by iRECIST Criteria: A Practical Approach |
Ilya Krivelevich,
Lei Gao,
Richard Kennan |
source |
9 |
| PharmaSUG |
2022 |
eCOA and SDTM: Bring Order to the Wild West |
Vincent Allibone,
Franklin E. Menius,
Monali Khanna |
source |
8 |
| PharmaSUG |
2022 |
Fast hashes for complex joins |
Bartosz Szymecki |
source |
12 |
| PharmaSUG |
2022 |
Following Your Footsteps: Maintaining Traceability in ADaM Datasets |
Nancy Brucken,
Karl Miller |
source |
58 |
| PharmaSUG |
2022 |
Generating statistical Tables, Listings, and figures using machine learning, deep learning, and NLP techniques that provide more efficiency to the statistical programming process |
Farha Feroze,
Ilango Ramanujam |
source |
3 |
| PharmaSUG |
2022 |
How to create SDTM SAS transport datasets using Python |
Kevin Lee |
source |
8 |
| 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 |
Just Say No to Data Listings! |
Mercidita Navarro,
Nancy Brucken,
Aiming Yang,
Greg Ball |
source |
4 |
| PharmaSUG |
2022 |
Lessons Learned from Using P21 to Create ADaM define.xml with Examples |
Yizhuo Zhong,
Christine S Teng,
Majdoub Haloui |
source |
8 |
| PharmaSUG |
2022 |
Making an ADaM Dataset Analysis-Ready |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2022 |
Monitoring SDTM Compliance in Data Transfers from CROs |
Sunil Kumar Gupta |
source |
7 |
| PharmaSUG |
2022 |
PROC FUTURE PROOF 1.2 - Linked Data |
Danfeng Fu,
Ellie Norris,
Suhas R. Sanjee,
Susan Kramlik |
source |
13 |
| PharmaSUG |
2022 |
Programmed Value-Level Metadata for Define XML 2.0 |
Abhinav Srivastva |
source |
6 |
| 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 |
Redefining Industry Standards: Making CDASH and SDTM Work Together from the Database Level |
Chad Fewell,
Jesse Beck |
source |
5 |
| PharmaSUG |
2022 |
Rita: Automated Transformations, Normality Testing, and Reporting |
Daniel Mattei |
source |
15 |
| 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 |
Sponsor-defined Controlled Terminologies: A Tiny Key to a Big Door |
Shefalica Chand |
source |
15 |
| PharmaSUG |
2022 |
Subjects Enrolled in Multiple Cohorts within a Study - Challenges and Ideas |
Peng Du,
Hongli Wang |
source |
7 |
| PharmaSUG |
2022 |
Upgrading from Define-XML 2.0 to 2.1 |
Trevor Mankus |
source |
6 |
| PharmaSUG |
2022 |
Working with Dataset-JSON using SAS |
Lex Jansen |
source |
23 |
| PHUSE US |
2022 |
A Better Way: eCOA/ePRO Annotated Screen Reports (aSR) Provide Data Clarity from Data Collection to Submission |
Franklin E. Menius,
Monali Khanna,
Vincent Allibone |
source
presentation source |
6 |
| PHUSE US |
2022 |
A Practical Exploration of SEND for CBER Submissions |
Jack Baker |
source
presentation source |
11 |
| PHUSE US |
2022 |
Automating Analysis Result Metadata [presentation] |
Ghanshyam Jangid |
source
video |
17 |
| PHUSE US |
2022 |
CDISC Analysis Results Standards - Approach and Development Update [presentation] |
Bess LeRoy,
Jeffrey M. Abolafia,
Bhavin Busa |
source |
18 |
| PHUSE US |
2022 |
Clinical Data Standardization and Integration Using Data Warehouse and Data Mart Processes [presentation] |
Clio Wu |
source |
15 |
| PHUSE US |
2022 |
Collection, Standardization, and Reporting of Adverse Events with Toxicity Changes Using CDISC Standards in Oncology Clinical Trials |
Madhusudhan Reddy Papasani,
Swathi Kotla,
Elisabeth Pyle |
source
video
presentation source |
12 |
| PHUSE US |
2022 |
How Rapid SDTM Data Conversion Enabled Early Insights into Vaccine Safety and Efficacy in COVID-19 Trials [presentation] |
Gilbert Hunter,
Rachael Yates |
source
video |
16 |
| PHUSE US |
2022 |
Incorporating Immunogenicity Data from Various Analyzing Labs [presentation] |
Elisabeth van Son-Palmen,
Gunasekaran Subramaniam |
source |
19 |
| PHUSE US |
2022 |
Metadata-driven Case Report Tabulation for Regulatory Submissions |
Jacques Lanoue,
Rajashekar Thota |
source
presentation source |
8 |
| PHUSE US |
2022 |
Navigation of Professional Development Planning Through the Performance Appraisal Process [presentation] |
Parag Shiralkar |
source
video |
13 |
| PHUSE US |
2022 |
Pan-pharma Industry Collaboration - New Horizon, Success Stories [presentation] |
Tadeusz Lewandowski |
source
video |
21 |
| PHUSE US |
2022 |
Safety ADaM Automation from Design to Implementation [presentation] |
Chengxin Li,
Toshio Kimura |
source
video |
18 |
| 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 |
Trial Design Datasets in Oncology Clinical Trials [presentation] |
Anastasiia Drach |
source
video |
23 |
| PHUSE US |
2022 |
Trial Summary SDTM Domain Made Easy for Regulatory Submissions [presentation] |
Kishore Pothuri |
source |
16 |
| PHUSE US |
2022 |
Using odmlib to Create ODM and Define-XML Tools in Python |
Samuel Hume |
source
presentation source |
6 |
| PHUSE US |
2022 |
Using the Nest-map-unnest Workflow in R for Sub-group Analysis in Clinical Trial Reporting [presentation] |
Mia Qi,
Sheng-Wei Wang |
source
video |
12 |
| PHUSE US |
2022 |
Vaccine Trials: The Basics You Need to Know [presentation] |
Prashanthi Selvakumar |
source |
11 |
| PHUSE EU |
2021 |
A Beginner's Guide to Data Analysis |
Shuva Dey |
source
video |
15 |
| PHUSE EU |
2021 |
A case of mistaken ID: reimagining rescreenings and reenrollments |
Matt Metherell |
source
video
presentation source |
5 |
| PHUSE EU |
2021 |
Advanced Excel Specification for Automatic SDTM Generation |
Aleksandra Gorbunova,
Ilya Mishchenko |
source
video
presentation source |
10 |
| PHUSE EU |
2021 |
Automated creation of a mapping specification for a pooled database |
Thomas Wollseifen |
source
video
presentation source |
12 |
| PHUSE EU |
2021 |
Balancing Automation and Flexibility in Programming Processes |
Helen Nicholson,
Punitha Philip |
source
video
presentation source |
5 |
| PHUSE EU |
2021 |
Bringing to Light - Analysis Results Metadata v1.0 for Define-XML v2 [presentation] |
Hrishikesh K S,
Limna Salim |
source
video |
11 |
| 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 |
Code Sharing is Caring [presentation] |
Lucy Palmen |
source
video |
16 |
| PHUSE EU |
2021 |
F3: Fitness, FAIR & Filing [presentation] |
Bhupendra Mistry,
Nigel Montgomery |
source
video |
19 |
| PHUSE EU |
2021 |
How to Be Traceable in ADaM |
Angelo Tinazzi |
source
video
presentation source |
9 |
| PHUSE EU |
2021 |
How to Handle Large Data Volumes in SDTM Using Continuous Glucose Monitoring as an Example [presentation] |
Ari Siggaard Knoph,
Martin Gram |
source
video |
14 |
| 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 |
Learnings Using R for Creating CDISC Data for Analysis and Reporting Purposes! [presentation] |
Gustav Söderström,
Nicole Major |
source
video |
23 |
| PHUSE EU |
2021 |
Metadata: Errors Not Detected by the Pinnacle 21 Tool [presentation] |
Caroline Pelckmans,
Pamphile Beaujean |
source
video |
20 |
| PHUSE EU |
2021 |
Methods and Challenges of R Validation for Regulatory Submission Analysis [presentation] |
Parvee Kumar |
source
video |
14 |
| PHUSE EU |
2021 |
Multi-study programming - a best practice outline |
Simon Purkess,
Matt Metherell |
source
video
presentation source |
9 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
7 |
| PHUSE EU |
2021 |
Next Generation MDR Solution for Study Design and Configuration Using Concept-based Standards [presentation] |
Mikkel Traun |
source
video |
15 |
| 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 |
Real-world Data, CDISC SDTM, HL7 FHIR and the Future of Regulatory Submissions [presentation] |
Jozef Aerts |
source
video |
17 |
| PHUSE EU |
2021 |
SAS Formats On The Fly Using ADaM Datasets [presentation] |
John Hendrickx |
source
video |
12 |
| PHUSE EU |
2021 |
The Value of Optimising Your CDISC Analysis Data Model (ADaM) Specifications [presentation] |
Amine Khemiri,
Caroline Pelckmans |
source
video |
17 |
| PHUSE EU |
2021 |
Utilising LSAF for Data Management at a Belgian Biotech |
Louella Schoemacher |
source
video
presentation source |
7 |
| PHUSE US |
2021 |
A Macro to Automate Detection of Date Variables and Derivation of RFPENDTC |
Kiran Kumar Babu P |
source
video
presentation source |
8 |
| PHUSE US |
2021 |
ADaM Generator Tool [presentation] |
Gustav Bernard |
source
video |
45 |
| 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 |
Automation of a Web-based Metadata Repository for SAS Datasets with Selenium Technology [presentation] |
Eugene Tsykalov |
source
video |
14 |
| PHUSE US |
2021 |
Automation of CDISC ADaM Using Statistical Data and Metadata eXchange (SDMX) [presentation] |
Stuart Malcolm |
source
video |
29 |
| PHUSE US |
2021 |
Challenges and Solutions in SDTM Implementation and Programming of the Ophthalmic Examinations (OE) Domain [presentation] |
Shivam Kumar,
Vinita Dora |
source
video |
16 |
| 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 |
Common JumpStart Data Quality Findings [presentation] |
Alan Shapiro,
Michael Xue |
source
video |
16 |
| PHUSE US |
2021 |
Controlled Terminology Best Practices [presentation] |
Sarah Angelo |
source
video |
29 |
| 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 |
Dynamic Macro Using the Convergence Dataset to Generate the Odds Ratio (OR), Risk Ratio (RR) and Risk Difference (RD) per SOC and PT Using the Genmod Procedure [presentation] |
Jagadish Katam |
source
video |
26 |
| 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 |
Get Ready in One Click: Clean SDTM Datasets by Using Library Backend Rules [presentation] |
Annelies Van Zeveren,
Sofie Stynen |
source
video |
49 |
| PHUSE US |
2021 |
How the R Programming Language Handles the CDISC Library API |
Joseph W. Hinson |
source
video
presentation source |
11 |
| PHUSE US |
2021 |
Industry Metrics for Extensions of CDISC Terminology [presentation] |
Sergiy Sirichenko |
source
video |
36 |
| PHUSE US |
2021 |
Managing TFL Development in LSAF 5.3 Using SAS and R Code [presentation] |
Jean-Marc Ferran,
Stijn Rogiers |
source
video |
33 |
| PHUSE US |
2021 |
Pinnacle 21: Improving the Data Fitness Score for eSubmission |
Renu Motwani |
source
video
presentation source |
9 |
| PHUSE US |
2021 |
Planning and Execution of Real-world Data Evidence Analysis |
Nicole Thorne,
Ramesh Sundaram |
source
video
presentation source |
6 |
| PHUSE US |
2021 |
Process Optimization for Submissions Participating in the FDA's Real Time Oncology Review Pilot Program [poster] |
Grace Sun,
Kevin Liu |
source |
1 |
| 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 |
Python for Visualization in Solid Tumor Studies |
Hengwei Liu |
source
video
presentation source |
10 |
| PHUSE US |
2021 |
SDTM Mapping and Conversion Using NLP [presentation] |
Eric Weising |
source
video |
16 |
| PHUSE US |
2021 |
SDTM, ADaM and Database Normal Forms Implementation [presentation] |
Andrii Borzenkov |
source
video |
21 |
| 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: 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: DS06: CDISC Analysis Results Standard [presentation] |
Bess LeRoy |
source |
25 |
| PHUSE US |
2021 |
Template of Analysis Reviewer's Guide in Oncology [presentation] |
Hong Qi,
Mary N. Varughese |
source
video |
19 |
| PHUSE US |
2021 |
The Encoding Dilemma |
Angelo Tinazzi |
source
video
presentation source |
10 |
| PHUSE US |
2021 |
VALSPEC Utility to Validate CDISC Specifications [presentation] |
Aman Bahl,
Hrideep Antony |
source
video |
12 |
| PharmaSUG |
2021 |
A Lead Programmer-s Guide to a Successful Submission |
Pranav Soanker,
Santosh Shivakavi |
source |
8 |
| PharmaSUG |
2021 |
A SAS Macro to Generate Slim Version of Define for RTOR |
Jeff Xia |
source |
8 |
| PharmaSUG |
2021 |
A Unique Way to Identify the Errors in SDTM Annotations Using SAS |
Xingxing Wu,
Bala Dhungana |
source |
9 |
| PharmaSUG |
2021 |
ADaM Implementation Guide for Medical Devices |
Julia Yang,
Silvia Faini,
Karin LaPann |
source |
11 |
| PharmaSUG |
2021 |
ADaM-like Dataset: how to do big things in a short time |
Oksana Mykhailova,
Andrii Klekov |
source |
7 |
| PharmaSUG |
2021 |
Adding Rows to a BDS Dataset: When to Use DTYPE in Addition to Metadata |
Sandra Minjoe |
source |
11 |
| PharmaSUG |
2021 |
An efficient method to review annotation and create bookmark for case report form (acrf.pdf) using SAS program, FDF files, excel and Javascript in Acrobat |
Chen-Jung Wu |
source |
12 |
| 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 |
Biomedical Concepts - An Emerging CDISC Data Standard: A Stepwise Approach for Building a Library of Data Definitions |
Kirsten Langendorf,
Johannes Ulander |
source |
15 |
| PharmaSUG |
2021 |
CDISC ADaM Phases, Periods, and Subperiods: A Case Study |
Jennifer K. Fulton |
source |
9 |
| PharmaSUG |
2021 |
Challenges and Solutions for an ISM Development |
Si Ru Tang,
Yanhong Li |
source |
9 |
| PharmaSUG |
2021 |
Collaborative Review of CDISC QRS Instruments |
Steven A. Wilson,
Steve Kopko,
Dana Booth |
source |
54 |
| PharmaSUG |
2021 |
Common Dating in R: With an example of partial date imputation |
Teckla Akinyi |
source |
14 |
| PharmaSUG |
2021 |
Creating Hyperlinks in SDTM Specifications |
Carey G. Smoak |
source |
5 |
| PharmaSUG |
2021 |
Customizing define.xml files |
Steffen Müller |
source |
9 |
| PharmaSUG |
2021 |
Design ADaM Specification Template that Simplifies ADaM Programming and Creation of Define XML in CDISC Era |
Xiang Wang,
Daniel Huang |
source |
11 |
| PharmaSUG |
2021 |
Don-t send the Macros, send the Catalog! The SAS Macro Catalog: a perfect way to send your macros to the client without sharing the code. |
Steven C. Black |
source |
6 |
| PharmaSUG |
2021 |
e-Submissions key difference of FDA and PMDA |
Giri Prasad,
Hareeshkumar Gurrala |
source |
8 |
| PharmaSUG |
2021 |
Easing the Process of Creating CRF Annotations |
Samadi Karunasundera,
Jun Wang |
source |
7 |
| PharmaSUG |
2021 |
Effective Approach for ADaM Submission to FDA and PMDA |
Ranvir Singh |
source |
6 |
| PharmaSUG |
2021 |
Extracting Data Standards Metadata and Controlled Terminology from the CDISC Library using SAS with PROC LUA |
Lex Jansen |
source |
23 |
| PharmaSUG |
2021 |
Fast, Efficient, and Automated Real-time Analytics for Clinical Trials |
Aditya Gadiko,
Christopher C. Hurley,
Anish Iyer |
source |
5 |
| PharmaSUG |
2021 |
First Time Creating a Submission Package? Don-t Worry, We Got You Covered! |
Lyma Faroz |
source |
10 |
| PharmaSUG |
2021 |
Generating FDA-ready Submission Datasets directly from EHRs |
Jozef Aerts |
source |
9 |
| PharmaSUG |
2021 |
Generating Synthetic CDISC Clinical Trial Data. |
Jose C. Lacal |
source |
14 |
| PharmaSUG |
2021 |
Macro Development from Design to Implementation Applied to Occurrence Data Frequency Analysis |
Chengxin Li,
Michael Pannucci,
Toshio Kimura |
source |
9 |
| PharmaSUG |
2021 |
Manage SAS Log in Clinical Programming |
Yuping Wu |
source |
4 |
| 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 |
Neoadjuvant and Adjuvant Oncology Clinical Trials and Considerations for Designing the Subject Level Analysis Dataset (ADSL) |
Madhusudhan Reddy Papasani,
Swathi Kotla,
Elisabeth Pyle |
source |
9 |
| 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 |
PROC FUTURE PROOF v1.1 - Linked Data |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee,
Jindřich Mynarz,
Danfeng Fu |
source |
12 |
| PharmaSUG |
2021 |
SEND for CBER |
Lisa Lin |
source |
26 |
| PharmaSUG |
2021 |
Shiny App for Generating Data Dependency Flowchart in ADRG |
Simiao Ye,
Yilong Zhang |
source |
8 |
| PharmaSUG |
2021 |
The Tortoise and the Hare - Lessons Learned in Developing ADaM Training |
Alyssa M. Wittle |
source |
6 |
| PharmaSUG |
2021 |
Types of Devices in Therapeutic Area User Guides |
Carey G. Smoak |
source |
7 |
| PharmaSUG |
2021 |
Using Stata for handling CDISC compliant datasets and outputs |
Tong Zhao,
Jin Shi |
source |
7 |
| PharmaSUG |
2021 |
Validation of CDISC specifications using VALSPEC utility macro |
Hrideep Antony,
Aman Bahl |
source |
8 |
| PharmaSUG |
2021 |
When Should I Break ADaM Rules? |
Sandra Minjoe |
source |
8 |
| PharmaSUG |
2021 |
Where-s Waldo? An SDTM Crawler |
Derek P. Morgan |
source |
9 |
| SGF |
2021 |
Analyzing Data Missing Due to COVID-19: From Raw Data to ADaM and Beyond |
Yuliia Bahatska |
source
presentation |
12 |
| PHUSE EU |
2020 |
A Collaborative Approach to Analysis Standards [presentation] |
Margie Merlino,
Marleen Nijs |
source
video |
22 |
| PHUSE EU |
2020 |
A SAS Solution to Compare Folders Instead of Single Datasets |
Guido Wendland |
source
video |
6 |
| PHUSE EU |
2020 |
ADaM is Back: The New ADaM IG 1.2 and Beyond |
Angelo Tinazzi |
source
video |
8 |
| PHUSE EU |
2020 |
Advancing SDTM Annotation Through Automation [presentation] |
Anja Kreis,
Wolfgang Rohnert |
source
video |
20 |
| PHUSE EU |
2020 |
Are We on the Same Page - Trial-level Metadata Based Upon Project Metadata [presentation] |
Bo Sølgaard Andersen,
Frederik Vandvig Heinen |
source
video |
18 |
| PHUSE EU |
2020 |
Best Practices for Annotated CRFs [poster] |
Amy Garrett |
source
video |
1 |
| PHUSE EU |
2020 |
Clean Data One Click Away: Using Backend Library Rules to Clean on SDTM Datasets |
Annelies Van Zeveren,
Glenn Borgmans |
source
video
presentation source |
46 |
| PHUSE EU |
2020 |
Data Integrity & Standards in the Clinical Data Pipeline [presentation] |
Mark Wheeldon,
Raj Indupuri |
source
video |
30 |
| PHUSE EU |
2020 |
Define-XML for ADaM: Clinical Standards Toolkit vs. Pinnacle 21? [presentation] |
Frederikke Høyer |
source
video |
16 |
| PHUSE EU |
2020 |
Defining Standards: Challenges and Solutions in the Development of Define-XML for SDTM and ADaM |
Sofia Vale |
source
video
poster source |
9 |
| PHUSE EU |
2020 |
Digital Data Flow - A Solution for Study Start-up and Amendments [presentation] |
Palanipandiyan Chokkalingam,
Srinivasan Mahalingam |
source
video |
22 |
| PHUSE EU |
2020 |
Don't UnderMine the Value of Your CRF - with Perl Regular Expressions [presentation] |
John McDade |
source
video |
22 |
| PHUSE EU |
2020 |
Effective Data Integrations [poster] |
Kirsty Wall,
Nicola Perry |
source
video |
1 |
| PHUSE EU |
2020 |
Flow Dependencies in ADaM Generation |
Ari Siggaard Knoph,
Jeppe Juul |
source
video
presentation source |
6 |
| PHUSE EU |
2020 |
Getting It Right: Refinement of SEND Validation Rules [presentation] |
Kristin Kelly |
source
video |
29 |
| 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 |
Guide to Electronic Submission of Pharmacometric Datasets and Analyses to the Regulatory Authorities [presentation] |
Pooja Kulkarni |
source
video |
17 |
| PHUSE EU |
2020 |
Handling Protocol Deviations - SDTM and ADaM [poster] |
Niels-Kristian Kjøller,
Tobias Kröpelin |
source
video |
1 |
| 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 |
Last Mile Problem to Manage Data Transformation for Analysis & Reporting [presentation] |
Deven Babre,
Rajaram Venkatesan |
source
video |
19 |
| 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 |
Metadata to Support ADaM Generation [presentation] |
Anne Katrine Alsing,
Jeppe Juul |
source
video |
14 |
| PHUSE EU |
2020 |
Novel eCRF Study Template to Support Adaptive Design Studies in Medidata Rave [presentation] |
Nele Claes,
Ray Lacchman |
source
video |
29 |
| 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 |
Please Take Care of Your Metadata |
Angelo Tinazzi |
source
video
poster source |
5 |
| PHUSE EU |
2020 |
Pooling lab data to support FDA submission: keep it clear and simple |
Joske van Schijndel |
source
video |
5 |
| PHUSE EU |
2020 |
Poster PP03 |
Roman Radelicki |
source
video
poster source |
8 |
| PHUSE EU |
2020 |
Replicating the CDISC Pilot Project Submission Project Using R and pharmaRTF [presentation] |
Michael Stackhouse |
source
video |
20 |
| 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 |
SDTM Mapping and Conversion Using ML/NLP [presentation] |
Eric Weising,
Farha Feroze |
source
video |
15 |
| PHUSE EU |
2020 |
SDTM: Let's Read Outside the Bible [presentation] |
Sandra Latorre |
source
video |
23 |
| PHUSE EU |
2020 |
Solving Hundreds of SDTM Validation Errors and Notices in One Click: Pinnacle 21 SD1082 and SD1078 Rules [poster] |
Antonio Nieto,
Sonia Extremera |
source
video |
1 |
| PHUSE EU |
2020 |
The Good? The Bad? Or the Ugly? CDISC eSubmission Packages in Practice [presentation] |
Artur Krupa |
source
video |
26 |
| PHUSE EU |
2020 |
The TransCelerate Hackathon: Accelerating Development [presentation] |
Johannes Ulander |
source
video |
26 |
| 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 |
| SESUG |
2020 |
Check the aCRF through Programming |
Hengwei Liu,
Daiichi Sankyo |
source |
12 |
| SGF |
2020 |
Statistical Programming in the Pharmaceutical Industry: Advancing and Accelerating Drug Development |
Harper Forbes |
source |
10 |
| PharmaSUG |
2020 |
'This Is Not the Date We Need. Let's Backdate': An Approach to Derive First Disease Progression Date in Solid Tumor Trials |
Girish Kankipati,
Boxun Zhang |
source |
11 |
| PharmaSUG |
2020 |
A Guide for the Guides: Implementing SDTM and ADaM standards for parallel and crossover studies |
Azia Tariq,
Janaki Chintapalli |
source |
1 |
| PharmaSUG |
2020 |
A Novel Solution for Converting Case Report Form Data to SDTM using Configurable Transformations |
Sara Shoemaker,
Matthew Martin,
Robert Kleemann,
David Costanzo,
Tobin Stelling |
source |
12 |
| PharmaSUG |
2020 |
A Solution to Look-Ahead Observations |
Yongjiang (Jerry) Xu,
Yanhua (Katie) Yu |
source |
5 |
| 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 |
Automate your Safety tables using Artificial Intelligence & Machine Learning |
Roshan Stanly,
Ajith Baby Sadasivan,
Limna Salim |
source |
8 |
| PharmaSUG |
2020 |
Automating CRF Annotations using Python |
Hema Muthukumar,
Kobie O'Brian,
Julie Stofel |
source |
9 |
| PharmaSUG |
2020 |
Automating of Two Key Components in Analysis Data Reviewer's Guide |
Shunbing Zhao,
Jeff Xia |
source |
8 |
| PharmaSUG |
2020 |
Automation of Conversion of SAS Programs to Text files |
Sachin Aggarwal,
Sapan Shah |
source |
8 |
| PharmaSUG |
2020 |
Butterfly Plot for Comparing Two Treatment Responses |
Raghava Pamulapati |
source |
13 |
| PharmaSUG |
2020 |
CDISC Standards for Medical Devices: Historical Perspective and Current Status |
Carey G. Smoak |
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 |
Creating SDTMs and ADaMs CodeList Lookup Tables |
Sunil Kumar Gupta |
source |
8 |
| PharmaSUG |
2020 |
Data Review: What's Not Included in Pinnacle 21? |
Jinit Mistry,
Lyma Faroz,
Hao Meng |
source |
7 |
| PharmaSUG |
2020 |
Data Transformation: Best Practices for When to Transform Your Data |
Janet E. Stuelpner,
Olivier Bouchard,
Mira Shapiro |
source |
4 |
| PharmaSUG |
2020 |
Demystifying SDTM OE, MI, and PR Domains |
Lyma Faroz,
Sruthi Kola |
source |
8 |
| PharmaSUG |
2020 |
End-to-end Prostate-Specific Antigen (PSA) Analysis in Clinical Trials: From Mock-ups to ADPSA |
Joy Zeng,
Varaprasad Ilapogu,
Xinping Cindy Wu |
source |
12 |
| PharmaSUG |
2020 |
Ensuring Consistency Across CDISC Dataset Programming Processes |
Jennifer K. Fulton |
source |
10 |
| PharmaSUG |
2020 |
Generating ADaM compliant ADSL Dataset by Using R |
Vipin Kumpawat,
Lalitkumar Bansal |
source |
9 |
| PharmaSUG |
2020 |
Getting It Right: Refinement of SEND Validation Rules |
Kristin Kelly |
source |
7 |
| PharmaSUG |
2020 |
Highlight changes: An extension to PROC COMPARE |
Abhinav Srivastva |
source |
4 |
| PharmaSUG |
2020 |
Impact of WHODrug B3/C3 Format on Coding of Concomitant Medications |
Lyma Faroz,
Jinit Mistry |
source |
6 |
| PharmaSUG |
2020 |
Improving the Quality of Define.xml: A Comprehensive Checklist Before Submission |
Ji Qi,
Yan Li,
Lixin Gao |
source |
8 |
| PharmaSUG |
2020 |
Is Your Dataset Analysis-Ready? |
Kapila Patel,
Nancy Brucken |
source |
10 |
| PharmaSUG |
2020 |
Metadata-driven Modular Macro Design for SDTM and ADaM |
Ellen (Zihui) Lin,
Aditya Tella,
Yeshashwini Chenna,
Michael Hagendoorn |
source |
9 |
| PharmaSUG |
2020 |
MKADRGM: A Macro to Transform Drug-Level SDTM Data into Traceable, Regimen-Level ADaM Data Sets |
Sara McCallum |
source |
34 |
| PharmaSUG |
2020 |
Moving A Hybrid Organization Towards CDISC Standardization |
Kobie O'Brian,
Sara Shoemaker,
Robert Kleemann,
Kate Ostbye |
source |
8 |
| PharmaSUG |
2020 |
Natural History Study - A Gateway to Treat Rare Disease |
Tabassum Ambia |
source |
5 |
| PharmaSUG |
2020 |
Next Level Programming-Reusability and Importance of Custom Checks |
Akhil Vijayan,
Limna Salim |
source |
9 |
| PharmaSUG |
2020 |
Overcoming Pitfalls of DS: Shackling the 'Elephant in the room' |
Soumya Rajesh,
Michael Wise |
source |
9 |
| PharmaSUG |
2020 |
Pinnacle 21 Community v3.0 - A Users Perspective |
Ajay Gupta |
source |
10 |
| PharmaSUG |
2020 |
Preparing a Successful BIMO Data Package |
Elizabeth Li,
Carl Chesbrough,
Inka Leprince |
source |
20 |
| PharmaSUG |
2020 |
PROC Future Proof; |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee |
source |
8 |
| PharmaSUG |
2020 |
Project Metrics - a powerful tool that supports workload management and resource planning for Biostats & Programming department. |
Jian Hua (Daniel) Huang,
Rajan Vohra,
Andy Chopra |
source |
11 |
| PharmaSUG |
2020 |
Remove Strikethrough Texts from Excel Documents by VBA Macro |
Li Liu |
source |
5 |
| PharmaSUG |
2020 |
SDSP: Sponsor and FDA Liaison |
Bhanu Bayatapalli,
Shefalica Chand |
source |
8 |
| PharmaSUG |
2020 |
SDTM to ADaM Programming: Take the Leap! |
Jennifer McGrogan,
Alyssa M. Wittle |
source |
5 |
| PharmaSUG |
2020 |
Shell Script automation for SDTM/ADaM and TLGs |
Pradeep Acharya,
Aniket Patil |
source |
6 |
| PharmaSUG |
2020 |
Simplifying PGx SDTM Domains for Molecular biology of Disease data (MBIO). |
Sowmya Srinivasa Mukundan,
Charumathy Sreeraman |
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 |
Standardised MedDRA Queries (SMQs): Programmers Approach from Statistical Analysis Plan (SAP) to Analysis Dataset and Reporting |
Sumit Pratap Pradhan |
source |
18 |
| PharmaSUG |
2020 |
Successful US Submission of Medical Device Clinical Trial using CDISC |
Phil Hall |
source |
6 |
| PharmaSUG |
2020 |
Supplementary Steps to Create a More Precise ADaM define.xml in Pinnacle 21 Enterprise |
Majdoub Haloui,
Hong Qi |
source |
10 |
| PharmaSUG |
2020 |
SUPPQUAL Datasets: Good Bad and Ugly |
Sergiy Sirichenko |
source |
14 |
| PharmaSUG |
2020 |
Tackle Oncology Dose Intensity Analysis from EDC to ADaM |
Song Liu,
Mijun Hu,
Jieli Fang,
Cindy Q. Song,
Quting Zhang |
source |
7 |
| 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 |
Text Wrangling with Regular Expressions: A Short Practical Introduction |
Noory Y. Kim |
source |
7 |
| PharmaSUG |
2020 |
Transpose Procedure: Turning it Around Again |
Janet E. Stuelpner |
source |
8 |
| PharmaSUG |
2020 |
Trial Sets in Human Clinical Trials |
Fred Wood |
source |
13 |
| PharmaSUG |
2020 |
Untangling the Subject Elements Domain |
Christine McNichol |
source |
8 |
| PharmaSUG |
2020 |
Updates in SDTM IG V3.3: What Belongs Where - Practical Examples |
Lucas Du,
William Paget,
Lingyun Chen,
Todd Case |
source |
8 |
| PharmaSUG |
2020 |
Why Are There So Many ADaM Documents, and How Do I Know Which to Use? |
Sandra Minjoe |
source |
10 |
| PHUSE US |
2020 |
A Collaborative Approach to Analysis Standards |
Margaret Merlino,
Marleen Nijs |
source
poster source |
5 |
| PHUSE US |
2020 |
ADaM Data in High Definition |
Varia Cartledge |
source
presentation source |
12 |
| PHUSE US |
2020 |
An automated code translation approach in SDTM specifications using %translate macro |
Hrideep Antony |
source
presentation source |
7 |
| PHUSE US |
2020 |
An Update on CDISC-SEND Data Submissions to FDA |
Jesse Anderson,
Christopher Bartlett,
Jennifer Feldmann,
Valerie Gross,
Alejandro Mankin,
Qingying Lu,
Kathryn Matto,
Lilliam Rosario |
source
presentation source |
7 |
| PHUSE US |
2020 |
Automating Module 5 Packaging with Customizable Metadata |
Dhananjay Chhatre,
Kevin Miller |
source
presentation source |
6 |
| PHUSE US |
2020 |
Automating the Analysis Data Reviewer's Guide (ADRG) in Early-stage Development Studies |
Jing Su,
Pranab K. Mitra |
source |
5 |
| PHUSE US |
2020 |
Automation of Submission Packages Quality Checks |
Sendil K. Ramabadran,
Anne-Sophie Bekx |
source
poster source |
6 |
| PHUSE US |
2020 |
Be the Master for a Master Protocol Study |
Ke Xiao |
source
poster source |
8 |
| PHUSE US |
2020 |
Building a Deeper Bench: Writing ADaM Specifications |
Kristen Reece Harrington,
Shane Rosanbalm |
source
presentation source |
3 |
| PHUSE US |
2020 |
Case Study: Integrated SDTM to Integrated ADaM to TLFs |
Kishore Pothuri |
source
presentation source |
6 |
| PHUSE US |
2020 |
CDISC 360: Using Biomedical Concept Metadata to Generate Case Report Forms and Dataset Definitions |
Samuel Hume |
source
presentation source |
13 |
| PHUSE US |
2020 |
CDISC Implementation Primer |
Bess LeRoy,
Rebecca Baker |
source |
5 |
| PHUSE US |
2020 |
CDISC Library Try-out: From Implementation to Evaluation of the API |
Roman Radelicki |
source
presentation source |
9 |
| 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 |
Challenges and Solutions While Mapping Laboratory Data [poster] |
Ratheesh Gunda |
source |
1 |
| PHUSE US |
2020 |
Common Data Quality Issues Seen During FDA's JumpStart Service |
Aaron Belowich,
Andrea Arbelaez |
source
presentation source |
7 |
| PHUSE US |
2020 |
Complexities in Adhering to Data Standards for ISS NDA Submissions |
Vidya Muthukumar |
source
presentation source |
3 |
| PHUSE US |
2020 |
Confusing Data Validation Rules Explained, Part 2 |
Michael Beers,
Blue Bell |
source |
6 |
| PHUSE US |
2020 |
Data Compliance: Hidden Benefits |
Priyanka Adusumilli |
source |
3 |
| PHUSE US |
2020 |
Data Exchange in Clinical Trial - Programming Perspective |
Chao Wang |
source
presentation source |
5 |
| 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 |
Developing SEND for CBER - Collaborative Workstream Initiative Update |
Lisa Lin,
Susan DeHaven |
source
presentation source |
6 |
| PHUSE US |
2020 |
Documentation, Applicability and Automation: How Best Practices Can Help You Achieve Best Results |
Aadesh Shah |
source
presentation source |
7 |
| PHUSE US |
2020 |
Early Detection and Prevention of Compliance Issues |
Vara Prasad Reddy Sakampally |
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 |
Feature of SDTM Mapping and Conversion Using NLP |
Eric Weising,
Shiva Katepalli |
source
presentation source |
3 |
| PHUSE US |
2020 |
Getting It Right: Refinement of SEND Validation Rules |
Kristin Kelly,
Blue Bell |
source
presentation source |
6 |
| PHUSE US |
2020 |
Giving Back to the Community - Managing CDISC Terminology |
Dorte Straarup |
source
poster source |
1 |
| PHUSE US |
2020 |
Handling Duplicate Records in SDTM for Effective Resolution and Explanation in Data Submission |
Varun Debbeti |
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 |
Industry Experiences Submitting Standardized Study Data to Regulatory Authorities |
Janet Low,
Vincent Guo |
source
presentation source |
12 |
| 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 |
Let your SDTM or ADaM SAS code update itself whenever the Specs change |
Joseph W. Hinson |
source
presentation source |
8 |
| PHUSE US |
2020 |
Leveraging Metadata for SDTM QC Automation |
Sunil Kumar Gupta |
source
presentation source |
5 |
| PHUSE US |
2020 |
Leveraging Python to Generate Define-XML v2.0 |
Kevin Miller,
Larry Sleeper |
source |
5 |
| PHUSE US |
2020 |
Machine Learning for CDISC Specification Recommendations |
S. Preston Burns |
source
presentation source |
7 |
| PHUSE US |
2020 |
Machine Learning-AI is the Future - What Now? |
Priyanka Adusumilli,
Priyank Patel |
source
poster source |
8 |
| 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 |
Mind the Gap: Raw Data Model |
Julie Smiley |
source
presentation source |
7 |
| PHUSE US |
2020 |
Poster - PP23 |
Mike Tan,
Richard Addy,
Deidre Kreifels |
source
poster source |
9 |
| PHUSE US |
2020 |
Real-time Oncology Review - Applicant Experience |
Annie Varghese |
source
presentation source |
5 |
| PHUSE US |
2020 |
Standardization = Automation: A Journey from Dataset Specification to SAS Code |
Anastasiia Khmelnytska |
source
presentation source |
11 |
| PHUSE US |
2020 |
SUPPQUAL Datasets: Good Bad and Ugly |
Sergiy Sirichenko,
Blue Bell |
source
presentation source |
13 |
| PHUSE US |
2020 |
The Elusive Goal of Automation in SDTM Mapping: A CRO perspective |
Sridhar Vijendra,
Ephicacy Lifescience |
source
presentation source |
6 |
| PHUSE US |
2020 |
The JumpStart Traceability Assessment |
Tejas Patel,
Sarah Ferkov |
source |
10 |
| PHUSE US |
2020 |
The Misery of the Miscellaneous Folder in Module 5 |
Marguerite Kolb |
source
presentation source |
8 |
| PHUSE US |
2020 |
Untangling the Subject Elements Domain |
Christine McNichol |
source
presentation source |
7 |
| PHUSE US |
2020 |
Using Standardization and Automation to Streamline Generation of SDTM/ADaM Codelists |
Eric Du |
source |
6 |
| PHUSE US |
2020 |
Validation Consistency and Conformance Checking of SEND Datasets |
Isaac Mativo,
Mohit Matthew |
source
presentation source |
6 |
| PHUSE US |
2020 |
Virtual Assistant for Conversational Experience with Clinical Data |
Amit Gulwadi,
Srinivasan Anandakumar |
source |
6 |
| 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 |
ADaM Programming Made Easy - Common ADaM Templates and an SAS Macro Library |
Niels-Kristian Kjøller |
source
poster source |
4 |
| PHUSE EU |
2019 |
ADaM Submission - How to Work with the Inconsistencies Between the FDA and PMDA Requirements |
Marianne Carames |
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 |
An Introduction to Python: The SAS Programmer's Guide |
Bradley Harris |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Automating the blankcrf.pdf and define.xml with your database build |
John McDade |
source
poster source |
6 |
| PHUSE EU |
2019 |
Basics of Dataset Integration |
Pradeep Kumar |
source
presentation source |
4 |
| PHUSE EU |
2019 |
CDISC 360: Continuing the Journey Towards End-to-End Automation |
Peter Van Reusel |
source
presentation source |
3 |
| PHUSE EU |
2019 |
Challenges Involved with Using Legacy Clinical Trial Study Data During Integration |
Adebola Opasanya |
source
poster source |
8 |
| PHUSE EU |
2019 |
Choosing the Right Path to Follow When Integrating ADaM |
Magalie Gallet,
Laura Phelan |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Considerations When Representing Multiple Subject Enrollments in SDTM |
Kristin Kelly,
Blue Bell |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Deconstructing SDTM - Starting Again |
Johannes Ulander |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Define.xml Review: Failing to Plan is Planning to Fail |
Robin Mann,
Parvee Kumar |
source
presentation source |
15 |
| PHUSE EU |
2019 |
Development of standard BIMO process to create clinsite dataset |
Hilde Delanghe |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Don't cha wish your tracker was clean like mine? |
Anisa Jeetoo |
source
presentation source |
8 |
| 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 |
End-to-end SDTM Automation: A Metadata-centric Approach (winner) |
Roman Radelicki |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Fake it Till You Make it with Global SDTM Laboratory Submissions [presentation] |
Éanna Kiely |
source |
31 |
| PHUSE EU |
2019 |
Formedix On: Advanced Metadata Management and Data Conversion [presentation] |
Kevin Burges |
source |
47 |
| PHUSE EU |
2019 |
Harmonising SDTM at the Source: Two Years Later |
Helen Scanlon,
Sue Huxtable |
source
presentation source |
11 |
| PHUSE EU |
2019 |
How Can We Ensure Our Study Data is F.A.I.R. (Findable, Accessible, Interoperable and Reusable)? |
Alana Harris |
source
presentation source |
4 |
| PHUSE EU |
2019 |
How to use SUPPQUAL for specifying natural key variables in define.xml? |
Sergiy Sirichenko,
Blue Bell |
source
presentation source |
8 |
| PHUSE EU |
2019 |
How Will You Use CDISC Library? |
Sally Cassells |
source
presentation source |
6 |
| PHUSE EU |
2019 |
Implementation of SDTM IG v.3.3 for Neurological Therapeutic Area |
Daryna Khololovych |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Implementing the CDISC Library API in Software Applications: First Experiences |
Jozef Aerts |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Lessons Learned from an FDA Real-time Oncology Review Pilot Programme: A Novartis & Roche Perspective |
Delphine Kerzerho,
Hiren Naygandhi |
source
presentation source |
10 |
| PHUSE EU |
2019 |
Macro-enabled Trial Design Domain Specification Template [poster] |
Chintankumar Patel |
source |
1 |
| PHUSE EU |
2019 |
Making data mapping process easier and smarter with SAS and R |
Andrii Artemchuk |
source
presentation source |
10 |
| PHUSE EU |
2019 |
Mapping Raw Data to SDTM Define Using the SAS Clinical Standards Toolkit |
Andrew Bullivant |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Medical Device SDTM: A Real Case |
Roberto Teli |
source
poster source |
5 |
| PHUSE EU |
2019 |
Navigating FDA Requirements: ISS/ISE Build Strategies |
Priyank Patel |
source |
9 |
| PHUSE EU |
2019 |
Onboarding a Junior Statistical Programmer in 10 Weeks: My Story, from University to First Analysis Delivery |
Pieter Coppens,
Annelies Van Zeveren |
source
presentation source |
6 |
| PHUSE EU |
2019 |
PHUSE CDISC Implementation Primer Project Overview and Update |
Beate Hientzsch,
Nick De Donder |
source
poster 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 |
Programming in the World of PK: Guidance for the Beginner |
Paige Lewis |
source
poster source |
7 |
| PHUSE EU |
2019 |
Quality Control and Validation - More Than Just PROC COMPARE |
Evgeny Starostin |
source
poster source |
7 |
| PHUSE EU |
2019 |
SDTM Validation Tool |
Anamaria Calai |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Semi Auto-generated Narratives |
Bjarke Klein |
source
presentation source |
7 |
| PHUSE EU |
2019 |
The Trials and Tribulations of Automated SDTM Delivery |
Edward R. Jones |
source
presentation source |
5 |
| 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 |
Use of FHIR in Clinical Research: From Electronic Medical Records to Analysis |
Jeffrey M. Abolafia,
Priya Gopal,
Samuel Hume |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Validating a CDISC Dataset at Development Time Using Pinnacle 21 CLI via SAS |
David W. Meek |
source
presentation source |
8 |
| PHUSE EU |
2019 |
VBA for CRT, Automating the Master Spec |
Matt Metherell |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Work Less - Do More: An Automated Approach to Define-XML Validation |
Kai Wanke |
source
presentation source |
8 |
| SESUG |
2019 |
Cutting Out the Middle Man - Bypassing ADaM to Calculate Tumor Response Inputs using RECIST 1.1 Guidelines and Collected Data in SDTM Format |
Response Inputs |
source |
6 |
| SESUG |
2019 |
ePRO: A View from Statistical Programmer |
Vijetha Kode,
Saigovind Chenna |
source |
18 |
| SESUG |
2019 |
One Click to Analysis Results Metadata |
Srivathsa Ravikiran,
Priscilla Gathoni |
source |
18 |
| MWSUG |
2019 |
Findings About: De-mystifying the When and How |
Michael Wise,
Soumya Rajesh |
|
9 |
| MWSUG |
2019 |
Timing is Everything: Defining ADaM Period, Subperiod and Phase |
Nancy Brucken |
|
7 |
| WUSS |
2019 |
A Strategy for Dealing with Pinnacle 21 Errors and Warnings |
Carey G. Smoak |
source |
2 |
| WUSS |
2019 |
Automating ADSL Programming Using Pinnacle 21 Specifications |
Tracy Sherman,
Aakar Shah |
source |
12 |
| WUSS |
2019 |
Root Cause Analysis Using Pinnacle 21 Validation Reports: How to Improve End-to-End Programming Process |
Aakar Shah,
Tracy Sherman |
source |
13 |
| PharmaSUG |
2019 |
A Practical Guide to the Issues Summary in the Data Conformance Summary of Reviewer's Guides |
Gary E. Moore |
source |
15 |
| PharmaSUG |
2019 |
A SAS and VBScript cyborg to send emails effectively. |
Nikita Sathish |
source |
6 |
| PharmaSUG |
2019 |
Achieving Zen: A Journey to ADaM Compliance |
Kirsty R. Lauderdale,
Kjersten Offenbecker,
Alice Ehmann |
source |
7 |
| PharmaSUG |
2019 |
ADaM 1.1 Compliant ADEVENT and ADTTE development in a Cardiovascular Study |
Chao Su |
source |
6 |
| PharmaSUG |
2019 |
ADME Study PK SDTM/ADaM And Graph |
Fan Lin |
source |
9 |
| PharmaSUG |
2019 |
An Application of Supervised Machine Learning Models on Natural Language Processing: Classifying QC Comments into Categories |
Xiaoyu Tang,
Todd Case |
source |
10 |
| PharmaSUG |
2019 |
An Automated, Metadata Approach to Electronic Dataset Submissions |
Janette Garner |
source |
8 |
| PharmaSUG |
2019 |
Auto-Annotate Case Report Forms with SAS and SAS XML Mapper |
Yating Gu |
source |
7 |
| PharmaSUG |
2019 |
Auto-generation of Clinical Laboratory Unit Conversions |
Alan Meier |
source |
9 |
| 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 |
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 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2019 |
Bidirectionality to LOINC: Handling the Nitty Gritty of Lab Data |
Bhargav Koduru |
source |
8 |
| PharmaSUG |
2019 |
Clinical Development Standards for FDA Bioresearch Monitoring (BIMO) Submissions |
Denis Michel,
Julie Maynard |
source |
11 |
| PharmaSUG |
2019 |
Common Pinnacle 21 Report Issues: Shall we Document or Fix? |
Ajay Gupta |
source |
11 |
| PharmaSUG |
2019 |
Compare and conquer SDTM coding |
Phaneendhar Gondesi |
source |
5 |
| PharmaSUG |
2019 |
Considerations and Updates in the Use of Timing Variables in Submitting SDTM-Compliant Datasets |
Jerry Salyers |
source |
9 |
| PharmaSUG |
2019 |
Considerations in Effectively Generating PK Analysis Input Datasets |
Jianli Ping |
source |
10 |
| PharmaSUG |
2019 |
Considerations When Representing Multiple Subject Enrollments in SDTM |
Kristin Kelly,
Mike Hamidi |
source |
8 |
| PharmaSUG |
2019 |
Dataset Specifications: Recipes for Efficiency and Quality |
David A. Scocca |
source |
7 |
| 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 Analysis & Reporting Standards For Pharmaco-Epidemiology Observational Studies |
Bo Zheng,
Xingshu Zhu |
source |
5 |
| 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 |
Experiences in Building CDISC Compliant ADaM Dataset to Support Multiple Imputation Analysis for Clinical Trials |
Xiangchen (Bob) Cui |
source |
20 |
| PharmaSUG |
2019 |
Exploring Common CDISC ADaM Conformance Findings |
Trevor Mankus |
source |
6 |
| PharmaSUG |
2019 |
Findings About: De-mystifying the When and How |
Soumya Rajesh,
Michael Wise |
source |
9 |
| PharmaSUG |
2019 |
Forewarned is forearmed or how to deal with ADSL issues |
Anastasiia Oparii |
source |
16 |
| PharmaSUG |
2019 |
Have You Met Define.xml 2.0? |
Christine McNichol |
source |
15 |
| PharmaSUG |
2019 |
Homogenizing Unique and Complex data into Standard SDTM Domains with TAUGs |
Sowmya Srinivasa Mukundan,
Charumathy Sreeraman |
source |
10 |
| PharmaSUG |
2019 |
How to use SUPPQUAL for specifying natural key variables in define.xml? |
Sergiy Sirichenko |
source |
8 |
| PharmaSUG |
2019 |
Implementing CDISC Standards for Device-Drug Studies |
Karin LaPann,
Wenying Tian |
source |
10 |
| PharmaSUG |
2019 |
Implementing Laboratory Toxicity Grading for CTCAE Version 5 |
Keith Shusterman,
Mario Widel |
source |
11 |
| PharmaSUG |
2019 |
Incremental Changes: ADaMIG v1.2 Update |
Nancy Brucken,
Brian Harris,
Terek Peterson,
Alyssa Wittle,
Deborah Goodfellow |
source |
8 |
| PharmaSUG |
2019 |
Information Requests During An FDA Review |
Hong Qi,
Lei Xu,
Mary N. Varughese |
source |
8 |
| PharmaSUG |
2019 |
Interactive TLFs - A Smarter Way to Review your Statistical Outputs |
Bhavin Busa |
source |
5 |
| PharmaSUG |
2019 |
ISS Challenges and Solutions for a Compound with Multiple Submissions in Parallel |
Aiming Yang |
source |
4 |
| PharmaSUG |
2019 |
Joining the SDTM and the SUPPxx Datasets |
David W. Franklin |
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 |
Leveraging Intermediate Data Sets to Achieve ADaM Traceability |
Yun (Julie) Zhuo |
source |
12 |
| PharmaSUG |
2019 |
Making Lab Toxicity Tables Less Toxic on Your Brain |
Lindsey Xie,
Jinlin Wang,
Jennifer Sun,
Rita Lai,
Richann J. Watson |
source |
13 |
| PharmaSUG |
2019 |
More Traceability: Clarity in ADaM Metadata and Beyond |
Wayne Zhong,
Richann J. Watson,
Daphne E. Ewing,
Jasmine Zhang |
source |
26 |
| 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 |
Pharmacokinetic Parameters for Sparse and Intensive Sampling - Nonclinical and Clinical Studies |
Shallabh Mehta |
source |
5 |
| PharmaSUG |
2019 |
Practical Guidance for ADaM Dataset Specifications and Define.xml |
Jack Shostak |
source |
14 |
| PharmaSUG |
2019 |
Practical Guide for Creating ADaM Datasets in Cross-over Studies |
Neha Sakhawalkar,
Kamleshkumar Patel |
source |
10 |
| PharmaSUG |
2019 |
Practices in CDISC End-to-End Streamlined Data Processing |
Chengxin Li |
source |
14 |
| PharmaSUG |
2019 |
Process optimization for efficient and smooth e-data submissions to both FDA and PMDA |
Eri Sakai,
Malla Reddy Boda,
Akari Kamitani,
Yoshitake Kitanishi |
source |
13 |
| PharmaSUG |
2019 |
Programmatically mapping source variables to output SDTM variables based upon entries in a standard specifications Excel file |
Frederick A. Cieri,
Rama Arja,
Zev Kahn,
Ramesh Karuppusamy |
source |
16 |
| PharmaSUG |
2019 |
Progression-Free Survival (PFS) Analysis in Solid Tumor Clinical Studies |
Na Li |
source |
14 |
| PharmaSUG |
2019 |
Project Management Fundamentals for Programmers and Statisticians |
Jennifer Sniadecki |
source |
19 |
| PharmaSUG |
2019 |
Raising the Bar: CDASH implementation in a biometrics CRO |
Julie Barenholtz |
source |
4 |
| 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 |
Streamlining the Metadata Management Process Using SAS Life Science Analytics Framework |
Alex Ford |
source |
6 |
| PharmaSUG |
2019 |
Sum Fun with Flags! Sum Any Flagged Occurrence Data with FLAGSUM and Report It with FLAGRPT or PROC REPORT. |
Brendan Bartley |
source |
31 |
| PharmaSUG |
2019 |
Tame Your SHARE with a Python and SAS |
Michael Stackhouse,
Terek J. Peterson |
source |
6 |
| PharmaSUG |
2019 |
Text Analysis of QC/Issue Tracker Using Natural Language Processing (NLP) Tools |
Huijuan Zhang,
Todd Case |
source |
8 |
| 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 |
Time to COMPARE Programmer to Analyst: Examine the Differences and Decide Best Path Forward |
Ginger Barlow,
Carol Matthews |
source |
8 |
| PharmaSUG |
2019 |
Timing is Everything: Defining ADaM Period, Subperiod and Phase |
Nancy Brucken |
source |
7 |
| PharmaSUG |
2019 |
Tool Development Methods for Implementing and Converting to New Controlled Terminology in SDTM datasets |
Martha O'Brien,
Keith Shusterman |
source |
10 |
| PharmaSUG |
2019 |
Updates on validation of ADaM data |
Sergiy Sirichenko |
source |
9 |
| PharmaSUG |
2019 |
Useful SAS techniques in Efficacy Analysis for Oncology studies |
Joy Zeng |
source |
21 |
| PharmaSUG |
2019 |
Using CDISC Standards with an MDR for EDC to Submission Traceability |
Paul K. Slagle,
Eric Larson |
source |
4 |
| PharmaSUG |
2019 |
Using Pinnacle 21 Enterprise for define.xml Creation: Tips and Tricks from a CRO Perspective. |
Franklin E. Menius |
source |
14 |
| PharmaSUG |
2019 |
Validating Hyperlinks in SDTM define.xml Using Python |
Brandon L. Welch,
Gregory Weller |
source |
8 |
| PharmaSUG |
2019 |
Value-Level Metadata Done Properly |
Sandra Minjoe,
Mario Widel |
source |
21 |
| PharmaSUG |
2019 |
Vendor's Guide to Consistent, Reliable, and Timely CDISC Deliverables |
Dharmendra Tirumalasetti,
Santosh Reddy Lekkala,
Bhavin Busa |
source |
5 |
| PharmaSUG |
2019 |
What-s New in the SDTMIG v3.3 and the SDTM v1.7 |
Fred Wood |
source |
13 |
| PharmaSUG |
2019 |
When biomarker drives primary endpoint: An oncology case study of SDTM design using multiple myeloma. |
Girish Kankipati,
Bhargav Koduru |
source |
5 |
| PHUSE US |
2019 |
A Linked Data Model and Hypermedia API for CDISC Share 2.0 |
Samuel Hume,
Frederik Malfait |
source |
12 |
| 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 |
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 |
An Overview of the PHUSE ML/AI Working Group Project |
Sairam Gorthi,
Kevin Lee |
source
presentation source |
4 |
| PHUSE US |
2019 |
Approach of Programming Production Harmonized with Submission |
Chengxin Li |
source
presentation source |
6 |
| PHUSE US |
2019 |
Best Practices for the Preparation of the ISS/ISE Datasets [poster] |
Aatiya Zaidi,
Bhavin Busa |
source |
1 |
| PHUSE US |
2019 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source
presentation source |
3 |
| 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 |
Check Your Data: Tools for Automating Data Assessment |
Paul Stutzman |
source
presentation source |
10 |
| PHUSE US |
2019 |
Code Generator to Verify Implementation of Cut-off Date |
Christine S Teng |
source
presentation source |
4 |
| PHUSE US |
2019 |
Compliance Report for Patient Reported Outcomes |
Shu-Ching,
Christine S Teng |
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 |
Creation of Define-XML v2.0 Using SAS Program and Pinnacle 21 |
Yan Lei,
Yongjiang Xu |
source
presentation source |
10 |
| PHUSE US |
2019 |
Developing SEND for CBER - Collaborative Workstream Initiative |
Lisa Lin,
Susan DeHaven |
source
presentation source |
6 |
| PHUSE US |
2019 |
Developing, Implementing and Governing End-to-End Standards at Gilead |
Dhananjay Chhatre |
source
presentation source |
5 |
| 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 |
DR3 - A Tool to Create Define-XML (SDTM/ADaM with ARM) [presentation] |
Eric Weising |
source |
7 |
| PHUSE US |
2019 |
Dynamically Harvesting Study Dates to Construct and QC the Subject Visits (sv) SDTM Domain |
Laura Bellamy,
Cleopatra Deleon |
source
presentation source |
6 |
| PHUSE US |
2019 |
Effective Presentations of CTCAE-graded Laboratory Data |
William Coar,
Amber Randall |
source
presentation source |
7 |
| PHUSE US |
2019 |
End-to-End SDTM Automation: A Metadata-centric Approach |
Roman Radelicki,
Swapna Pothula |
source
presentation source |
12 |
| 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 |
Evolving CDISC to the Next Decades: The CDISC Proof of Concept |
Peter Van Reusel,
Samuel Hume |
source
presentation source |
3 |
| PHUSE US |
2019 |
Expectations and Collaboration - Recipe for Successful CDISC Deliverables! |
Santosh Reddy Lekkala,
Bhavin Busa |
source
presentation source |
4 |
| PHUSE US |
2019 |
Formedix On: Advanced Metadata Management Now With Data! [presentation] |
Kevin Burges,
Steven Benham |
source |
45 |
| PHUSE US |
2019 |
From Source Data to SDTM: Enabling a Semi-automated Conversion |
Pieter Blomme |
source
presentation source |
4 |
| PHUSE US |
2019 |
Have You Ever Wanted to Join a CDISC Team? |
Amy Palmer |
source
poster source |
1 |
| PHUSE US |
2019 |
Have You Met Define-XML v2.0? |
Christine McNichol |
source
presentation source |
12 |
| PHUSE US |
2019 |
High-quality Study Data Standards for Submission |
Majdoub Haloui,
Ellen L. Asam |
source
presentation source |
9 |
| PHUSE US |
2019 |
Identifying Hurdles for Submission of Electronic Nonclinical Data (SEND) |
Bob Friedman,
Lou Ann Kramer |
source
presentation source |
10 |
| PHUSE US |
2019 |
Impact of SEND Data on FDA Review of Nonclinical Studies |
Kevin Snyder,
Matthew Whittaker |
source
presentation source |
6 |
| PHUSE US |
2019 |
Implementing Imputation Rules and Creating Analysis Flags Following CDISC Guidelines |
Venkata Madhira,
Harish Yeluguri |
source
presentation source |
8 |
| PHUSE US |
2019 |
Incremental Changes: ADaMIG v1.2 Update |
Brian Harris,
Deborah Goodfellow |
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 |
Interactive Monitoring of Hepatotoxicity |
Susan Duke |
source
presentation source |
10 |
| PHUSE US |
2019 |
Interactive Visualization of SEND Clinical Pathology Data Using R Shiny |
Kevin Snyder |
source
presentation source |
8 |
| PHUSE US |
2019 |
Interpreting CDISC Standards for Device-drug Studies |
Karin LaPann,
Wenying Tian |
source
presentation source |
9 |
| PHUSE US |
2019 |
Let's Create Standard Value-level Metadata |
David A. Fielding |
source
presentation source |
8 |
| PHUSE US |
2019 |
Managing Complexity Towards Submission |
Johannes Ulander |
source
presentation source |
26 |
| PHUSE US |
2019 |
Mapping Programs - Written by MDR |
Jörn Bilow |
source
presentation source |
2 |
| PHUSE US |
2019 |
Metadata Framework for Script Repository and Development |
Vara Prasad Reddy Sakampally,
Hanming Tu |
source
poster source |
10 |
| PHUSE US |
2019 |
Metadata-based Auto-Programming Process - Part 2: Map Human Language to SAS Code by Natural Language Processing (NLP) |
Sumesh Kalappurakal,
Harry Chen |
source
presentation source |
11 |
| PHUSE US |
2019 |
Metadata-driven Automation in Drug Research |
Hanming Tu,
Zhongping Lin |
source
presentation source |
13 |
| PHUSE US |
2019 |
Modeling Safety Pharmacology Study Designs in SEND: An Analysis of a Proof-of-Concept Dataset |
Kevin Snyder |
source
presentation source |
5 |
| PHUSE US |
2019 |
Next Generation Data Management: Case Studies for Ontology-driven Graph Databases |
Jim Lapointe |
source
presentation source |
8 |
| PHUSE US |
2019 |
Remotely Manage Your Team's Time and Tasks Efficiently |
Vara Prasad Reddy Sakampally |
source
presentation source |
5 |
| PHUSE US |
2019 |
Removing Silos: Placing Data at the Center |
David Iberson-Hurst |
source
presentation source |
9 |
| PHUSE US |
2019 |
Simplifying P21 Process for Define Creation |
Ghanshyam Jangid |
source
presentation source |
5 |
| PHUSE US |
2019 |
Simplifying the Integration Riddle |
Deepak Ananthan,
Karthik Raja Subbiah |
source
presentation source |
6 |
| PHUSE US |
2019 |
Stay Relaxed... A Utility to Auto-create Specification! |
Kaveri Pachiappan |
source
poster source |
7 |
| PHUSE US |
2019 |
Streamline Process: To Generate SDTM Programs by Automation |
Hemalatha Elumalai |
source
poster source |
8 |
| 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 |
Take Advantage of CDISC Standards and Plan Your Study Specifications File |
Vara Prasad Reddy Sakampally,
Siddarth Lokineni |
source
poster source |
6 |
| PHUSE US |
2019 |
Tame Your SHARE with a Python and SAS |
Terek J. Peterson,
Michael Stackhouse |
source
poster source |
5 |
| PHUSE US |
2019 |
The Benefits, Challenges and Myths of SEND |
Bill Houser,
Lou Ann Kramer |
source
presentation source |
8 |
| PHUSE US |
2019 |
The Importance of Work Instructions When Creating Reviewer's Guides |
Jennifer McGrogran |
source
poster source |
8 |
| 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 |
Today's Standards Governance: Getting a Boost from Leveraging an MDR |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE US |
2019 |
Use of FHIR in Clinical Research: From Electronic Medical Records to Analysis |
Priya Gopal |
source
presentation source |
12 |
| PHUSE US |
2019 |
Using an MDR to Manage Your Lab Test Definitions |
Daniel Ringenbach,
Roopa Kandukuri |
source
presentation source |
7 |
| PHUSE US |
2019 |
Using CDISC-SEND Standardized Data in FDA Toxicology Review: The KickStart Service |
Jesse Anderson,
Christopher Bartlett |
source |
4 |
| PHUSE US |
2019 |
Using Pinnacle 21 Enterprise for define.xml Creation: Tips and Tricks from a CRO Perspective. |
Franklin E. Menius |
source
presentation source |
12 |
| 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 |
| SCSUG |
2018 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
source |
8 |
| PHUSE EU |
2018 |
A Critique of the Use of the Medical Device SDTM Domains in the Therapeutic Area User Guides |
Carey G. Smoak |
source
presentation source |
8 |
| 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 |
A Proprietary CDASH/SDTM-hybrid Data Model to Expedite Clinical Data Review |
Lieke Gijsbers,
Tom Van Der Spiegel |
source
presentation source |
6 |
| PHUSE EU |
2018 |
AI-powered Xbiom 3.1 Smart Curation & Transformation of Data [presentation] |
Kurien Abraham,
Nicolas Philippe |
source |
12 |
| PHUSE EU |
2018 |
Automated Creation of Submission-Ready Artifacts [presentation] |
Silas McKee,
Lourdes Devenney |
source |
15 |
| PHUSE EU |
2018 |
Automating SDTM - Get it Prepared with Your Voice |
Akhil Vijayan,
Anoop Ambika |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Best Practice for Explaining Validation Results in the Study Data Reviewer's Guide |
Kristin Kelly,
Michael Beers |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Can You Cut It? Implementing the Data Cut-off |
Lewis Meares |
source
presentation source |
9 |
| PHUSE EU |
2018 |
CDISC SDTM Data Automation Tool |
Brinitha Sathyabhama |
source
presentation source |
6 |
| PHUSE EU |
2018 |
CDISC Standards: Creating Clarity Out of Confusion [presentation] |
Kit Howard |
source |
20 |
| PHUSE EU |
2018 |
Challenges of Submitting Electronic Study Data to Two Authorities: The PMDA & FDA |
Torsten Petsching |
source
presentation source |
6 |
| PHUSE EU |
2018 |
Conformance Rules - How to Follow and Comply When Specified by Multiple Sources? |
Francis Dsa |
source
presentation source |
4 |
| PHUSE EU |
2018 |
Crowdsourced ADaM Programming and Standardisation: A Design Study |
Holger Langkabel |
source
presentation source |
10 |
| PHUSE EU |
2018 |
Data Visualisation in a Risk-Based Approach to Support Decision-making |
Joke De Wever,
Irina Sargsyan |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Define'ing the Future |
Johan Schoeman,
Nicola Perry |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Define-XML-centric Dataset Development |
Leonid Tseytlin,
Yevhen Pavlenko |
source
presentation source |
3 |
| PHUSE EU |
2018 |
Diagnostics of technical errors in define.xml file |
Sergiy Sirichenko,
Max Kanevsky |
source
presentation source |
9 |
| PHUSE EU |
2018 |
Do's and Don'ts of Define.xml |
David Roulstone |
source
presentation source |
10 |
| PHUSE EU |
2018 |
Easing Your Pain with Biomedical Concepts |
Kirsten Langendorf |
source
presentation source |
12 |
| PHUSE EU |
2018 |
eSource to SDTM: Trade-offs and Pay-offs |
Donald Benoot,
Swapna Pothula |
source
presentation source |
11 |
| PHUSE EU |
2018 |
First Aid Kit for an Observational Study |
Yuliia Bahatska,
Vladlen Ivanushkin |
source
poster source |
4 |
| PHUSE EU |
2018 |
From Machine-readable CDISC Standard Specifications to the e-Protocol |
Jozef Aerts |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Generating Define-XML and Analysis Results Metadata Using Specifications, Datasets and TFL Annotation |
Mark Crangle |
source
presentation source |
13 |
| PHUSE EU |
2018 |
Guideline for Submission-ready aCRF |
Christina Paul,
Eva Bervar |
source
poster source |
5 |
| PHUSE EU |
2018 |
How Do You Determine #SDTMs, ADaMs and TFLs and Their Impact on Outsourcing? |
Roy Ward |
source
presentation source |
10 |
| PHUSE EU |
2018 |
How to Easily Generate Define.pdf from Define-XML - Submission Request |
Ralf Goetzelmann,
Endri Elnadav |
source
presentation source |
5 |
| PHUSE EU |
2018 |
How to Manage Changes to CDISC Standards |
Sune Dandanell,
Mikkel Traun |
source
presentation source |
4 |
| PHUSE EU |
2018 |
How to Write ADaM Specifications Like a Ninja |
Caroline Francis |
source
poster source |
5 |
| 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 |
Into the Fire Linking CDISC & FHIR |
David Iberson-Hurst |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Is it Possible to Make a Global CDISC Submission? |
Marianne Carames |
source
presentation source |
2 |
| 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 |
Mapping Programs - Written by MDR |
Jörn Bilow |
source
presentation source |
2 |
| PHUSE EU |
2018 |
Need for Speed - Accelerating Centralised Monitoring |
Parag Naithani,
Pramod Chittam |
source
poster source |
1 |
| PHUSE EU |
2018 |
Optimizing the Traceability Method in ADaM Parallel Conversions |
Roxane Debrus |
source
presentation source |
15 |
| PHUSE EU |
2018 |
Overcoming Resistance to Technology Change: A Linked Data Perspective |
Tim P. Williams |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Please Put Your Data in an Upright Position - Or How to Tackle Verticalisation |
Kristina Zweier |
source
presentation source |
9 |
| PHUSE EU |
2018 |
Post-processing PDFs with Ghostscript |
Jonathan North |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Practical Benefits of EC: Building a Comprehensive Exposure Story |
Zegher Vereecke,
Donald Benoot |
source
presentation source |
5 |
| PHUSE EU |
2018 |
Practical Lessons Learned from Recent NDA and BLA Submissions to the FDA |
Carey G. Smoak,
Lisa Brooks |
source
presentation source |
5 |
| PHUSE EU |
2018 |
Robust Test Data |
Jennie McGuirk,
Ramesh Ayyappath |
source
poster source |
3 |
| PHUSE EU |
2018 |
SAS and UNIX: Rerun Your Batches in a Smarter Way |
Yaroslav Haiovyi |
source
presentation source |
19 |
| PHUSE EU |
2018 |
SDTM Legacy Data Conversion |
Markus Stoll,
Angelo Tinazzi |
source
presentation source |
13 |
| PHUSE EU |
2018 |
SDTMIG v3.3: New Domains - New Benefits |
Nick De Donder |
source
presentation source |
6 |
| PHUSE EU |
2018 |
Speed Up Evaluation by Parallelisation |
Michael Weiss |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Stop Copying CDISC Standards |
Craig Parry |
source
poster source |
21 |
| PHUSE EU |
2018 |
The "CDISC Stupidario" (the CDISC Nonsense) |
Angelo Pinazzi |
source
poster source |
11 |
| PHUSE EU |
2018 |
The interpretation and development of SDTM standards for non-submission purposes |
Paul Vervuren |
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 |
Updates on validation of ADaM data |
Max Kanevsky,
Sergiy Sirichenko |
source
presentation source |
7 |
| 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 |
ValueListDefs, MethodDefs and WhereClauses: How to Define Data Traceability in a Metadata Repository |
Judith Goud |
source
presentation source |
11 |
| SESUG |
2018 |
A Macro to Add SDTM Supplemental Domain to Standard Domain |
Pratap Singh Kunwar |
source |
6 |
| SESUG |
2018 |
A User Defined SDTM Data Quality Checking and Tracking System |
Zemin Zeng,
Yunzhi Ling |
source |
6 |
| SESUG |
2018 |
Are You Ready for It? Preparing for Your Next Technical Interview |
Christine McNichol |
source |
6 |
| SESUG |
2018 |
SDTM - Just a Walk in the (Theme) Park, Exploring SDTM in the Most Magical Place on Earth |
Magical Place |
source |
10 |
| SESUG |
2018 |
Tips on Developing SDTM Datasets for Complex Long-Term Safety Studies |
Yunzhi Ling,
Helen Wang |
source |
7 |
| SESUG |
2018 |
Working with the SAS ODS EXCEL Destination to Send Graphs, and Use Cascading Style Sheets When Writing to EXCEL Workbooks |
William E. Benjamin Jr. |
source |
19 |
| MWSUG |
2018 |
Automated Transfer of a Sea of SAS Programs between Data Transfers |
Xuelin Li,
Jiangang Cai,
Cindy Lee |
|
6 |
| MWSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson |
|
15 |
| MWSUG |
2018 |
Conversion of CDISC specifications to CDISC data - specifications driven SAS programming for CDISC data mapping |
Yurong Dai,
Jiangang Jameson Cai |
|
9 |
| WUSS |
2018 |
A Macro to Avoid P21 FDAC036 Error Message for Regulatory Submission Datasets |
Venkata Madhira,
Prabhakara Rao Burma |
source |
3 |
| WUSS |
2018 |
A Macro Tool to Find and/or Split Variable Text String Greater Than 200 Characters for Regulatory Submission Datasets |
Venkata Madhira,
Harish Yeluguri |
source |
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 |
Generating Variable Attributes for Define 2.0 |
Abhinav Srivastva |
source |
10 |
| WUSS |
2018 |
How FDA will reject non-CDISC submission |
Kevin Lee |
source |
6 |
| WUSS |
2018 |
How sensitive is your analysis? A case study on addressing it at ADaM level. |
Bhargav Koduru,
Balavenkata Pitchuka |
source |
7 |
| 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 |
Achieving Highest Quality and Usability of SEND through Industry and Regulatory Collaboration |
William Houser,
Lou Ann Kramer |
source |
7 |
| PHUSE US |
2018 |
ADaM Intermediate Dataset: How to Improve Your Analysis Traceability |
Angelo Tinazzi,
Ashish Aggarwal |
source
presentation source |
12 |
| PHUSE US |
2018 |
An Automated Macro to Compare Data Transfers |
Franklin E. Menius |
source
presentation source |
11 |
| PHUSE US |
2018 |
Automate Analysis Result Metadata in the Define-XML v2.0 |
Hong Qi,
Larry Wu |
source
presentation source |
8 |
| PHUSE US |
2018 |
Automated Creation of Submission-Ready Artifacts |
Lourdes Devenney,
Silas McKee |
source
presentation source |
5 |
| PHUSE US |
2018 |
Benefits of a Rapidly Growing Library of Clinically Relevant Visualization Templates/Patterns |
Eric Herbel |
source
presentation source |
4 |
| PHUSE US |
2018 |
Best Practices for Explaining Validation Results in the Study Data Reviewer's Guide |
Kristin Kelly |
source
presentation source |
6 |
| PHUSE US |
2018 |
Bili's Journey |
Chris Hurley,
Lisa Kaye Brooks |
source
poster source |
3 |
| PHUSE US |
2018 |
BIMO Listings - Check That Off Your NDA To-Do List |
Charanjit Kahlon,
Bhavin Busa |
source |
7 |
| PHUSE US |
2018 |
Business-based Value in an MDR |
Manori Turmel,
Brooke Hinkson |
source
presentation source |
11 |
| PHUSE US |
2018 |
Can Clinical Trial Datasets (CDSIC - SDTM/ADaM) be Generated Using R? |
Prasanna Murugesan |
source
presentation source |
3 |
| 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 |
Commissioning a MDR System: Next-generation of Standards implementation |
Abhinav Jain |
source
presentation source |
6 |
| PHUSE US |
2018 |
Common Define.xml File Issues Seen During FDA's JumpStart Service |
Peter Glass,
Caitlin Anderson,
Margo Cohen,
Kathryn Matto,
Austin Taylor,
Sergiy Sirichenko,
Max Kanevsky,
Michael Beers,
Mary Doi,
Alan Shapiro,
Barbara Witczak,
Jesse Anderson |
source
poster source |
5 |
| 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 |
Confusing Data Validation Rules Explained |
Michael Beers |
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 |
Define-XML Value-level Metadata Coding and Naming Guidance |
Charles Sowers |
source
presentation source |
3 |
| PHUSE US |
2018 |
Don't Sweat It! Consider Taking the Risk Out of your Outsourced Deliverables |
Jennifer True,
Nancy Haeusser |
source
presentation source |
4 |
| PHUSE US |
2018 |
Easing Your Pain with Biomedical Concepts |
Kirsten Langendorf |
source
presentation source |
13 |
| PHUSE US |
2018 |
Generating Define.xml v2.0 and Analysis Result Metadata using ADaM Specifications ADaM Datasets and TFL Shells Annotation |
Mark Crangle,
Hima Bhatia |
source
presentation source |
9 |
| PHUSE US |
2018 |
Harnessing the Web to Streamline Statistical Programming Processes |
Daniel J. Boisvert,
Gordon Schantz |
source
presentation source |
8 |
| PHUSE US |
2018 |
How do I have ONE Interpretation of CDISC for all my Studies? |
Mor Meyerovich |
source
presentation source |
5 |
| PHUSE US |
2018 |
How To Derive Parameters At ADaM Level For Generating Yearly Interval Exposure Tables [presentation] |
Geetha Kesireddy |
source |
10 |
| PHUSE US |
2018 |
How to Prepare High Quality Metadata for Submission [presentation] |
Varun Debbeti |
source |
31 |
| PHUSE US |
2018 |
Improving Traceability for Complex Algorithms in ADaM Datasets [poster] |
Priya Lakshmi Saradha |
source |
1 |
| PHUSE US |
2018 |
Incorporating Pinnacle 21 with LSAF |
Sonali Garg,
Aleksey Vinokurov |
source
presentation source |
6 |
| 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 |
Incremental Changes: ADaMIG v1.2 Update |
Brian Harris,
Terek J. Peterson |
source
presentation source |
6 |
| PHUSE US |
2018 |
It's Time To Change |
David Iberson-Hurst |
source |
14 |
| PHUSE US |
2018 |
Keeping Control in a Changing World |
Johannes Ulander |
source
presentation source |
6 |
| PHUSE US |
2018 |
Lead Programmer Needs Help: Dedicated Programming Project Manager to the Rescue! |
Smitha Nathan,
Bhavin Busa |
source |
5 |
| PHUSE US |
2018 |
Making PK Analysis Easier: The New ADaM Data Standard ADNCA |
Peter Schaefer |
source
presentation source |
6 |
| PHUSE US |
2018 |
Metadata-based Auto-Programming Process |
Lisa Lyons,
Harry Chen |
source
presentation source |
11 |
| PHUSE US |
2018 |
Methods for Handling Concentration Values Below the Limit of Quantification in PK Studies |
James R. Johnson |
source
presentation source |
9 |
| PHUSE US |
2018 |
Optimizing SDTM Specification Development with Auto-population |
Cori Kramer,
Ryan Adalbert |
source
presentation source |
6 |
| PHUSE US |
2018 |
Patterns Emerging from Chaos |
Alan Cantrell |
source
presentation source |
5 |
| PHUSE US |
2018 |
Practical Benefits of EC: Building a Comprehensive Exposure Story |
Donald Benoot,
Zegher Vereecke |
source |
5 |
| PHUSE US |
2018 |
Qualitative Analysis of Actual SEND Datasets for Trial Design Domains [poster] |
G. Sato |
source |
1 |
| PHUSE US |
2018 |
Ready Set Go: Planning and Preparing a CDISC Submission |
Maria Dalton |
source
presentation source |
11 |
| 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 |
Secure Data Office: An Independent Team that Can Come to the Rescue in Blinded Trials |
Annelies Van Zeveren,
Yana Hoorne |
source
presentation source |
9 |
| PHUSE US |
2018 |
Split-Coalesce Tumor Data Handling Woes and Safety-Efficacy Dilemma |
Idya Muthukumar |
source
presentation source |
11 |
| PHUSE US |
2018 |
Step Up Your ADaM Compliance Game |
Ramesh Ayyappath |
source
presentation source |
5 |
| PHUSE US |
2018 |
Supporting a Data Review and Visualization Application with SDTM |
Deepika Sunkara,
Jagadish Dhanraj |
source
presentation source |
6 |
| PHUSE US |
2018 |
The First and Last Words of ADaM |
Susan J. Kenny |
source |
4 |
| 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 a Waiver Process as a Change-Control Tool from ADaM Standards Governance |
Karin LaPann |
source
presentation source |
6 |
| PHUSE US |
2018 |
Want Submission-Ready Datasets Package from the Get-Go? |
Kishore Pothuri,
Bhavin Busa |
source |
7 |
| PharmaSUG |
2018 |
A Critique of the Use of the Medical Device SDTM Domains in Therapeutic Area User Guides |
Carey G. Smoak |
source |
10 |
| PharmaSUG |
2018 |
A CRO's perspective on successful partnering to deliver SDTM/SEND contributions |
Helen Owen,
Kirsty Payne |
source |
7 |
| PharmaSUG |
2018 |
A Framework for Implementing [Conflicting] FDA Guidance |
Todd Case |
source |
6 |
| PharmaSUG |
2018 |
A Macro to Create Program Inventory for Analysis Data Reviewer's Guide |
Xianhua Zeng |
source |
6 |
| PharmaSUG |
2018 |
A SAS Macro to Create Validation Summary of Dataset Report |
Zemin Zeng |
source |
6 |
| PharmaSUG |
2018 |
A Simple Method for Integrating Analysis Result Metadata into Existing Define.xml 2.0 |
Jeff Xia |
source |
9 |
| PharmaSUG |
2018 |
A time saving approach to track data issues |
Aishhwaryapriya Elamathivadivambigai |
source |
8 |
| PharmaSUG |
2018 |
Accessing the Metadata from Define-XML |
Lex Jansen |
source |
44 |
| PharmaSUG |
2018 |
ADaM data structure layout: common issues and ways to avoid |
Jianfei Jiang |
source |
5 |
| PharmaSUG |
2018 |
ADaM Define.xml v2.0 Validation - The Perl Way in SAS |
Yuxin (Ellen) Jiang |
source |
8 |
| PharmaSUG |
2018 |
ADaM for Medical Devices: Extending the Current ADaM Structures |
Julia Yang,
Sandra Minjoe |
source |
7 |
| PharmaSUG |
2018 |
ADaM Integration for Summary of Clinical Safety: The 'Unique Patient' Paradox |
Aakar Shah,
Tracy Sherman |
source |
12 |
| PharmaSUG |
2018 |
ADaM Structures for Integration: A Preview |
Deborah J. Bauer,
Kimberly Minkalis,
Wayne Zhong |
source |
14 |
| PharmaSUG |
2018 |
ADINTDT and ADTTE for Survival Sweep in Oncology Studies |
Christine S Teng,
Wenyu Hu |
source |
6 |
| PharmaSUG |
2018 |
Advanced Visualization using TIBCO Spotfire and SAS |
Ajay Gupta |
source |
14 |
| PharmaSUG |
2018 |
An alternate way to create the standard SDTM domains |
Sunil Kumar Pusarla |
source |
8 |
| PharmaSUG |
2018 |
An Automated Macro to Compare Data Transfers |
Michael Stackhouse,
Franklin E. Menius |
source |
12 |
| PharmaSUG |
2018 |
Analysis of Oncology Studies for Programmers and Statisticians |
Kevin Lee |
source |
7 |
| PharmaSUG |
2018 |
Are You Ready for It? Preparing for Your Next Technical Interview |
Christine McNichol |
source |
6 |
| PharmaSUG |
2018 |
Automatically Configure SDTM Specifications Using SAS and VBA |
Xingxing Wu |
source |
15 |
| PharmaSUG |
2018 |
Automation of STDM dataset integration and ADaM dataset formation |
Rinki Jajoo,
William Wei |
source |
11 |
| PharmaSUG |
2018 |
Avoid chasing one's Tail - Challenges and Solutions for managing changes in SDTM Standards Development |
Erica Davis,
Veena Nataraj |
source |
7 |
| PharmaSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
18 |
| PharmaSUG |
2018 |
Best Practice for Explaining Validation Results in the Study Data Reviewer's Guide |
Kristin Kelly |
source |
6 |
| PharmaSUG |
2018 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2018 |
Challenges & Strategies in PKPD Programming |
Jing Su,
Jiannan Kang |
source |
6 |
| PharmaSUG |
2018 |
Challenges for Implementing Study Data Standardization Plan (SDSP) in Legacy Data Submission |
Shengfeng Ho |
source |
9 |
| 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 |
Coming soon: ADNCA and the PK submission |
Luke Reinbolt,
Liz MacDonald |
source |
6 |
| PharmaSUG |
2018 |
Common Data Related Review Issues and Prevention: A Statistical Reviewer's Thoughts |
Huanyu Chen |
source |
18 |
| 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 |
Complying with the ADaM Compliance Rules |
Alyssa M. Wittle,
Steven R. Kirby |
source |
4 |
| PharmaSUG |
2018 |
Confusing Data Validation Rules Explained |
Michael Beers |
source |
6 |
| PharmaSUG |
2018 |
Core and Extension studies - Challenges and solutions towards SDTM submission |
Murali Marneni |
source |
6 |
| PharmaSUG |
2018 |
Creating an ADaM Data Set for Correlation Analyses |
Chad W. Melson |
source |
11 |
| PharmaSUG |
2018 |
Data Management and CDISC Formatting for Transdermal Patches |
Lois Lynn |
source |
11 |
| PharmaSUG |
2018 |
Data Standards for Population Pharmacokinetic (POPPK) and Non-Compartmental Analysis (NCA) |
Neelima Thanneer |
source |
7 |
| PharmaSUG |
2018 |
define.xml (noun): Fear Inducing Task for SAS Programmers |
Kjersten Offenbecker,
Antonio Cardozo,
Kirsty R. Lauderdale |
source |
17 |
| PharmaSUG |
2018 |
Derivations of Response Status from SDTM Domains using RECIST 1.1 |
Christine S Teng,
Lei Pang |
source |
10 |
| PharmaSUG |
2018 |
Designing Flexible Data Standards Models |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2018 |
Diagnostics of technical errors in define.xml file |
Sergiy Sirichenko,
Max Kanevsky |
source |
9 |
| PharmaSUG |
2018 |
Doctor-s 'Prescription' to Reengineer Process of Pinnacle21 Community Version Friendly ADaM Developm |
Aakar Shah,
Tracy Sherman |
source |
9 |
| PharmaSUG |
2018 |
Dosing In NONMEM Datasets an Enigma |
Sree Harsha Sreerama Reddy,
Vishak Subramoney |
source |
11 |
| PharmaSUG |
2018 |
eSubmission - Are you really Compliant? |
Majdoub Haloui,
Suhas R. Sanjee |
source |
5 |
| PharmaSUG |
2018 |
Experience of electronic data submission via Gateway to PMDA |
Kumiko Kimura,
Iori Sakakibara,
Laurence Carpenter |
source |
7 |
| PharmaSUG |
2018 |
Family of PARAM***: PARAM, PARAMCD, PARAMN, PARCATy(N), PARAMTYPE |
Kamleshkumar Patel |
source |
12 |
| PharmaSUG |
2018 |
Generating Define.xml from Pinnacle 21 Validator |
Pinky Anandani |
source |
15 |
| PharmaSUG |
2018 |
Global checklist to QC SDTM Lab data |
Murali Marneni,
Sekhar Badam |
source |
10 |
| PharmaSUG |
2018 |
How PK and PD analyses drive dataset designs |
David Radtke,
Brian A. Moser |
source |
7 |
| 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 |
Improving Metadata Compliance and Assessing Quality Metrics with a Standards Library |
Veena Nataraj,
Erica Davis |
source |
9 |
| PharmaSUG |
2018 |
Incorporating Pinnacle 21 with LSAF |
Aleksey Vinokurov,
Sandeep Juneja,
Sonali Garg |
source |
6 |
| PharmaSUG |
2018 |
Integrations Made Easier |
Kirsty R. Lauderdale |
source |
6 |
| PharmaSUG |
2018 |
It's all about getting the Source and Codelist Implementation right for ADaM Define.xml v2.0 |
Supriya Davuluri |
source |
11 |
| PharmaSUG |
2018 |
Know your PET: From the Scans to SDTM Datasets |
Balavenkata Pitchuka,
Bhargav Koduru |
source |
8 |
| 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 |
Levista - An Integrated Programming Environment with Visualization |
Priya Lakshmi Saradha |
source |
4 |
| PharmaSUG |
2018 |
Macro-Supported Metadata-Driven Process for Mapping SDTM VISIT and VISITNUM |
Pragathi Dayananda,
Eric Crockett |
source |
6 |
| PharmaSUG |
2018 |
No News Is Good News: A Macro to Reveal the Untold Normal Lab Results |
Ming Yan |
source |
7 |
| PharmaSUG |
2018 |
Preparing to Meet FDA Requirements for Submission of Standardized Data and Documentation |
Steven R. Kirby,
Mario Widel |
source |
11 |
| 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 |
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 |
SDTM EX and EC: Considerations When Submitting Exposure Data |
Jerry Salyers,
Kristin Kelly |
source |
8 |
| PharmaSUG |
2018 |
SDTMs in a Medical Device Trial - A First Attempt |
Phil Hall |
source |
6 |
| PharmaSUG |
2018 |
Shiny Happy People: Using RShiny and SDTM Data to generate a Quick Interactive Dashboard |
Saranya Duraisamy,
Nate Mockler |
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 |
Standardization Efforts at Medtronic, its benefits and Lessons Learned |
Firdouse Fathima |
source |
4 |
| PharmaSUG |
2018 |
Statistical Programming: Revolution, Evolution, or Status Quo? |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
9 |
| 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 |
Telling Stories with Jupyter Notebook |
Kevin Lee |
source |
14 |
| PharmaSUG |
2018 |
The Statistical Programming Summit |
Todd Case |
source |
4 |
| 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 |
Traceability: Some Thoughts and Examples for ADaM Needs |
Richann J. Watson,
Kent Letourneau,
Wayne (Weizhen) Zhong,
Sandra Minjoe |
source |
18 |
| PharmaSUG |
2018 |
Trial Summary: The Golden Gate towards a Successful Submission |
Bhargav Koduru,
Girish Kankipati |
source |
9 |
| 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 |
UTF What? A Guide for Handling SAS Transcoding Errors with UTF-8 Encoded Data |
Michael Stackhouse,
Lavanya Pogula |
source |
15 |
| PharmaSUG |
2018 |
Want Submission-Ready Datasets Package from the Get-Go? |
Kishore Pothuri,
Bhavin Busa |
source |
8 |
| PharmaSUG |
2018 |
Watch Out For Blind Spots While Keeping Up With the Speed of Evolving Standards and Regulations |
Srinivas Veeragoni |
source |
14 |
| PharmaSUG |
2018 |
Why organizations need MDR systems to manage metadata? |
Abhinav Jain |
source |
7 |
| PharmaSUG |
2018 |
Working with the SAS ODS EXCEL Destination to Send Graphs, and Use Cascading Style Sheets When Writing to EXCEL Workbooks |
William E. Benjamin Jr. |
source |
19 |
| SGF |
2018 |
The Anatomy of Clinical Trials Data: A Beginner's Guide |
Venky Chakravarthy |
source |
14 |
| SGF |
2018 |
Using the ODS EXCEL Destination with SAS University Edition to Send Graphs to Microsoft Excel [presentation] |
William E. Benjamin Jr. |
source |
19 |
| SESUG |
2017 |
A Data-Driven Approach for Generating Define.xml v2.0 using ADaM Specifications and ADaM Datasets |
Jaskaran Sing Gill,
Hima Bhatia,
ICON Plc |
source |
8 |
| SESUG |
2017 |
An Introduction to Visit Window Challenges and Solutions |
Mai Ngo |
source |
6 |
| SESUG |
2017 |
Challenges and Solutions for Handling Re - screened Subjects in SDTM |
Charity Quick,
Paul Nguyen |
source |
6 |
| SESUG |
2017 |
Clinical Data Visualization using TIBCO Spotfire and SAS |
Ajay Gupta |
source |
12 |
| SESUG |
2017 |
DE-Identifying Data when Sharing Clinical Data |
Pushpa Saranadasa |
source |
5 |
| SESUG |
2017 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
source |
8 |
| SESUG |
2017 |
One Project, Two Teams: The Unblind Leading the Blind |
Kristen Reece Harrington |
source |
5 |
| SESUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| SESUG |
2017 |
Streamlining ADaM Dataset Specifications |
Hunter Vega |
source |
6 |
| SESUG |
2017 |
Timing Variables In Clinical Trials: Avoiding Common Mistakes And Dealing With Unforeseen Issues |
Gregory Weller |
source |
4 |
| SCSUG |
2017 |
Red Rover, Red Rover, Send Data Right Over: Exploring External Geographic Data Sources with SAS |
Louise S. Hadden |
source |
9 |
| PHUSE EU |
2017 |
A Labour-saving SAS Macro fro Programmed Patient Narratives |
Vineeth Kurnala,
Prafulla Girase |
source
presentation source |
9 |
| PHUSE EU |
2017 |
ADaM Mapping - KeyConsiderations forMetadata Driven Realization |
Elenea Gathe |
source |
12 |
| PHUSE EU |
2017 |
ADAM Programming - The Good, The Bad and The Ugly |
Pam Howard |
source
presentation source |
8 |
| 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 |
Automatic Creation of Define .xml for ADaM: A Fast Way Approach, Starting from ADaM Metadata |
Andreas Parodi,
Dimitri Petratchenko |
source
presentation source |
7 |
| 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 |
Clinical Study Oversight: Different Approaches to Using Data Standards |
Jasmine Kestermont,
Peter Van Reusel |
source
presentation source |
6 |
| 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 |
Constrain your Terminology - Use Integrity Constraints to Validate your Data |
Sven Greiner |
source
presentation source |
9 |
| PHUSE EU |
2017 |
Consuming Your Metadata for a Healthy Mapping |
Alan Cantrell,
Julius Kusserow |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Decrypting SDTM Trial Design Datasets for Complex Study Designs |
Charumathy Sreeraman |
source
presentation source |
14 |
| PHUSE EU |
2017 |
Define.xml Tools Supporting SEND/SDTM Data Process |
Kirsten Langendorf |
source
presentation source |
14 |
| PHUSE EU |
2017 |
Detecting Treatment Emergent Adverse Events (TEAEs) |
Matthias Lehrkamp |
source
presentation source |
12 |
| PHUSE EU |
2017 |
End-to-End Traceability from Protocol Development to Submission |
Mikkel Traun,
Trine Danø Klingberg |
source
presentation source |
3 |
| PHUSE EU |
2017 |
Extension Studies - CDISC Submission Challengesand Scenarios |
Arvind Sri Krishna Mani,
Deepak Anathan |
source
presentation source |
3 |
| PHUSE EU |
2017 |
GUI Method of Mapping SDTM from Raw Data |
Elisa Natale |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Harmonizing SDTM at the Source: Designing Collection Instruments that Support Sponsor Standards |
Sue Huxtable,
Charlotte Lomberg |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Helping The Define.xml User |
David Iberson-Hurst |
source
presentation source |
12 |
| PHUSE EU |
2017 |
How a Metadata Repository can Facilitate Automated Data Collection Processes |
Judith Goud |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Implementation of CDISC ADaM and Pharmacodynamics |
Françoise Frérart,
Joanna Magielse |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Implementing a Meta-data Repository (MDR) Using Functional Service Provider (FSP) How Does it Work? |
Carla Santillán |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Industry Standards - What Else Exists Beside CDISC |
Joerg Dillert |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Intervention ML: Mapping of Meal data |
Rahul Loharkar |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Job of Jobs |
Kris Lauwers,
Raphael Noirfalise |
source
presentation source |
3 |
| PHUSE EU |
2017 |
Mapping of Gastrointestinal Tolerance Data to SDTM |
Lieke Gijsbers |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Metadata-driven Tool for Creation of a Dataset for Exploratory Analyses |
Alexey Kuznetsov |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Moving Towards a Round World Linking Multi-dimensional Clinical Metadata Across the CDISC Standards |
Chris Decker,
Scott A. Bahlavooni |
source
presentation source |
8 |
| 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 |
Reducing Dataset Merges with Data Driven Formats |
Paul Grimsey |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Robust Study Database Build: An Effective Start Towards Creation of Quality SDTMs |
Onkar Tajarekar |
source
presentation source |
9 |
| PHUSE EU |
2017 |
SDTM Domains by Query - is it Possible? |
Johannes Ulander |
source
presentation source |
8 |
| PHUSE EU |
2017 |
SDTM vs CDASH: Why You Need Them Both! [presentation] |
Kit Howard,
Shannon Labout |
source |
20 |
| PHUSE EU |
2017 |
SDTM-ADaM Hybrid: Supermodel or Frankenstein? |
Kenneth Stoltzfus |
source
presentation source |
8 |
| PHUSE EU |
2017 |
Streamline SDTM Development and QC |
Stephen Gormley |
source
presentation source |
9 |
| PHUSE EU |
2017 |
The Secure Data Office Concept |
Annemie Van Dijck |
source
presentation source |
9 |
| PHUSE EU |
2017 |
The Untapped Potential of the Protocol Representation Model |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source
presentation source |
10 |
| 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 |
Visualising CDSIC SDTM for Monitoring and Review |
Philip Bartle |
source
presentation source |
11 |
| PHUSE EU |
2017 |
Worst CDISC Implementation Processes - How to Avoid Some Very Basic Mistakes in SDTM ADaM Define |
Hannes Engberg Reader,
Michale Riech |
source
presentation source |
10 |
| MWSUG |
2017 |
ADQRS: Basic Principles for Building Questionnaire, Rating and Scale Analysis Datasets |
Nancy Brucken,
Karin LaPann |
|
6 |
| MWSUG |
2017 |
Mapping MRI data to SDTM and ADaM |
Lingling Xie,
Xiaoqi Li |
|
10 |
| MWSUG |
2017 |
No News Is Good News: A Smart Way to Impute Missing Clinical Trial Lab Data |
Ming Yan |
|
4 |
| WUSS |
2017 |
A Critique of Implementing the Submission Data Tabulation Model (SDTM) for Drugs and Medical Devices |
Carey G. Smoak |
source |
16 |
| WUSS |
2017 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
15 |
| WUSS |
2017 |
Red Rover, Red Rover, Send Data Right Over: Exploring External Geographic Data Sources with SAS |
Louise S. Hadden |
source |
9 |
| WUSS |
2017 |
SDTMs in a Medical Device Trial - A First Attempt |
Phil Hall |
source |
5 |
| WUSS |
2017 |
Working with the SAS ODS EXCEL Destination to Send Graphs, and Use Cascading Style Sheets When Writing to EXCEL Workbooks |
William E. Benjamin Jr. |
source |
19 |
| PharmaSUG CN |
2017 |
Assigning VISITNUM and EPOCH [presentation] |
Na Duan,
Ru He |
|
32 |
| PharmaSUG CN |
2017 |
Constructive Practice of Generating ADaM Datasets |
Amos Shu |
|
7 |
| PharmaSUG CN |
2017 |
Create Zero Observation dataset to achieve maximum metadata resolution in CDISC Submission |
M K Sinha |
|
7 |
| PharmaSUG CN |
2017 |
Extract Information from aCRF by using EXCEL VBA |
Kai Zhou,
Annie Xu |
|
5 |
| 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 custom ADaM domain for time to event analysis in adverse events |
John Saida Shaik |
source |
4 |
| PharmaSUG |
2017 |
A novel method to track mapping of all CRF variables into SDTM datasets. |
Aishhwaryapriya Elamathivadivambigai |
source |
7 |
| PharmaSUG |
2017 |
A SASsy Study of eDiary Data |
Amie Bissonett |
source |
5 |
| PharmaSUG |
2017 |
ADaM Compliance - Validating your Specifications |
Trevor Mankus,
Kent Letourneau |
source |
9 |
| PharmaSUG |
2017 |
ADaM Grouping: Groups, Categories, and Criteria. Which Way Should I Go? |
Jack Shostak |
source |
12 |
| PharmaSUG |
2017 |
ADQRS: Basic Principles for Building Questionnaire, Rating and Scale Analysis Datasets |
Nancy Brucken,
Karin LaPann |
source |
6 |
| 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 |
An Efficient Solution to Efficacy ADaM Design and Implementation |
Chengxin Li,
Zhongwei Zhou |
source |
7 |
| 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 |
Basic SDTM House-Keeping |
Emmy V Pahmer |
source |
3 |
| PharmaSUG |
2017 |
Building a Fast Track for CDISC: Practical Ways to Support Consistent, Fast and Efficient SDTM Delivery |
Steven R. Kirby,
Mario Widel,
Richard Addy |
source |
14 |
| PharmaSUG |
2017 |
CDISC Compliant NCA PK Parameter Analysis When Using Phoenix WinNonlin |
Renfang Hwang |
source |
11 |
| PharmaSUG |
2017 |
Challenge for Dramatic Streamlining of TLFs Creation Process with SAS and Java |
Yohei Takanami,
Fumihiro Yamasaki |
source |
8 |
| PharmaSUG |
2017 |
Check Your Data: Tools for Automating Data Assessment |
Paul Stutzman |
source |
12 |
| PharmaSUG |
2017 |
Clarifications About ADaM Implementation Provided in ADaMIG Version 1.1 |
John K. Troxell |
source |
5 |
| PharmaSUG |
2017 |
Clinical Data Visualization using TIBCO Spotfire and SAS |
Ajay Gupta |
source |
12 |
| PharmaSUG |
2017 |
Common Programming Errors in CDISC data |
Sergiy Sirichenko |
source |
9 |
| 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 |
Controlled Terminology Without Excel |
Mike Molter |
source |
15 |
| PharmaSUG |
2017 |
Conversion of CDISC specifications to CDISC data - specifications driven SAS programming for CDISC data mapping |
Yurong Dai,
Jameson Cai |
source |
9 |
| PharmaSUG |
2017 |
Converting Non-Imputed Dates for SDTM Data Sets With PROC FCMP |
Noory Y. Kim |
source |
12 |
| 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 |
Dear Dave, Please See the .LST File for Our Validation Differences. Thanks, Bad Validation Programmer |
Tracy Sherman,
David W. Carr,
Brian P. Fairfield-Carter |
source |
9 |
| PharmaSUG |
2017 |
Deriving Rows in CDISC ADaM BDS Datasets |
Sandra Minjoe |
source |
12 |
| PharmaSUG |
2017 |
Developing ADaM Dataset for Cardiovascular Outcome Studies |
Joanne C. Zhou,
Rakesh Kumar,
David L. Wade,
David C. Chen |
source |
4 |
| PharmaSUG |
2017 |
Documenting Traceability for the FDA: Clarifying the Legacy Data Conversion Plan & Introducing the Study Data Traceability Guide |
David C. Izard,
Kristin Kelly,
Jane Lozano |
source |
9 |
| PharmaSUG |
2017 |
Good Data Validation Practice |
Sergiy Sirichenko,
Max Kanevsky |
source |
10 |
| 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 |
Gray Areas of ADaM and Ways to Provide Color [presentation] |
Susan J. Kenny,
Sandra Minjoe,
Nate Freimark,
Jack Shostak,
John K. Troxell,
Deborah J. Bauer |
source |
38 |
| PharmaSUG |
2017 |
Harmonizing CDISC Data Standards across Companies: A Practical Overview with Examples |
Keith Shusterman,
Prathima Surabhi,
Binoy Varghese |
source |
6 |
| PharmaSUG |
2017 |
How to find the best MDR solution for your organization |
Kevin Lee |
source |
3 |
| PharmaSUG |
2017 |
How will FDA Reject non-CDISC submission? |
Kevin Lee |
source |
6 |
| 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 |
In-Licensing from a Programming Perspective |
Asif Karbhari |
source |
5 |
| 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 |
Leveraging metadata when mapping to CDISC Standards with SAS machine learning in a Results as a Service plus Model (RAAS+) |
Ben E. Bocchicchio,
Sandeep Juneja,
Preetesh Parikh |
source |
6 |
| 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 |
Multiple Imputation: A Statistical Programming Story |
Christopher J. Smith,
Scott Kosten |
source |
16 |
| PharmaSUG |
2017 |
One Project, Two Teams: The Unblind Leading the Blind |
Kristen Reece Harrington |
source |
5 |
| PharmaSUG |
2017 |
Overview and Application of the HCV Vertical Resistance Analysis Template |
Yan Xie |
source |
5 |
| 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 |
Planning to Pool SDTM by Creating and Maintaining a Sponsor-Specific Controlled Terminology Database |
Cori Kramer,
Ragini Hari,
Keith Shusterman |
source |
7 |
| PharmaSUG |
2017 |
Preparing Analysis Data Model (ADaM) Data Sets and Related Files for FDA Submission |
Sandra Minjoe |
source |
12 |
| 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 |
Reporting Non-Printable and Special Characters for Review in Excel |
Abhinav Srivastva |
source |
11 |
| PharmaSUG |
2017 |
Roadmap for Managing Multiple CRO Vendors |
Veena Nataraj,
Karin LaPann |
source |
7 |
| PharmaSUG |
2017 |
SAS Application to Automate a Comprehensive Review of DEFINE and All of its Components |
Walter H. Hufford Jr.,
Vincent Guo,
Mijun Hu |
source |
8 |
| 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 |
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 |
Supporting the CDISC Validation Life-Cycle with Microsoft Excel VBA |
Eric Crockett |
source |
7 |
| PharmaSUG |
2017 |
Takeaways from Integrating Studies Conducted by Bristol-Myers Squibb (BMS) and ONO |
Yan Wang |
source |
2 |
| PharmaSUG |
2017 |
The Benefits of Traceability Beyond Just From SDTM to ADaM in CDISC Standards |
Maggie Ci Jiang |
source |
8 |
| PharmaSUG |
2017 |
The CDISC SDTM Exposure Domains (EX & EC) Demystified. How EC Helps You Produce A Better (more compliant) EX. |
Thomas Guinter |
source |
9 |
| PharmaSUG |
2017 |
The CDISC Trial Design Model (TDM), the EPOCH variable, and the Treatment Emergent Flag: How to Leverage these to Improve Review |
Thomas Guinter |
source |
4 |
| 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 Road Not Taken: SAS for Pharmacometrics |
Vishak Subramoney,
Sree Harsha Sreerama Reddy |
source |
4 |
| PharmaSUG |
2017 |
The Untapped Potential of the Protocol Representation Model |
Frank C. DiIorio,
Jeffrey M. Abolafia |
source |
10 |
| PharmaSUG |
2017 |
Three Issues and Corresponding Work-Around Solution for Generating Define.xml 2.0 Using Pinnacle 21 Enterprise |
Jeff Xia,
Lugang Larry Xie,
Shari Lisnov |
source |
6 |
| PharmaSUG |
2017 |
Usage of Pinnacle 21 Community Toolset 2.x.x for Clinical Programmers |
Sergiy Sirichenko,
Michael DiGiantomasso |
source |
23 |
| PharmaSUG |
2017 |
Use of Traceability Chains in Study Data and Metadata for Regulatory Electronic Submission |
Tianshu Li |
source |
8 |
| PharmaSUG |
2017 |
Using SAS ODS EXCEL Destination with SAS University Edition to send graphs to Excel |
William E. Benjamin Jr. |
source |
15 |
| PharmaSUG |
2017 |
Visual Basic for Applications: A Solution for Handling Non-ASCII Removal and Replacement |
Eric Crockett |
source |
4 |
| PharmaSUG |
2017 |
Where Is the Link Broken - Another Look at SDTM Oncology Tumor Packages |
Hong Wang,
Ke Xiao |
source |
12 |
| 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 |
Automate Validation of CDISC SDTM with SAS |
Sy J. Truong |
source |
11 |
| SGF |
2017 |
Automatically Map CDASH Data to the Study Data Tabulation Model (SDTM) Structure |
Hao Xu,
Hong Chen |
source |
18 |
| SGF |
2017 |
Deriving Rows in CDISC ADaM BDS Data Sets Using SAS DATA Step Programming |
Sandra Minjoe |
source |
17 |
| SGF |
2017 |
Import and Export XML Documents with SAS |
Fei Wang |
source |
15 |
| SGF |
2017 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
source |
8 |
| SGF |
2017 |
Preparing Analysis Data Model (ADaM) Data Sets and Related Files for FDA Submission with SAS |
Sandra Minjoe,
John K. Troxell |
source |
12 |
| SGF |
2017 |
Quality Control Programming: A Lost Art? |
Amber Randall,
Bill Coar |
source |
15 |
| SGF |
2017 |
Using the ODS EXCEL Destination with SAS University Edition to Send Graphs to Microsoft Excel |
William E. Benjamin Jr. |
source |
13 |
| SESUG |
2016 |
Converting Non-Imputed Partial Dates (for SDTM Data Sets) Using PROC FCMP |
Noory Y. Kim |
source |
8 |
| SESUG |
2016 |
SDTM What? ADaM Who? A Programmer's Introduction to CDISC |
Venita DePuy |
source |
9 |
| PHUSE EU |
2016 |
Analysis Datasets for Baseline Characteristics and Exposure Time for Multi-stage Clinical Trials |
Kimberly Umans,
Katherine Riester |
source
presentation source |
5 |
| PHUSE EU |
2016 |
Analysis Results Metadata...Are We There Yet? |
Carla Santillán |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Assessing CDISC Therapeutic Area User Guides in a Machine Readable Format |
Johannes Ulander,
Niels Both |
source
presentation source |
4 |
| PHUSE EU |
2016 |
Automating ADaM |
Helen Hart,
Christof Binder |
source
presentation source |
3 |
| PHUSE EU |
2016 |
Automating Frequency Tables with ClinXport SAS Macro Package |
Loizos Nicolaou |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Boosting the Efficiency of Data Review by using SAS Integration Technologies and VBA |
Giuseppe Di Monaco |
source
presentation source |
9 |
| PHUSE EU |
2016 |
Clinical Data in Business Intelligence |
Mike Collinson |
source
presentation source |
7 |
| 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 |
Developing MDR Metadata Requirements for Operational Implementation |
Andy Richardson,
Scott A. Bahlavooni |
source
presentation source |
5 |
| PHUSE EU |
2016 |
Device Domains: Examples of their Use in Clinical Trials |
Oksana Voevutska |
source
presentation source |
12 |
| PHUSE EU |
2016 |
DIY: Create Your Own SDTM Mapping Framework |
Bas van Bakel |
source
presentation source |
11 |
| PHUSE EU |
2016 |
Efficiency comes From Reusability and Repeatability |
Hanming Tu,
Dave Evans |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Efficiently Converting Datasets to Vertical Structure using Metadata |
Thevaki Mahadevan |
source
presentation source |
6 |
| 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 |
Fast Track to Define-XML v2.0 - SDTM and ADaM |
Jörn Bilow |
source
presentation source |
4 |
| PHUSE EU |
2016 |
Fast Track to Domain: SDTM.PC and SDTM.PP |
Lina Ulkjær Jørgensen |
source
presentation source |
2 |
| PHUSE EU |
2016 |
From SDTM to Displays, through ADaM & Analysis Results Metadata, a Flight on Board Metadata Airlines |
Omar Sefiani,
Stéphane Bouget |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Generating Analysis Results and Metadata - Report from a PHUSE CS Project |
Marc Andersen,
Marcelina Hungria,
Suhas R. Sanjee |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Get a JumpStart on Clinical Data Analysis and Visualisation with Standard Scripts |
Jared Slain,
Hanming Tu |
source
presentation source |
20 |
| PHUSE EU |
2016 |
How a Metadata Repository Enables Dynamism and Automation in SDTM-like SAS Dataset Generation |
Judith Goud,
Akana Shetty |
source
presentation source |
7 |
| PHUSE EU |
2016 |
How to Create your Define-XML as Early as Possible with the Click of a Button |
Roman Radelicki |
source
presentation source |
7 |
| 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 |
Increasing Work Group Transparency: ADaMIG v1.2 Update and New Team Working Process Review |
Terek J. Peterson,
Brian Harris |
source
presentation source |
8 |
| PHUSE EU |
2016 |
Japanese Electronic Submission in CDISC Formats |
Takashi Kitahara |
source
presentation source |
8 |
| PHUSE EU |
2016 |
Linking Metadata from CDASH to ADaM |
João Gonçalves |
source
presentation source |
6 |
| PHUSE EU |
2016 |
Metadata on the Go: Achieving Metadata Accuracy and Consistency Continually |
Swapna Pothula |
source
presentation source |
6 |
| PHUSE EU |
2016 |
On the Fast Lane to a Successful Submission - A Lead Programmer's Guide to Efficient, High-quality Submission Programming Deliverables |
Michael Reich,
Hannes Engberg Raeder |
source
presentation source |
9 |
| PHUSE EU |
2016 |
Out-of-the-box %Define-XML - Just a Simple SAS Macro |
Katja Glass |
source
presentation source |
11 |
| PHUSE EU |
2016 |
Pattern-based MDR: Towards High-quality Data Standards |
Alan Cantrell,
Julius Kusserow |
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 |
QC of the aCRF Using SAS |
Rune Pedersen,
Niels Both |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Shopping for your CRF: Combining Sources for a Simple Data Collection Browser |
Rod Bower |
source
presentation source |
5 |
| 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 |
To Create Define-XML Using - XML and the OpenCDISC Validator [presentation] |
Murali Neela |
source |
17 |
| PHUSE EU |
2016 |
Understanding the Potential of Share: A Visual Business Case and Technical Use Case |
Peter Van Reusel |
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 |
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 |
Working with the SAS ODS EXCEL Destination to Send Graphs, and Use Cascading Style Sheets When Writing to EXCEL Workbooks |
William E. Benjamin Jr. |
|
19 |
| PharmaSUG CN |
2016 |
ADaM Compliance VS Easy-Reviewed in Design and Construct Efficacy Analysis Datasets |
Huadan Li |
|
8 |
| PharmaSUG CN |
2016 |
ADaM Tips for Exposure Summary |
Kriss Harris |
|
6 |
| PharmaSUG CN |
2016 |
Automation of SDTM Programming in Oncology Disease Response Domain |
Yiwen Wang,
Yu Cheng,
Ju Chen |
|
10 |
| PharmaSUG CN |
2016 |
Building Your Own CDISC Application with SAS Clinical Standards Toolkit |
Jing Gao |
presentation |
13 |
| PharmaSUG CN |
2016 |
Define.xml Content Validation - CRF Page Check |
Shenglin Zhang |
presentation |
7 |
| PharmaSUG CN |
2016 |
How to handle the mapping of the eCRF form with the combined information |
Shirley Wu |
|
4 |
| PharmaSUG CN |
2016 |
Practical Experience in Implementing CDISC Standards for Global Cardiovascular, Clinical Outcome Assessment and Respiratory Trials [presentation] |
David Ju |
|
20 |
| PharmaSUG CN |
2016 |
Proposal for Streamlining the SDRG and ADRG Authoring Process [presentation] |
Stanley Wei |
|
1 |
| PharmaSUG CN |
2016 |
Strategy to Start to Implement CDISC Standards [presentation] |
Victor Wu |
|
24 |
| PharmaSUG CN |
2016 |
The Dream of a Common Vision: (Evolving) Standards |
Todd Case |
|
4 |
| WUSS |
2016 |
A Case of Retreatment - Handling Retreated Patient Data |
Sriramu Kundoor,
Seattle Genetics,
Sumida Urval |
source |
4 |
| WUSS |
2016 |
A Well-Formatted and Easy-to-Navigate Solution for Submitting SAS Source Code in NDA Submission |
Jeff Xia,
Lugang Larry Xie |
source |
7 |
| 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 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng,
Mike Wise,
Justina M. Flavin |
source |
20 |
| WUSS |
2016 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
source |
6 |
| 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 Data Preparation Primer: Getting Your Data Ready for Submission |
Janet E. Stuelpner |
source |
3 |
| PharmaSUG |
2016 |
A Macro to Automatically Flag Baseline in SDTM |
Taylor Markway |
source |
8 |
| PharmaSUG |
2016 |
A Practical Approach to Re-sizing Character Variable Lengths for FDA Submission Datasets (both SDTM and ADaM) |
Xiangchen (Bob) Cui,
Min Chen |
source |
19 |
| PharmaSUG |
2016 |
A SAS Macro Tool to Automate Generation of Define.xml V2.0 from SDTM Specification for FDA Submission |
Min Chen,
Xiangchen (Bob) Cui |
source |
24 |
| PharmaSUG |
2016 |
AE: An Essential Part of Safety Summary Table Creation |
Rucha Landge |
source |
12 |
| 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 |
CDISC Standards End-to-End: Transitional Hurdles |
Alyssa M. Wittle,
Christine McNichol,
Antonio Cardozo |
source |
6 |
| PharmaSUG |
2016 |
Clinical Graphs Using SAS |
Sanjay N. Matange |
source |
19 |
| PharmaSUG |
2016 |
Codelists Here, Versions There, Controlled Terminology Everywhere |
Shelley Dunn |
source |
12 |
| PharmaSUG |
2016 |
Conformance, Compliance, and Validation: An ADaM Team Lead-s Perspective |
John K. Troxell |
source |
7 |
| PharmaSUG |
2016 |
Consider Define.xml Generation during Development of CDISC Dataset Mapping Specifications |
Vara Prasad Reddy Sakampally,
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 |
Creating Time to Event ADaM Dataset for a Complex Efficacy Endpoint in Multiple Sclerosis Therapeutic Area |
Ittai Rambach |
source |
8 |
| PharmaSUG |
2016 |
Deconstructing ADRS: Tumor Response Analysis Data Set |
Steve Almond |
source |
11 |
| 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 |
Duplicate records - it may be a good time to contact your data management team |
Sergiy Sirichenko,
Max Kanevsky |
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 |
Enhanced OpenCDISC Validator Report for Quick Quality Review |
Ajay Gupta |
source |
12 |
| PharmaSUG |
2016 |
Good versus Better SDTM: Data Listings |
Mario Widel,
Henry B. Winsor |
source |
11 |
| PharmaSUG |
2016 |
Handling Interim and Incomplete Data in a Clinical Trials Setting |
Paul Stutzman |
source |
13 |
| PharmaSUG |
2016 |
Implementation of ADaM Basic Data Structure for Cross-over Studies |
Songhui Zhu |
source |
10 |
| PharmaSUG |
2016 |
Importance of Niche Provider for Successful NDA Submission: Rescue Case Study |
Aparna Poona,
Bhavin Busa,
Tim Southwick |
source |
9 |
| PharmaSUG |
2016 |
Lab CTCAE - the Perl Way |
Marina Dolgin |
source |
7 |
| PharmaSUG |
2016 |
Macro to get data from specific cutoff period |
Kiranmai Byrichetti,
Jeffrey Johnson |
source |
11 |
| PharmaSUG |
2016 |
May the Function Be With You: Helpful SAS Functions, Particularly When Handling CDISC Data |
Angela Lamb |
source |
9 |
| 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 |
Moving up! - SDTM v3.2 - What is new and how to use it |
Alyssa M. Wittle,
Christine McNichol,
Antonio Cardozo |
source |
8 |
| PharmaSUG |
2016 |
New Features in Define-XML V2.0 and Its Impact on SDTM/ADaM Specifications |
Hang Pang |
source |
12 |
| PharmaSUG |
2016 |
Prepare for Re-entry: Challenges and Solutions for Handling Re-screened Subjects in SDTM |
Charity Quick,
Paul Nguyen |
source |
5 |
| 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 checks: Reviewing the overall quality of the deliverables without parallel programming |
Shailendra Phadke,
Veronika Csom |
source |
8 |
| PharmaSUG |
2016 |
Quick and Efficient Way to Check the Transferred Data |
Divyaja Padamati |
source |
6 |
| PharmaSUG |
2016 |
Results-Level Metadata: What, How, and Why |
Frank C. DiIorio,
Jeffrey M. Abolafia |
source |
11 |
| PharmaSUG |
2016 |
SDTM Automation with Standard CRF Pages |
Taylor Markway |
source |
10 |
| 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 |
Strategic Considerations for CDISC Implementation |
Amber Randall,
William Coar |
source |
6 |
| PharmaSUG |
2016 |
Submission-Ready Define.xml Files Using SAS Clinical Data Integration |
Melissa R. Martinez |
source |
10 |
| PharmaSUG |
2016 |
The Benefits and Know-how of Building a Central CDISC-Terminology Dictionary with a Macro System |
Solomon Lee,
Ronghai Bo |
source |
4 |
| PharmaSUG |
2016 |
The CDISC's are coming!! |
Annapurna Ravi,
Caroline Gray |
source |
7 |
| PharmaSUG |
2016 |
The Devil is in the Details - Reporting from Pinnacle 21 (OpenCDISC) Validation Report |
Amy Garrett,
Chris Whalen |
source |
11 |
| PharmaSUG |
2016 |
The Power of Data Access Functions: An example with Dataset-XML Creation |
Joseph W. Hinson |
source |
9 |
| PharmaSUG |
2016 |
The Power of Perl Regular Expressions: Processing Dataset-XML documents back to SAS Data Sets |
Joseph W. Hinson |
source |
9 |
| PharmaSUG |
2016 |
The Standard for the Exchange of Nonclinical Data (SEND): History, Basics, and Comparisons with Clinical Data |
Fred Wood |
source |
10 |
| PharmaSUG |
2016 |
Tips and tricks when developing Trial Design Model Specifications that provide Reductions in Creation time |
Ruth Marisol Rivera Barragan |
source |
10 |
| PharmaSUG |
2016 |
To IDB or Not to IDB: That is the Question |
Kjersten Offenbecker,
Beth Seremula |
source |
7 |
| PharmaSUG |
2016 |
Transforming Biomarker Data into an SDTM based Dataset |
Kiran Cherukuri |
source |
7 |
| PharmaSUG |
2016 |
Trivial Date Tasks? PROC FCMP Can Help |
Jueru Fan |
source |
10 |
| PharmaSUG |
2016 |
TRTP and TRTA in BDS Application per CDISC ADaM Standards |
Maggie Ci Jiang |
source |
8 |
| PharmaSUG |
2016 |
Up-Versioning Existing Define.xml from 1.0 to 2.0 |
Jeff Xia,
Lugang Xie (Larry) |
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 |
UTF What? A Guide to Using UTF-8 Encoded Data in a SDTM Submission |
Michael Stackhouse |
source |
10 |
| PharmaSUG |
2016 |
What is high quality study metadata? |
Sergiy Sirichenko,
Max Kanevsky |
source |
9 |
| PharmaSUG |
2016 |
When ANY Function Will Just NOT Do |
Richann J. Watson,
Karl Miller |
source |
8 |
| PharmaSUG |
2016 |
Working with Composite Endpoints: Constructing Analysis Data |
Pushpa Saranadasa |
source |
7 |
| SGF |
2016 |
Cleaning Up Your SAS Log: Note Messages |
Jennifer M. Srivastava |
source |
8 |
| SGF |
2016 |
Clinical Graphs Using SAS |
Sanjay N. Matange |
source
zip |
20 |
| SGF |
2016 |
Have SAS Annotate Your Blank CRF for You! Plus Dynamically Add Color and Style to Your Annotations |
Steven C. Black |
source
zip |
16 |
| SGF |
2016 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng,
Justina M. Flavin,
Michael Wise |
source |
20 |
| PHUSE EU |
2015 |
A Model for Reviewing the Operational Implementation of the CDISC Standards |
Andy Richardson |
source
presentation source |
7 |
| PHUSE EU |
2015 |
A Modularised Approach to the Development of a Data Science Tool |
Guiseppe Di Monaco |
source
presentation source |
10 |
| PHUSE EU |
2015 |
Access to CDISC SHARE Metadata: A La Cate, Prix Fixe or Table d'Horte? |
Kenneth Stoltzfus |
source
presentation source |
9 |
| PHUSE EU |
2015 |
ADaM - Our Experience |
Rob Wartenhorst |
source
presentation source |
5 |
| PHUSE EU |
2015 |
ADaM Reviewer's Guide - Interpretation and Implementation |
Steve Griffiths |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Analysing the Role of a Lead Programmer |
Ester Schoeman |
source
presentation source |
9 |
| PHUSE EU |
2015 |
Are Your Ready for SEND? |
Roman Radelicki |
source
presentation source |
8 |
| 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 |
Automating Production of the blankcrf.pdf in a CRO Environment |
Jonathan North |
source
presentation source |
10 |
| PHUSE EU |
2015 |
CDISC Standards and the Semantic Web |
David Iberson-Hurst |
source
presentation source |
9 |
| 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 |
Dataset-XML - A New CDISC Standard for Data Exchange |
Julie A. Maddox,
Lex Jansen |
source
presentation source |
16 |
| PHUSE EU |
2015 |
Developing annotated CRF: SAS, Excel and patience as your friends |
Ilias Pyrnokokis |
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 |
Ensuring Data Quality in Outsourced Studies - The Role of the Data Scientist |
Sarah Malbon,
Vikki Horton |
source
presentation source |
8 |
| PHUSE EU |
2015 |
EPOCH in Reverse |
Ann Croft |
source
presentation source |
7 |
| PHUSE EU |
2015 |
Errors Beyond Open CDISC Validator |
Gayatri Karkera,
Nehan Mohan |
source
presentation source |
4 |
| PHUSE EU |
2015 |
Finding Out about Findings About |
Carolina Clark-Steel |
source
presentation source |
2 |
| PHUSE EU |
2015 |
Flexible Solutions for Insight and Data-driven Innovation |
Catharina Dahblo |
source
presentation source |
6 |
| 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 |
Implementation of an in-house Data QC Tool to Streamline SDTM Production Data |
Karlien Knevels |
source
presentation source |
3 |
| PHUSE EU |
2015 |
Improving CDISC SDTM Data Quality & Compliance Right from the Beginning |
Bharat Chaudhary,
Padamsimh Balekundri |
source
presentation source |
9 |
| 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 |
Introduction to CDISC BRIDG |
Joerg Dillert |
source
presentation source |
11 |
| PHUSE EU |
2015 |
Introduction to GPP with Hints and Tips to Make them Second Nature |
Alexandra Marquat,
Shafi Chowdhury |
source
presentation source |
7 |
| PHUSE EU |
2015 |
Managing ADaM Metadata |
Ann Fitzherbert,
Khilit Shah |
source
presentation source |
6 |
| PHUSE EU |
2015 |
Managing Data Standards Libraries Compliance (to CDISC) |
Deborah Paletta |
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 |
Results-Level Metadata: What, How, and Why |
Frank C. DiIorio,
Jeffrey M. Abolafia |
source
presentation source |
11 |
| PHUSE EU |
2015 |
Standardised Reporting Using ADaM (STREAM Model) |
Ankur Chakraborty |
source
presentation source |
2 |
| PHUSE EU |
2015 |
The Highs, Lows and Lessons of a First-Time Study Lead |
Bethan Thomas |
source
presentation source |
7 |
| PHUSE EU |
2015 |
The SAS Clinical Standards Toolkit - A helpful tool for creating CDISC SDTM compliant study data |
Nicolai Haag |
source
presentation source |
2 |
| PHUSE EU |
2015 |
Therapeutic Area Standards and their Impact on Current SDTM Implementations |
Johannes Ulander,
Niels Both |
source
presentation source |
6 |
| SESUG |
2015 |
Reporting of treatment emergent adverse events based on pooled data Analysis or Country Specific Submissions: A case study |
Sheetal Shiralkar |
source |
8 |
| WUSS |
2015 |
Building and Customizing a CDISC Compliance and Data Quality Application |
Wayne (Weizhen) Zhong,
Accretion Softworks |
source |
5 |
| WUSS |
2015 |
How to Speed Up Your Validation Process Without Really Trying |
Alice M. Cheng |
source |
23 |
| PharmaSUG CN |
2015 |
A Macro to Add Variables to SDTM Standard Domains |
Xianhua Zeng |
|
5 |
| 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 |
Generating Define.xml Using SAS By Element-by-Element And Domain-by-Domian Mechanism |
Lina Qin |
|
12 |
| PharmaSUG CN |
2015 |
Generic Macros for Data Mapping |
Qian Zhao,
John Wang,
Ruofei Hao |
|
9 |
| PharmaSUG CN |
2015 |
Hands-On ADaM ADAE Development |
Sandra Minjoe |
|
7 |
| PharmaSUG CN |
2015 |
Managing the analysis programming effort for an NDA submission |
Yu Cheng,
Quan Zhou |
|
8 |
| PharmaSUG CN |
2015 |
Multilingual data support in Dataset-XML with SAS Clinical Data Integration |
Jing Gao |
|
12 |
| 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 |
The loop within: A macro on looping variables and observations |
Eduard Joseph Siquioco |
|
9 |
| PharmaSUG CN |
2015 |
Tips for efficient CDISC eCRT production |
Lanting Li,
Yu Zhu,
Yuejuan Meng,
Huan Zhu |
|
11 |
| 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 SAS Macro Tool to Automate Generation of Define.xml V2.0 from ADaM Specification for FDA Submission |
Min Chen,
Xiangchen (Bob) Cui |
source |
28 |
| 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 Unique Way to Annotate Case Report Forms (CRFs) in PDF, Using Forms Data Format (FDF) Techniques |
Boxun Zhang,
Tyler Kelly |
source |
6 |
| PharmaSUG |
2015 |
A Way to Manage Clinical Project Metadata in SAS Enterprise Guide |
David L. Wang |
source |
5 |
| PharmaSUG |
2015 |
Accelerate define.xml generation using defineReady |
Senthilkumar Karuppiah,
Georgina Wood |
source |
4 |
| PharmaSUG |
2015 |
ADaM Example for a Complex Efficacy Analysis Dataset |
Milan Mangeshkar,
Sandra Minjoe |
source |
8 |
| PharmaSUG |
2015 |
ADDL Model for Device Analysis |
Priya Gopal |
source |
6 |
| PharmaSUG |
2015 |
Advantages and Disadvantages of Two Commonly Used CRO Resourcing Models in the Pharmaceutical SAS Programming Environment |
Ying (Evelyn) Guo,
Mark Matthews |
source |
7 |
| 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 |
Challenges in Developing ADSL with Baseline Data |
Hongyu Liu,
Hang Pang |
source |
6 |
| PharmaSUG |
2015 |
Considerations in ADaM Occurrence Data: Handling Crossover Records for Non-Typical Analysis |
Karl Miller,
Richann J. Watson |
source |
6 |
| PharmaSUG |
2015 |
Considerations in Conforming Data from Multiple Implantable Medical Devices to CDISC Standards Using SAS |
Julia Yang |
source |
9 |
| PharmaSUG |
2015 |
Considerations in Submitting Non-Standard Variables: Supplemental Qualifiers, Findings About, or a Custom Findings Domain |
Jerry Salyers,
Richard Lewis,
Fred Wood |
source |
6 |
| PharmaSUG |
2015 |
DIABETES: Submission Data Standards and Therapeutic End Points |
Naveed M Khaja |
source |
9 |
| PharmaSUG |
2015 |
Evaluating SDTM SUPP Domain For AdaM - Trash Can Or Buried Treasure |
Xiaopeng Li,
Yi Liu,
Chun Feng |
source |
7 |
| PharmaSUG |
2015 |
Fresh Cup of Joe: Utilizing Java to automate Define.XML for SDTM Origin mapping from SAS aCRF PDFs |
Tony Cardozo |
source |
9 |
| PharmaSUG |
2015 |
Generic Macros for Data Mapping |
Qian Zhao,
Jun (John) Wang,
Ruofei Hao |
source |
9 |
| PharmaSUG |
2015 |
Get a Data Dictionary using PROC contents: Easily |
Beatriz Garcia,
Alberto Hernandez |
source |
5 |
| PharmaSUG |
2015 |
Have SAS Annotate Your Blank CRF for You! Plus Dynamically Add Color and Style to Your Annotations |
Steven C. Black |
source |
12 |
| PharmaSUG |
2015 |
Implementing Various Baselines for ADaM BDS datasets |
Songhui Zhu |
source |
7 |
| PharmaSUG |
2015 |
Improving Data Quality - Missing Data Can Be Your Friend! |
Julie Chen |
source |
12 |
| PharmaSUG |
2015 |
Introducing a Similarity Statistic to Compare Data Libraries for Improving Program Efficiency for Similar Clinical Trials |
Taylor Markway,
Amanda Johnson |
source |
5 |
| PharmaSUG |
2015 |
It Depends On Your Analysis Need |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2015 |
Leveraging ADaM Principles to Make Analysis Database and Table Programming More Efficient |
Andrew L Hulme |
source |
13 |
| PharmaSUG |
2015 |
LOCF vs. LOV in Endpoint DTYPE Development with CDISC ADaM Standards |
Maggie Ci Jiang |
source |
6 |
| PharmaSUG |
2015 |
Managing the Evolution of SAS Programming |
Carey G. Smoak |
source |
4 |
| PharmaSUG |
2015 |
Mlibcompare - keep an eye on the changes of your data |
Wen Shi |
source |
29 |
| PharmaSUG |
2015 |
PhUSE De-Identification Working Group: Providing De-Identification Standards to CDISC Data Models |
Jean-Marc Ferran,
Jacques Lanoue |
source |
8 |
| PharmaSUG |
2015 |
Process and Programming Challenges in Producing Define.xml |
Mike Molter |
source |
13 |
| PharmaSUG |
2015 |
Proper Parenting: A Guide in Using ADaM Flag/Criterion Variables and When to Create a Child Dataset |
Richann J. Watson,
Karl Miller,
Paul K. Slagle |
source |
10 |
| PharmaSUG |
2015 |
SAS Tools for Working with Dataset-XML files |
Lex Jansen |
source |
18 |
| PharmaSUG |
2015 |
SDTM Annotations: Automation by implementing a standard process |
Geo Joy,
Andre Couturier |
source |
11 |
| 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 |
Team-work and Forensic Programming: Essential Foundations of Indestructible Projects |
Brian P. Fairfield-Carter |
source |
14 |
| PharmaSUG |
2015 |
The Best Practices of CDISC ADaM Validation Checks: Past, Present, and Future |
Shelley Dunn,
Ed Lombardi |
source |
9 |
| PharmaSUG |
2015 |
The Implementation of Display Auto-Generation with Analysis Results Metadata Driven Method |
Chengxin Li |
source |
11 |
| PharmaSUG |
2015 |
The Most Common Issues in Submission Data |
Sergiy Sirichenko,
Max Kanevsky |
source |
9 |
| PharmaSUG |
2015 |
Tips on Creating a Strategy for a CDISC Submission |
Rajkumar Sharma |
source |
5 |
| 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 |
Usage of OpenCDISC Community Toolset 2.0 for Clinical Programmers |
Sergiy Sirichenko,
Michael DiGiantomasso,
Travis Collopy |
source |
19 |
| PharmaSUG |
2015 |
Using SAS Clinical Data Integration to Roundtrip a Complete Study Study Metadata (Define-XML) and Study Data (Dataset-XML) |
Ken Ellis |
source |
19 |
| PharmaSUG |
2015 |
What is the "ADAM OTHER" Class of Datasets, and When Should it be Used? |
John K. Troxell |
source |
5 |
| PharmaSUG |
2015 |
What to Expect in SDTMIG v3.3 |
Fred Wood |
source |
10 |
| SESUG |
2014 |
SDTM What? ADaM Who? A Programmer's Introduction to CDISC |
Venita DePuy |
source |
9 |
| SESUG |
2014 |
Stretching Data Training Methods: A Case Study in Expanding SDTM Skills |
Richard Addy |
source |
4 |
| 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 |
ADaM Conversions: The Good, The Bad and The Ugly |
Carla Santillán,
Jessica Minuke |
source
presentation source |
11 |
| PHUSE EU |
2014 |
ADaM Standards: What's New? |
Gavin Winpenny |
source
presentation source |
9 |
| PHUSE EU |
2014 |
Automated SDTM Creation and Discrepancy Detection Jobs: The Numbers Tell the Tale |
Joris De Bondt |
source
presentation source |
2 |
| PHUSE EU |
2014 |
Automating Production of the blankcrf.pdf |
Walter H. Hufford Jr. |
source
presentation source |
5 |
| PHUSE EU |
2014 |
CDISC Dataset-XML - A Dataset Structure for Clinical Trial Data Transport for Future Drug Submissions |
Joerg Dillert |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Challenges of Different MedDRA Versions for Integrated Data and Databases |
Peter Bonata |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Challenges with the Interpretation of CDIOSC - Who Can We Trust? |
Linda Palm Simonsson |
source
presentation source |
10 |
| PHUSE EU |
2014 |
Clinical Study Data Processes @ LEO Pharma |
Joergen Iversen |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Considerations in Creating Transparent SDTM-Based Datasets |
Jerry Salyers,
Richard Lewis |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Consistent Data Delivery |
Thevaki Mahedevan |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Discover Define-XML |
Mark Wheeldon,
Kevin Burges |
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 |
FDA Guidance on Standardised Study Data for Electronics Submissions |
Lauren L. Shinaberry,
Éanna Kiely |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Findings About: "Findings About" |
Madhura Khare |
source
presentation source |
8 |
| 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 |
Handling Non-Standardised Questionnaires |
Anne Sophie Beckx,
Éanna Kiely |
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 |
How to Improve Performance on SDD 3.5 |
Rob Wartenhorst |
source
presentation source |
3 |
| PHUSE EU |
2014 |
Implementation of CDISC ADaM in the Pharmacokinetics Department |
Joanna Magielse,
Tineke Callant |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Implementation of Oncology Specific SDTM Domains |
Jacintha Eben |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Is Your Clinical Data Standards Library Ready for Change? Adapting to TA Specific Standards |
Lauren L. Shinaberry |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Leveraging R And Shiny for Point and Click ADaM Analysis [presentation] |
Ian Fleming |
source |
10 |
| PHUSE EU |
2014 |
Looking for SDTM Migration Specialist |
Angelo Tinazzi |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Metadata Design for Analysis and Reporting |
Gopinath Viswanathan,
Giri Balasubramanian |
source
presentation source |
2 |
| PHUSE EU |
2014 |
Metadata, Study Standards, Interoperability: Key Concepts Toward Compliance to FDA Guidance |
Isabelle de Zegher |
source
presentation source |
3 |
| PHUSE EU |
2014 |
Models, Metadata and Messaging: Exploring Standards Governance in the CDISC Era |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE EU |
2014 |
My Transition From Placement Student to Permanent Employee Within the Same Company |
Robyn Rosser |
source
presentation source |
4 |
| PHUSE EU |
2014 |
Representation of CDISC Foundational Standards Using RDF Authors |
Scott A. Bahlavooni,
Frederik Malfait |
source
presentation source |
3 |
| PHUSE EU |
2014 |
SDTM in Business Intelligence |
Mike Collinson |
source
presentation source |
3 |
| PHUSE EU |
2014 |
SDTM Mapping Becomes more EASY with SAS Clinical Data Integration |
Saumilkumar Tripathi |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Successfully Embracing Challenges to CDISC Standards [presentation] |
Elke Sennewald |
source |
30 |
| PHUSE EU |
2014 |
The On-Going Evolutionary Changes of our Industry [presentation] |
Christian Mueller |
source |
34 |
| PHUSE EU |
2014 |
Traceability: Plan Ahead for Future Needs |
Sandra Minjoe |
source
presentation source |
8 |
| 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 CDISC Validation Tools in a Validated Hosted Environment |
Sandeep Juneja |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Why Don't You Define It? |
Nick De Donder,
Anne-Sophie Bekx |
source
presentation source |
7 |
| PharmaSUG CN |
2014 |
An implementation of XSL-FO techniques to convert define.pdf from define.xml |
Kyle Chang |
|
6 |
| PharmaSUG CN |
2014 |
Brief Introduction of Oncology Domains in SDTMIG,Version 3.2 |
Haishan Kadeerbai |
|
3 |
| PharmaSUG CN |
2014 |
Design and Construct Efficacy Analysis Datasets in Later Phase Oncology Study |
Huadan Li,
Changhong Shi |
|
9 |
| PharmaSUG CN |
2014 |
From Coal Mining to Data Mining: Advancing Programming Management for Clinical Projects with Text Analytics |
Zhouming Sun |
|
10 |
| PharmaSUG CN |
2014 |
Submission of Pharmacokinetics (PK) Data in a CDISC Compliant Format |
Yu Zhu |
|
9 |
| WUSS |
2014 |
Exploring Phase 1 ADaM Deriving System from SDTM |
Yiwen Li |
source |
4 |
| WUSS |
2014 |
TLF Validation Etiquette:What to Say, When to Say, How to Say, Why to Say |
Karen Walker |
source |
10 |
| PharmaSUG |
2014 |
A Guide to the ADaM Basic Data Structure for Dataset Designers |
Michelle Barrick,
John K. Troxell |
source |
12 |
| PharmaSUG |
2014 |
A Macro to Create Occurrence Flags for Analysis Datasets |
Ed Lombardi |
source |
4 |
| PharmaSUG |
2014 |
A Road Map to Successful CDISC ADaM Submission to FDA: Guidelines, Best Practices & Case Studies |
Vikash Jain,
Sandra Minjoe |
source |
9 |
| PharmaSUG |
2014 |
A SAS Macro to address PK timing variables issues |
Timothy J. Harrington |
source |
14 |
| PharmaSUG |
2014 |
A Toolkit to Check Dictionary Terms in SDTM |
Huei-Ling Chen,
Helen Wang |
source |
8 |
| 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 |
An ADaM Interim Dataset for Time-to-Event Analysis Needs |
Tom Santopoli,
Kimberly Minkalis,
Sandra Minjoe |
source |
9 |
| PharmaSUG |
2014 |
An Alternative Way to Create Define.XML for ADaM with SAS Macro Automation |
Yiwen Li |
source |
4 |
| PharmaSUG |
2014 |
An Alternative Way to Detect Invalid Reference Records in Supplemental Domains |
Steven Wang |
source |
5 |
| PharmaSUG |
2014 |
Applying ADaM BDS Standards to Therapeutic Area Ophthalmology |
Songhui Zhu |
source |
10 |
| PharmaSUG |
2014 |
Automating Production of the blankcrf.pdf |
Walter H. Hufford Jr. |
source |
5 |
| PharmaSUG |
2014 |
Automation of ADAM Dataset Creation with a Retrospective, Prospective and Pragmatic Process |
Karin LaPann,
Terek J. Peterson |
source |
6 |
| PharmaSUG |
2014 |
BreakOnWord: A Macro for Partitioning Long Text Strings at Natural Breaks |
Richard Addy,
Charity Quick |
source |
8 |
| PharmaSUG |
2014 |
CDISC Electronic Submission |
Kevin Lee |
source |
6 |
| PharmaSUG |
2014 |
CDISC Mapping and Supplemental Qualifiers |
Arun Raj Vidhyadharan,
Sunil Mohan Jairath |
source |
6 |
| PharmaSUG |
2014 |
Challenges in Processing Clinical Lab Data |
Alan Meier |
source |
15 |
| PharmaSUG |
2014 |
Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS |
Karin LaPann,
Terek J. Peterson |
source |
20 |
| PharmaSUG |
2014 |
Cleaning up your SAS log: Overwritten Variable Info Messages |
Jennifer M. Srivastava |
source |
6 |
| 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 |
Considerations in the Submission of Exposure Data in SDTM-Based Datasets |
Fred Wood,
Jerry Salyers,
Richard Lewis,
Kristin Kelly |
source |
6 |
| PharmaSUG |
2014 |
Creating Define-XML version 2 with the SAS Clinical Standards Toolkit 1.6 |
Lex Jansen |
source |
33 |
| PharmaSUG |
2014 |
Creating Define.xml v2 Using SAS for FDA Submissions |
Qinghua (Kathy) Chen,
James Lenihan |
source |
20 |
| PharmaSUG |
2014 |
D is for Dynamic, putting Dynamic back into CDISC (A simple macro utilizing PROC SQL which auto-formats continuous variables for lab tables) |
Steven C. Black |
source |
9 |
| 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 |
DefKit : A Micro Framework for CDISC Define-XML Application Development |
Lei Zhang |
source |
23 |
| PharmaSUG |
2014 |
Developing ADaM Specifications to Embrace Define-XML 2.0.0 Requirements |
Lin Yan |
source |
10 |
| 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 |
Forging New SDTM Standards for In-Vitro Diagnostic (IVD) Devices: A Use-Case |
Carey G. Smoak,
Smitha Krishnamurthy,
Mansi Singh,
Sy J. Truong |
source |
6 |
| 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 |
Hands-On ADaM ADAE Development |
Sandra Minjoe,
Kimberly Minkalis |
source |
7 |
| PharmaSUG |
2014 |
Having Fun with RACE Derivation in DM Domain |
Chunxia Lin,
Deli Wang |
source |
5 |
| PharmaSUG |
2014 |
How Valued is Value Level Metadata? |
Shelley Dunn |
source |
12 |
| PharmaSUG |
2014 |
Let SAS Improve Your CDISC Data Quality |
Wayne (Weizhen) Zhong |
source |
12 |
| PharmaSUG |
2014 |
OpenCDISC Validator Implementation: A Complex Multiple Stakeholder Process |
Terek J. Peterson,
Gareth Adams |
source |
9 |
| PharmaSUG |
2014 |
Referencing Medical Device Data in Standard SDTM domains |
Timothy L Bullock,
Ramkumar Krishnamurthy |
source |
7 |
| PharmaSUG |
2014 |
Round Trip Ticket - Using the Define.xml file to Send and Receive your Study Specifications |
Julie A. Maddox |
source |
10 |
| 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 |
SAS as a Tool to Manage Growing SDTM+ Repository for Medical Device Studies |
Julia Yang |
source |
12 |
| PharmaSUG |
2014 |
SDTM, ADaM and define.xml with OpenCDISC |
Angela S. Ringelberg,
Tracy Sherman |
source |
21 |
| PharmaSUG |
2014 |
That SASsy Lab Data |
Amie Bissonett |
source |
6 |
| PharmaSUG |
2014 |
The New Tradition: SAS Clinical Data Integration |
Vincent J. Amoruccio,
Janet E. Stuelpner |
source |
18 |
| PharmaSUG |
2014 |
TLF Validation Etiquette:What to Say, When to Say, How to Say, Why to Say |
Karen Walker |
source |
10 |
| PharmaSUG |
2014 |
XML in a SAS and Pharma World |
Mike Molter |
source |
19 |
| SGF |
2014 |
Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS |
Karin LaPann,
Terek J. Peterson |
source |
19 |
| SGF |
2014 |
Converting Clinical Database to SDTM: The SAS Implementation |
Hong Chen |
source |
5 |
| SGF |
2014 |
Creating Define.xml v2 Using SAS for FDA Submissions |
Qinghua (Kathy) Chen,
James Lenihan |
source |
20 |
| WUSS |
2013 |
Building a Controlled Statistical Programming Environment |
Wayne F. Woo |
source |
10 |
| WUSS |
2013 |
Implementation of DEFINE.XML Generators using SAS Hash Objects and User-Defined Functions |
Lei Zhang |
source |
19 |
| WUSS |
2013 |
Introduction to the CDISC Standards |
Sandra Minjoe |
source |
10 |
| SESUG |
2013 |
Imputing Dose Levels for Adverse Events |
John R. Gerlach,
Igor Kolodezh |
source |
8 |
| SESUG |
2013 |
Patient Profile Graphs Using SAS |
Sanjay N. Matange |
source |
14 |
| PHUSE EU |
2013 |
A How-To Guide for Extending Controlled Terminology Using SAS Clinical Data Integration [presentation] |
Melissa R. Martinez |
source |
71 |
| PHUSE EU |
2013 |
ADaM Datasets - Standard and Submission Ready |
Karin Fleischer Steffensen |
source
presentation source |
6 |
| PHUSE EU |
2013 |
ADaM Standards - Organising the Unorganised |
Heike Reichert |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Are You out of Your Mind? CDISC Mappings Using the Mind Map Tool |
Niels Both,
Johannes Ulander |
source
presentation source |
5 |
| PHUSE EU |
2013 |
Bringing Skeletons out of the Closet |
Parag Naithani |
source
presentation source |
10 |
| PHUSE EU |
2013 |
CDISC Journey on Solid Tumor Studies using RECIST 1.1 [presentation] |
Kevin Lee |
source |
36 |
| PHUSE EU |
2013 |
Check your Standards - An Example |
Véronique Bourcier |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Considerations in the Submission of Holter (EG) Data in an SDTM Compliant Format |
Elsa Lozachmeur,
Sophie Arnould |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Datacut Strategies: What, Why & How |
Hiren Naygandhi |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Define-XML v2 - What's New |
Lex Jansen |
source
presentation source |
15 |
| PHUSE EU |
2013 |
Designing ADaM Datasets: KISS the Complexity Goodbye [presentation] |
Bill J. Gibson |
source |
13 |
| PHUSE EU |
2013 |
Economic Evaluation in Clinical Trials. You Can Do it with SAS |
Artur Usov |
source
presentation source |
12 |
| PHUSE EU |
2013 |
Evolving Regulatory Guidance on the Submission of Standardised Data [presentation] |
James R. Johnson |
source |
25 |
| PHUSE EU |
2013 |
EXACT - A Metadata Driven System for Creating Standard Mockups and Data Displays [presentation] |
Kent Letourneau |
source |
55 |
| PHUSE EU |
2013 |
Going Against the Flow: Backmapping SDTM Data |
Panteleo Nacci |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Interpretation of the Output from the OpenCDISC Checker |
Joergen Iversen |
source
presentation source |
5 |
| PHUSE EU |
2013 |
Interpreting CDISC ADaM IG Through Users Interpretation |
Angelo Tinazzi |
source
presentation source |
12 |
| PHUSE EU |
2013 |
One Vision, Many Interpretations? |
Todd Case |
source
presentation source |
3 |
| PHUSE EU |
2013 |
Orphan Indication Therapies: Programming for a Patient Population without Options [presentation] |
Todd Case |
source |
24 |
| PHUSE EU |
2013 |
Overcoming Difficulties in Implementing RECIST Criteria |
Gerlind Ruhnke |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Round Trip Ticket - Using the Define.xml file to Send and Receive your Study Specifications |
Julie A. Maddox |
source
presentation source |
10 |
| 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 |
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 |
Standards Governance - A First Insight |
Claudia Meurer |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Supporting End to End Standards in Study Setup |
Anna Louise Wilson |
source
presentation source |
5 |
| PHUSE EU |
2013 |
The Evolution of SDTM - What's New |
Tina Apers |
source
presentation source |
5 |
| PHUSE EU |
2013 |
The Missing Link: Results Level Metadata |
Jeffrey M. Abolafia |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Two-way Ticket, Please...All aboard the SAS Clinical Standards Toolkit 1.5 Express |
Lex Jansen |
source
presentation source |
2 |
| MWSUG |
2013 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
|
7 |
| NESUG |
2013 |
Automating Validation of Define.xml using SAS |
Prafulla Girase,
Robert Agostinelli |
|
8 |
| NESUG |
2013 |
The ADaM Solutions to Non-endpoints Analyses |
Chengxin Li |
|
12 |
| NESUG |
2013 |
Using SAS and D3.js to create interactive visualizations for ADaM and SDTM data. |
Nathan Mockler |
|
12 |
| PharmaSUG |
2013 |
A Generic Concept to Handle SDTM (and other CDISC) Data Sets |
Peter Schaefer |
source |
8 |
| PharmaSUG |
2013 |
ADaM Datasets for Graphs |
Kevin Lee,
Chris Holland |
source |
15 |
| PharmaSUG |
2013 |
Analysis of Concomitant Medication Data |
Joseph J. Hantsch,
Karl Miller |
source |
4 |
| PharmaSUG |
2013 |
Automating Validation of Define.xml using SAS |
Prafulla Girase,
Robert Agostinelli |
source |
8 |
| PharmaSUG |
2013 |
Bring Excel file with SDTM data in multiple sheets to SAS |
Mindy Wang |
source |
7 |
| PharmaSUG |
2013 |
Building Traceability for End Points in Analysis Data Sets Using SRCDOM, SRCVAR, and SRCSEQ Triplet |
Xiangchen (Bob) Cui,
Tathabbai Pakalapati,
Qunming Dong |
source |
12 |
| PharmaSUG |
2013 |
Considerations in Data Modeling when Creating Supplemental Qualifiers Datasets in SDTM-Based Submissions |
Fred Wood |
source |
12 |
| PharmaSUG |
2013 |
Considerations in the Use of Timing Variables in Submitting SDTM-Compliant Datasets |
Jerry Salyers,
Richard Lewis,
Fred Wood |
source |
6 |
| PharmaSUG |
2013 |
Data Standards Will Be Required: Challenges for Medical Device Submissions |
Carey G. Smoak,
Kit Howard,
Fred Wood,
Rhonda Facile |
source |
5 |
| PharmaSUG |
2013 |
Defensive Programming and Error-handling: The Path Less Travelled |
Tracy Sherman,
Angela S. Ringelberg |
source |
9 |
| PharmaSUG |
2013 |
Derived observations and associated variables in ADaM datasets |
Arun Raj Vidhyadharan |
source |
7 |
| PharmaSUG |
2013 |
Designing and Tuning ADaM Datasets |
Songhui Zhu |
source |
9 |
| 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 |
Good vs Better SDTM: Limitations as Operational Model |
Henry B. Winsor,
Mario Widel |
source |
4 |
| PharmaSUG |
2013 |
Hands-On ADaM ADAE Development |
Sandra Minjoe |
source |
7 |
| PharmaSUG |
2013 |
If 'standard code' is so great ... |
Brian P. Fairfield-Carter |
source |
12 |
| PharmaSUG |
2013 |
Implementation Considerations for PARAM/PARAMCD Using ADaM BDS |
Karl Miller,
Joseph J. Hantsch |
source |
5 |
| 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 |
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 |
Let SAS Do Your DIRty Work |
Richann J. Watson |
source |
7 |
| 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 |
Macro to Conduct Consistency Checks |
Walter H. Hufford Jr. |
source |
6 |
| PharmaSUG |
2013 |
Map Metadata - Going Beyond the Obvious/Connecting the Dots |
Gregory C. Steffens,
Praveen Garg |
source |
8 |
| 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 |
Methods to Derive COVAL-COVALn in CO Domain |
Chunxia Lin |
source |
8 |
| PharmaSUG |
2013 |
OpenCDISC: Beyond Point and Click |
Frank C. DiIorio |
source |
12 |
| PharmaSUG |
2013 |
Patient Profile Graphs Using SAS |
Sanjay N. Matange |
source |
14 |
| PharmaSUG |
2013 |
Programming Validation Tips prior to using OpenCDISC validator |
Dany Guerendo |
source |
12 |
| PharmaSUG |
2013 |
Running OpenCDISC in SAS |
Kevin Lee |
source |
7 |
| PharmaSUG |
2013 |
SDTM Harmonization in the Absence of CDASH - A Modularized Approach to Domain Programming |
Annie S. Guo |
source |
12 |
| PharmaSUG |
2013 |
SDTM, ADaM and define.xml with OpenCDISC |
Angela S. Ringelberg,
Tracy Sherman |
source |
16 |
| PharmaSUG |
2013 |
Some Strategies for Validating Your Data before Submission |
Frank L. Roediger,
Sandeep Juneja |
source |
8 |
| 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 Y2K17 Bug! Using Metadata to Respond to PDUFA V Requirements |
Vincent J. Amoruccio |
source |
12 |
| PharmaSUG |
2013 |
Traceability in the ADaM Standard |
Ed Lombardi |
source |
8 |
| PharmaSUG |
2013 |
Using the SAS Clinical Standards Toolkit 1.5 to Import CDISC ODM Files |
Lex Jansen |
source |
28 |
| PharmaSUG |
2013 |
When Asked for Subject Incidences, Go Ahead and FREQ OUT |
Rod Norman |
source |
8 |
| SGF |
2013 |
A Practical Approach to Creating Define.XML by Using SDTM Specifications and Excel functions |
Amos Shu |
source
pdf |
7 |
| SGF |
2013 |
A Preventive Approach for Automatic Checking of CDISC ADaM Metadata to Detect Noncompliance [presentation] |
Xiangchen (Bob) Cui,
Min Chen,
Tathabbai Pakalapati |
source |
2 |
| SGF |
2013 |
A Simple Macro to Minimize Data Set Size |
Amos Shu |
source
pdf |
4 |
| SGF |
2013 |
Adding New Rows in the ADaM Basic Data Structure: When and How |
Mario Widel,
Sandra Minjoe |
source |
12 |
| SGF |
2013 |
Building Traceability for End Points in Analysis Data Sets Using SRCDOM, SRCVAR, and SRCSEQ Triplet |
Qunming Dong,
Tathabbai Pakalapati,
Xiangchen (Bob) Cui |
source
pdf |
12 |
| SGF |
2013 |
Developing Your SDTM Programming Toolkit |
David A. Scocca |
source |
10 |
| 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 |
From SDTM to ADaM |
Bob Lan,
Regan Li,
Sai Ma,
Suwen Li |
source
pdf |
7 |
| SGF |
2013 |
Knowing When To Start, Where You Are, and How Far You Need To Go: Customized Software Tracks Project Workflow, Deliverables, and Communication |
Eric Vandervort |
source |
14 |
| SGF |
2013 |
Patient Profile Graphs Using SAS |
Sanjay N. Matange |
source |
14 |
| SGF |
2013 |
The Hash-of-Hashes as a "Russian Doll" Structure: An Example with XML Creation |
Joseph W. Hinson |
source |
21 |
| SGF |
2013 |
Using SAS to Dynamically Generate SAS Code in Order to Display Both Variable Label and Name as Column Header in PROC REPORT and PROC PRINT |
Heli Ghandehari,
Victor Lopez |
source |
5 |
| SGF |
2013 |
Using the ADaM ADAE Structure for Non-AE Data |
Mario Widel,
Sandra Minjoe |
source |
13 |
| NESUG |
2012 |
Harnessing the Power of SAS ISO 8601 Informats, Formats, and the CALL IS8601_CONVERT Routine |
Kim M. Wilson |
|
15 |
| NESUG |
2012 |
Step by Step Approach to Port CDISC SAS Data Integration Repositories on Cross Platforms Using %OMAPORT Macro |
Salman Ali |
|
6 |
| SCSUG |
2012 |
POSTER: ADaM Implications of the CDER Data Standards Common Issues Document |
Sandra Minjoe |
source |
6 |
| PHUSE EU |
2012 |
ADaM Or SDTM? A Comparision of Pooling Strategies for Integrated Analyses in the Age of CDISC |
Joerg Guettner,
Alexandru Cuza |
source
presentation source |
7 |
| PHUSE EU |
2012 |
An Introduction to SDTM, 298 Pages in 20 Minutes? |
Jennie McGuirk |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Approaches to Creating ADaM Subject-Level Analysis Datasets (ADSL) for Integrated Analyses |
Thomas Clinch,
Nate Friemark |
source
presentation source |
6 |
| PHUSE EU |
2012 |
CDISC Advisory Board Validation Project - Best Practices for CDISC Validation Rules |
Lauren L. Shinaberry |
source
presentation source |
4 |
| PHUSE EU |
2012 |
Considerations for CSR Output Production from ADaM Datasets |
Andrew Noller |
source
presentation source |
1 |
| 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 |
Deep Dive into ODM Validation |
Ronald Steinhau |
source
presentation source |
3 |
| PHUSE EU |
2012 |
Define.xml for ADaM: From Results to SDTM [presentation] |
Dimitri Kutsenko |
source |
5 |
| PHUSE EU |
2012 |
Enhancing Research Through Clinical Data Standardisation |
Pankaj Bhardwaj |
source
poster source |
1 |
| PHUSE EU |
2012 |
Integrating Clinical Images into the Data Review Process |
Kellie Riley |
source
poster source |
5 |
| PHUSE EU |
2012 |
Interpreting ADaM Standards with OpenCDISC |
Trupti Bal,
Madhura Paranjape |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Mapping the Company's Legacy Data Model to SDTM |
Anja Feuerbacher,
Bruce Rogers |
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 |
SAS Clinical Standards Toolkit: define.xml and Value Level Metadata |
Gene Lightfoot |
source
presentation source |
27 |
| PHUSE EU |
2012 |
SDTM and AdaM: Metadata Playing Together Nicely |
Kenneth Stoltzfus |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Simplifying SAS Clinical Standards Toolkit - Where's the Easy Button? |
Gene Lightfoot |
source
poster source |
6 |
| 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 |
Validation CDISC Data with the SAS Clinical Standards Toolkit |
Nicolai Hagg |
source
poster source |
1 |
| PHUSE EU |
2012 |
Validation to define.xml |
Sam Tomioka,
Steven Huang |
source
poster source |
8 |
| SESUG |
2012 |
A SAS Macro Approach to Assign CTCAE Grades to Laboratory |
Mei Dey,
Lisa Pyle |
source |
10 |
| SESUG |
2012 |
A Standard SAS Program for Corroborating OpenCDISC Error Messages |
John R. Gerlach |
source |
11 |
| SESUG |
2012 |
An Introduction to the Clinical Standards Toolkit |
Mike Molter |
source |
13 |
| SESUG |
2012 |
Generating SUPPQUAL Domains From SDTM-Plus Domains |
John R. Gerlach,
Glenn O'Brien |
source |
6 |
| SESUG |
2012 |
Knowing When To Start, Where You Are, and How Far You Need To Go: Customized Software Tracks Project Workflow, Deliverables, and Communication |
Eric Vandervort |
source |
14 |
| SESUG |
2012 |
The SDTM Programming Toolkit |
David A. Scocca |
source |
10 |
| WUSS |
2012 |
Developing Integrated Summary of Safety Database using CDISC Standards |
Rajkumar Sharma |
source |
7 |
| PharmaSUG CN |
2012 |
Challenge in Legacy Studies Converting to CDISC - A Case Study from MacroStat [presentation] |
Weijin Gan |
|
|
| PharmaSUG CN |
2012 |
Clinical Review on iPad with DEFINE.XML |
Sy J. Truong |
|
10 |
| PharmaSUG CN |
2012 |
Taste of SDTM in Real Time [presentation] |
Changhong Shi,
Beilei Xu |
|
|
| PharmaSUG CN |
2012 |
Using HASH Table to reduce the use of merge for large datasets |
Long Fang |
|
7 |
| PharmaSUG |
2012 |
"Analysis-ready" - Considerations, Implementations, and Real World Applications |
Ellen (Zihui) Lin,
Beiying Ding |
source |
6 |
| PharmaSUG |
2012 |
7 Steps to Progression Free Survival Insights Using SAS |
Karen Walker |
source |
12 |
| PharmaSUG |
2012 |
A Complex ADaM dataset? Three different ways to create one. |
Kevin Lee |
source |
11 |
| PharmaSUG |
2012 |
A Standard SAS Program for Corroborating OpenCDISC Error Messages |
John R. Gerlach,
Ganesh Sankaran Thangavel |
source |
12 |
| PharmaSUG |
2012 |
ADaM Implications from the "CDER Data Standards Common Issues" and SDTM Amendment 1 Documents |
Sandra Minjoe |
source |
6 |
| PharmaSUG |
2012 |
An Innovative ADaM Programming Tool for FDA Submission |
Xiangchen (Bob) Cui,
Min Chen,
Tathabbai Pakalapati |
source |
25 |
| PharmaSUG |
2012 |
An Introduction to the Clinical Standards Toolkit and Clinical Data Compliance Checking |
Mike Molter |
source |
14 |
| PharmaSUG |
2012 |
Automate Validation of CDISC ADaM Variable Label Compliance |
Wayne (Weizhen) Zhong |
source |
4 |
| PharmaSUG |
2012 |
Automatic Consistency Checking of Controlled Terminology and Value Level Metadata between ADaM Datasets and Define.xml for FDA Submission |
Xiangchen (Bob) Cui,
Min Chen |
source |
15 |
| PharmaSUG |
2012 |
Automatic Detection and Identification of Variables with All Missing Values in SDTM/ADaM Datasets for FDA Submission |
Min Chen,
Xiangchen (Bob) Cui |
source |
7 |
| PharmaSUG |
2012 |
Automatic Version Control and Track Changes of CDISC ADaM Specifications for FDA Submission |
Xiangchen (Bob) Cui,
Min Chen |
source |
8 |
| PharmaSUG |
2012 |
Avoiding a REL-WRECK; Using RELREC Well |
Karl Miller,
Joseph J. Hantsch,
Janet E. Stuelpner |
source |
6 |
| PharmaSUG |
2012 |
Building Flexible ADaM Analysis Variable Metadata |
Songhui Zhu,
Lin Yan |
source |
10 |
| PharmaSUG |
2012 |
CDISC ADaM Application: Does All One-Record-per-Subject Data Belong in ADSL? |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2012 |
CDISC SDTM Conversion in ISS/ISE Studies: Tools |
Balaji Ayyappan |
source |
6 |
| PharmaSUG |
2012 |
Clinical Laboratory Results, Old and New Pains |
Mario Widel,
Scott A. Bahlavooni |
source |
6 |
| PharmaSUG |
2012 |
Common Misunderstandings about ADaM Implementation |
Nate Freimark,
Susan J. Kenny,
Jack Shostak,
John K. Troxell |
source |
10 |
| PharmaSUG |
2012 |
Considerations in the Submission of Exposure Data in an SDTM-Compliant Format |
Fred Wood,
Jerry Salyers,
Richard Lewis |
source |
4 |
| 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 an Integrated Summary of Safety Database using CDISC ADaM : Challenges, Tips and Things to Watch Out |
Rajkumar Sharma |
source |
7 |
| PharmaSUG |
2012 |
Creating Analysis Data Marts from SDTM Warehouses |
Frank L. Roediger |
source |
9 |
| PharmaSUG |
2012 |
Creating Define.pdf with SAS Version 9.3 ODS RTF |
Elizabeth Li,
Carl Chesbrough |
source |
36 |
| PharmaSUG |
2012 |
Creating the Time to Event ADaM Dataset: The Nuts and Bolts |
Nancy Brucken,
Paul K. Slagle |
source |
7 |
| PharmaSUG |
2012 |
Experiences in Leading a Company-Wide First CDISC Filing from a Programming Perspective |
Sho-Rong Lee |
source |
6 |
| PharmaSUG |
2012 |
Generating SUPPQUAL Domains From SDTM-Plus Domains |
John R. Gerlach,
Glenn O'Brien |
source |
6 |
| PharmaSUG |
2012 |
Getting Your Data in Shape With PROC TRANSPOSE |
Nancy Brucken |
source |
11 |
| 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 |
Identifying and Verifying Treatment-Emergent Adverse Events and Concomitant Medications by Date Specificity |
Tom Santopoli |
source |
5 |
| PharmaSUG |
2012 |
Metadata: Some Fundamental Truths |
Frank C. DiIorio |
source |
10 |
| 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 |
OpenCDISC Plus |
Annie S. Guo |
source |
10 |
| 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 |
SDTM, ADaM and define.xml with OpenCDISC |
Matthew J. Becker |
source |
14 |
| PharmaSUG |
2012 |
Seven New SDTM Domains for Medical Devices |
Carey G. Smoak,
Fred Wood,
Rhonda Facile,
Kit Howard |
source |
4 |
| PharmaSUG |
2012 |
Streamlining Regulatory Submission with CDISC/ADaM Standards for Non-standard Pharmacokinetic/Pharmacodynamic Analysis Datasets |
Xiaopeng Li,
Katrina E. Canonizado,
Chun Feng,
Nancy Wang |
source |
6 |
| PharmaSUG |
2012 |
The application of variable-dependent macro on SDTM conversion |
Mindy Wang |
source |
9 |
| PharmaSUG |
2012 |
Transform Incoming Lab Data into SDTM LB Domain with Confidence |
Anthony L. Feliu |
source |
27 |
| PharmaSUG |
2012 |
Tumor Assessment using RECIST: Behind the Scenes |
Suhas R. Sanjee,
Rajavel Ganesan,
Mary N. Varughese |
source |
7 |
| PharmaSUG |
2012 |
Using the SAS Clinical Standards Toolkit 1.4 for define.xml creation |
Lex Jansen |
source |
30 |
| SGF |
2012 |
A Standard SAS Program for Corroborating OpenCDISC Error Messages |
John R. Gerlach,
Ganesh Sankaran Thangavel |
source |
12 |
| SGF |
2012 |
Automatic Consistency Checking of Controlled Terminology and Value Level Metadata between ADaM Datasets and Define.xml for FDA Submission |
Xiangchen (Bob) Cui,
Min Chen |
source |
15 |
| SGF |
2012 |
Defining the Development Process and Governance of Implementing ADaM within an Organization |
Chris Decker |
source |
11 |
| SGF |
2012 |
Examples of Building Traceability in CDISC ADaM Datasets for FDA Submission |
Xiangchen (Bob) Cui,
Hongyu Liu,
Tathabbai Pakalapati |
source |
14 |
| SGF |
2012 |
One at a Time; Producing Patient Profiles and Narratives |
Joseph J. Hantsch,
Janet E. Stuelpner |
source |
6 |
| SGF |
2012 |
SAS Macros to Transpose SDTM Data Sets Automatically |
Chunmao Wang |
source |
7 |
| SGF |
2012 |
SUPPQUALWhere's My Mommy? |
Sandra VanPelt Nguyen |
source |
8 |
| 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 |
| SGF |
2012 |
Using SAS Macros to Remediate Existing SDTM Data Sets for New Drug Application (NDA) Submission |
Yanwei Han |
source |
4 |
| SESUG |
2011 |
Proc CDISC: Implementation and Assessments |
Sheetal Nisal |
source |
6 |
| SESUG |
2011 |
Resolving OpenCDISC Error Messages Using SAS |
John R. Gerlach |
source |
11 |
| WUSS |
2011 |
Clinical Data Review on iPad with DEFINE.XML |
Sy J. Truong |
source |
10 |
| WUSS |
2011 |
How to easily convert clinical data to CDISC SDTM |
Ale Gicqueau |
source |
9 |
| WUSS |
2011 |
Use CDISC SDTM as a data middle-tier to streamline your SAS infrastructure |
Kalyani Chilukuri |
source |
8 |
| PHUSE EU |
2011 |
"Overnight" Conversion to SDTM Datasets - Ready for SDTM Submission |
Niels Mathiesen |
source
presentation source |
7 |
| PHUSE EU |
2011 |
A SAS macro to check SDTM domains against controlled terminology |
Guido Wendland |
source
presentation source |
10 |
| PHUSE EU |
2011 |
ADaM on a diet: preventing wide and heavy analysis datasets |
Dirk Van Krunckelsven |
source
presentation source |
5 |
| PHUSE EU |
2011 |
ADaM Validation and Integrity Checks |
Louise Cross |
source
presentation source |
5 |
| PHUSE EU |
2011 |
Creating ADaM Friendly Analysis Data from SDTM Using Meta Data |
Erik Brun,
Rico Schiller |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Defining the Governance and Process of Implementing ADaM across an Organization |
Chris Decker |
source
presentation source |
11 |
| PHUSE EU |
2011 |
Ensuring Compliant and Consistent Data Mappings for SDTM-based Studies - an ICON Approach |
Jennie McGuirk,
Steven Thacker |
source
presentation source |
16 |
| PHUSE EU |
2011 |
Extension of the Six Steps Approach: How to go from an SDTM finding domain to an ADaM-compliant AD |
Carl Herremans,
Qian Wang |
source
poster source |
5 |
| PHUSE EU |
2011 |
FDA CDER Common Data Standards Issues: Evolution of SDTM Submission Standards |
Peter Van Reusel,
Tina Apers |
source
presentation source |
3 |
| PHUSE EU |
2011 |
Implementation of a CDISC standards supported by global mapping process and metadata library |
Dimitri Kutsenko |
source
presentation source |
5 |
| PHUSE EU |
2011 |
Implementing ADaM Using the SAS Clinical Standards Toolkit |
Gene Lightfoot |
source
presentation source |
12 |
| PHUSE EU |
2011 |
Much ADaM about Nothing - a PROC Away in a Day |
Endri Endri,
Rowland Hale |
source
presentation source |
8 |
| PHUSE EU |
2011 |
Programming for Early and Late Phase - really that different? |
Katherine Macey |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Rebuilding define.pdf by reading Word and XFDF files |
David J. Garbutt |
source
poster source |
23 |
| PHUSE EU |
2011 |
Remapping of Codes (and of course Decodes) in Analysis Data Sets for Electronic Submissions |
Joerg Guettner |
source
presentation source |
5 |
| 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 |
SDTM Implementation Guide - Clear as Mud: Strategies for Developing Consistent Company Standards |
Brian Mabe |
source
presentation source |
5 |
| 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 |
Three Unique Case Studies - On the Trail of the Holy Grail of SDTM Implementation |
Kenneth Stoltzfus |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Use of ODS tagsets.excelxp to create Excel type files |
Douglas Staddon |
source
presentation source |
9 |
| 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 |
How to Use SDTM Definition and ADaM Specifications Documents to Facilitate SAS Programming |
Yan Liu |
|
5 |
| MWSUG |
2011 |
Is It Time to Upgrade CDISC SDTM from v1.1/v3.1.1 to v1.2/v3.1.2? |
Susan M. Fehrer |
|
3 |
| MWSUG |
2011 |
Tracking Metadata within SAS Drug Development Using SDDPARMS |
Bradford J. Danner,
Matthew J. Wiedel,
Katrina E. Canonizado |
|
7 |
| NESUG |
2011 |
A Validation Macro to Check Compliance of CDISC SDTM Data |
Hany Aboutaleb |
|
13 |
| NESUG |
2011 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| NESUG |
2011 |
Generating Define.xml |
Sandeep Kottam,
Uma Sarath Annapareddy,
Sree Lakshmi Kalyani Tripuraneni |
|
20 |
| NESUG |
2011 |
Metadata: Some Fundamental Truths |
Frank C. DiIorio |
|
9 |
| NESUG |
2011 |
Validating CDISC Compliant Data and Creating Define.xml Made Easy |
Sandeep Purwar |
|
5 |
| PharmaSUG |
2011 |
A Cost-Effective SDTM Conversion for NDA Electronic Submission |
Xiangchen (Bob) Cui,
Scott E. Moseley,
Min Chen |
source |
12 |
| PharmaSUG |
2011 |
A Regular Language: The Annotated Case Report Form |
Ryan Wilkins,
Joel Campbell |
source |
9 |
| PharmaSUG |
2011 |
A Special SDTM Domain RELREC and its Application |
Changhong Shi,
Beilei Xu |
source |
8 |
| PharmaSUG |
2011 |
ADaM Standard Naming Conventions are Good to Have |
Christine S Teng |
source |
8 |
| PharmaSUG |
2011 |
An Excel Framework to Convert Clinical Data to CDISC SDTM Leveraging SAS Technology |
Sophie McCallum,
Stephen Chan |
source |
12 |
| PharmaSUG |
2011 |
Automating the Process of Preparing Data Definition Document for NDA Electronic Submission from Programming Specification in Word Format |
Min Chen,
Xiangchen (Bob) Cui,
Scott E. Moseley |
source |
12 |
| PharmaSUG |
2011 |
Basic Understanding on SE Domain for Beginners |
Gayatri Karkera |
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 |
CDISC Variable Mapping and Control Terminology Implementation Made Easy |
Balaji Ayyappan,
Manohar Sure |
source |
5 |
| PharmaSUG |
2011 |
Challenges in Implementing ADaM datasets: Balancing the Analysis-Ready and Traceability Concepts |
Pushpa Saranadasa |
source |
7 |
| 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 |
Creating a define.xml file for ADaM and SDTM |
John H. Adams |
source |
18 |
| PharmaSUG |
2011 |
Creating SDTM Datasets from Legacy Data |
Fred Wood |
source |
6 |
| PharmaSUG |
2011 |
Efficiencies Realized in Building and Utilizing ADaM from SDTM |
Shirish Nalavade,
Parag Shiralkar |
source |
5 |
| PharmaSUG |
2011 |
Ensuring Consistent Data Mapping Across SDTM-based Studies - a Data Warehouse Approach |
Annie S. Guo |
source |
12 |
| PharmaSUG |
2011 |
Evolution of SDTMIG 3.1.1 to 3.1.2: A mapping specialist must reference on these changes |
Rachit Desai,
Anirudh Gautam,
Vikash Jain |
source |
8 |
| PharmaSUG |
2011 |
Find / Track / Check and Close, Using SAS to Streamline SDTM Validation Including the Hyperlinks |
David Tillery,
Qiang Zhai,
Lily Peng |
source |
5 |
| PharmaSUG |
2011 |
From SAP to BDS: The Nuts and Bolts |
Nancy Brucken,
Paul K. Slagle |
source |
9 |
| PharmaSUG |
2011 |
Good Versus Better SDTM - Date and Time Variables |
Mario Widel,
Henry B. Winsor |
source |
3 |
| PharmaSUG |
2011 |
Importing and Parsing Comments From a PDF Document With Help From Perl Regular Expressions |
Joel Campbell,
Ryan Wilkins |
source |
5 |
| PharmaSUG |
2011 |
Keeping Patients on Schedule, The Art of Visit Windows and Cycle Slotting |
Paul K. Slagle |
source |
4 |
| PharmaSUG |
2011 |
Making a List, Checking it Twice (Part 1): Techniques for Specifying and Validating Analysis Datasets |
Elizabeth Li,
Linda Collins |
source |
8 |
| PharmaSUG |
2011 |
Method to Derive Reproducible SDTM Relationship Datasets |
Suwen Li,
Sai Ma,
Regan Li,
Bob Lan |
source |
9 |
| PharmaSUG |
2011 |
Methods of Building Traceability for ADaM Data |
Songhui Zhu,
Lin Yan |
source |
9 |
| 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 |
Producing Clinical Laboratory Shift Tables From ADaM Data |
Rao Bingi |
source |
12 |
| PharmaSUG |
2011 |
Resolving OpenCDISC Error Messages Using SAS |
Virginia Redner,
John R. Gerlach |
source |
10 |
| PharmaSUG |
2011 |
SDTM, ADaM and define.xml with OpenCDISC |
Matthew J. Becker,
Angela S. Ringelberg |
source |
13 |
| PharmaSUG |
2011 |
The Standard for the Exchange of Nonclinical Data (SEND): History and Basics |
Fred Wood,
Lou Ann Kramer |
source |
9 |
| PharmaSUG |
2011 |
Tracking Metadata within SAS Drug Development Using SDDPARMS |
Bradford J. Danner,
Matthew J. Wiedel,
Katrina E. Canonizado |
source |
7 |
| PharmaSUG |
2011 |
Trials and Tribulations of SDTM Trial Design |
Fred Wood,
Mary Lenzen |
source |
5 |
| PharmaSUG |
2011 |
Truncation, Variable Association, Controlled Terminology, and Some Other Pitfalls in the SDTM Mapping Process |
Na Li,
Gary de Jesus,
Daniel Bonzo |
source |
8 |
| PharmaSUG |
2011 |
Using the ADaM Basic Data Structure for Survival Analysis |
Nancy Brucken,
Sandra Minjoe,
Mario Widel |
source |
5 |
| PharmaSUG |
2011 |
Using the SAS Clinical Standards Toolkit for define.xml creation |
Lex Jansen |
source |
20 |
| PharmaSUG |
2011 |
Validating Controlled Terminology in SDTM Domains |
John R. Gerlach |
source |
12 |
| PharmaSUG |
2011 |
Validating define.xml: Tools, trials, and tribulations |
Sandra VanPelt Nguyen |
source |
5 |
| 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 |
Easy Ways to get SAS Enterprise Guide to Send Tables and Graphs to Microsoft Office Suite, Without Writing Code! |
William E. Benjamin Jr. |
source |
14 |
| SGF |
2011 |
How to Build ADaM Basic Data Structure from Mock Up Table |
Kevin Lee |
source |
4 |
| SGF |
2011 |
State of the Union: The Crossroads of CDISC Standards and SAS Supporting Role |
Michael J. Molter,
Chris Decker |
source |
14 |
| SGF |
2011 |
Using SAS to Incorporate the SDTM for a Study Funded by the NIH |
Fenghsiu Su,
Bradford Jackson,
Kaming Lo,
Sumihiro Suzuki,
Karan Singh,
David Coultas |
source |
8 |
| SGF |
2011 |
What CDISC Means to SAS Programmers |
Kevin Lee |
source |
3 |
| NESUG |
2010 |
Applying Metadata Attributes in Analysis Data Sets Using Macro Variables and Proc SQL in SAS |
Rita Tsang |
|
7 |
| NESUG |
2010 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| NESUG |
2010 |
Date Conversions in SDTM and ADaM Datasets |
Lily Zhang,
Lili Chen,
Huei-Ling Chen |
|
8 |
| NESUG |
2010 |
Outsourced Data Integration Project with CDISC SDTM and ADaM Deliverables |
Margaret M. Coughlin,
Christine S Teng |
|
11 |
| NESUG |
2010 |
SAS and open source tools for CDISC SDTM compliance checks for regulatory submissions |
Sandeep Kottam,
Peter Loonan,
Sree Lakshmi Kalyani Tripuraneni |
|
4 |
| NESUG |
2010 |
The 5 Biggest Challenges of ADaM |
Terek J. Peterson,
David C. Izard |
|
11 |
| NESUG |
2010 |
The Nitty-Gritty of FDA Electronic Submission: A Programmer's Perspective |
Sandeep N. Beniwal |
|
9 |
| SCSUG |
2010 |
Easy Ways to get SAS Enterprise Guide to Send Tables and Graphs to Microsoft Office Suite, Without Writing Code! |
William E. Benjamin Jr. |
source |
19 |
| WUSS |
2010 |
An Excel Framework to Convert Clinical Data to CDISC SDTM Leveraging SAS Technology |
Ale Gicqueau |
source |
12 |
| WUSS |
2010 |
Automation of 'makefile' for Use in Clinical Development |
Nalin Tikoo |
source |
7 |
| WUSS |
2010 |
Creating a Patient Profile using CDISC SDTM |
Marc Desgrousilliers |
source |
5 |
| PHUSE EU |
2010 |
Accessing the metadata from the define.xml using XSLT transformations |
Lex Jansen |
source
presentation source |
24 |
| PHUSE EU |
2010 |
An Animated Guide: the logical cascade throught the - Orres variable [poster] |
Russell M. Lavery |
source |
13 |
| PHUSE EU |
2010 |
BeST - Bioequivalence Study Template |
Pekka Heikkilä |
source
presentation source |
9 |
| 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 |
Challenges of Clinical projects shared between Pharma Companies [presentation] |
Oliver LeConte |
source |
27 |
| PHUSE EU |
2010 |
Clinetics Data Merge - A Platform for Exchange of Pharmacokinetic Data |
Ralf Schefer-Pregi,
Andreas Schwarzer |
source
presentation source |
5 |
| 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 |
Define.xml - Tips and Techniques for Creating CRT-DDS |
Julie A. Maddox,
Mark Lambrecht |
source
presentation source |
10 |
| PHUSE EU |
2010 |
Defining "Compliance" for Analysis Data |
Chris Decker,
Randall Austin |
source
presentation source |
7 |
| PHUSE EU |
2010 |
Facilitating Data Integration for Regulatory Submissions |
John R. Gerlach,
John Bowen |
source
presentation source |
8 |
| PHUSE EU |
2010 |
From ACE to ZINC |
Paul Vervuren |
source |
8 |
| PHUSE EU |
2010 |
Generate ATTRIB and FORMAT statements from the SAP |
Shafi Chowdhury |
source
presentation source |
7 |
| PHUSE EU |
2010 |
How Do I Map That? - SDTM Implementation Challenges |
Chris Price |
source
presentation source |
11 |
| PHUSE EU |
2010 |
How to clean up dirty data in Patient reported outcomes? |
Knut Mueller |
source
presentation source |
6 |
| PHUSE EU |
2010 |
How to go From an SDTM Findings Domain to an ADaM-Compliant Analysis Dataset: An Example |
Carl Herremans |
source
presentation source |
8 |
| PHUSE EU |
2010 |
How to improve quality control in a data conversion process? By extended usage of metadata! |
Dimitri Kutsenko |
source
presentation source |
4 |
| PHUSE EU |
2010 |
Implementing, Managing and Validating a Clinical Standard |
Gene Lightfoot |
source
presentation source |
12 |
| PHUSE EU |
2010 |
Initial Investment in CDISC Data Standards in Clinical Organisations |
Kenneth Stolzfus |
source |
10 |
| PHUSE EU |
2010 |
Introduction to SAS Clinical Standards Toolkit |
Andreas Mangold,
Nicole Waechter |
source
presentation source |
16 |
| 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 |
The Ultimate Integration Challenge |
Jennifer Choon-Moi Chin,
Hester Schoeman |
source
presentation source |
11 |
| 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 |
Using web service technologies for incremental, real-time transfers |
Andrew Newbigging |
source |
11 |
| SESUG |
2010 |
A Taste of ADaM |
Beilei Xu |
source |
9 |
| SESUG |
2010 |
Tips and Tricks Of Efficient SAS Programming for SDTM Data |
Eric Qi,
Fikret Karahoda |
source |
6 |
| 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 |
|
24 |
| PharmaSUG |
2010 |
Achieving Efficiency in CDISC-SDTM Conversion and its Challenges - Case Study |
Ilango Ramanujam |
|
6 |
| PharmaSUG |
2010 |
ADaM Dataset Checking Toolkit |
Huei-Ling Chen |
|
9 |
| PharmaSUG |
2010 |
Applying ADaM Principles in Developing a Response Analysis Dataset |
Mei Dey,
Lisa Pyle |
|
8 |
| PharmaSUG |
2010 |
Automating the Link Between Metadata and Analysis Datasets |
Misha Rittmann |
|
5 |
| PharmaSUG |
2010 |
Automating the Process of Creating the Contents of Data Definition Document |
David L. Wang |
|
10 |
| PharmaSUG |
2010 |
Checking for SDTM Compliance: The Need for Human Involvement |
Fred Wood,
Adrienne Boyance |
|
8 |
| PharmaSUG |
2010 |
Editing SAS Metadata - Automated From CSV Files Using XML String in SAS Data Integration Studio |
Annie S. Guo |
|
11 |
| PharmaSUG |
2010 |
Evolving role of statistical SAS programmers in the pharmaceutical industry |
Venkata Sekhar Bhamidipati,
Haiping Zhou |
|
5 |
| PharmaSUG |
2010 |
Exploring SAS PROC CDISC Model=ODM and Its Limitations |
Elena Valkanova,
Irene Droll |
|
9 |
| PharmaSUG |
2010 |
Facilitating Data Integration for Regulatory Submissions |
John R. Gerlach |
|
9 |
| PharmaSUG |
2010 |
From SAP to ADaM: The Nuts and Bolts |
Nancy Brucken,
Paul K. Slagle |
|
9 |
| 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 |
How to validate SDTM SUPPQUAL Data Set |
Kevin Lee |
|
4 |
| PharmaSUG |
2010 |
In-Depth Review of Validation Tools to Check Compliance of CDISC SDTM-Ready Clinical Datasets |
Bhavin Busa,
Kimberly Lindfield |
|
52 |
| PharmaSUG |
2010 |
In-Depth Review of Validation Tools to Check Compliance of CDISC SDTM-Ready Clinical Datasets |
Bhavin Busa,
Kimberly Lindfield |
|
8 |
| PharmaSUG |
2010 |
Insights into ADaM |
Matthew J. Becker |
|
9 |
| PharmaSUG |
2010 |
Medical Device and Diagnostic Industry 101 |
Carey G. Smoak |
|
5 |
| PharmaSUG |
2010 |
Multidimensional Data Visualization for Generating Patient Profile |
Rajavel Ganesan,
Suhas R. Sanjee,
Jason Clark |
|
4 |
| 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 |
SAS Programming Techniques for Manipulating Metadata on the Database Level |
Chris Speck |
|
7 |
| PharmaSUG |
2010 |
SDTM Attribute Checking Tool |
Ellen Xiao |
|
6 |
| PharmaSUG |
2010 |
Thanks CDISC - Free Utilities |
Robert Agostinelli |
|
5 |
| 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 SE Domain as Treatment Data Store: Using the SDTM Subject Elements (SE) domain to drive analyzing treatment |
Jeremy Gratt |
|
10 |
| PharmaSUG |
2010 |
Updating SDTM Metadata Excel File (Define.xls) with SAS |
Lin Yan |
|
6 |
| SGF |
2010 |
Automating SDTM File Creation: Speeding Up the Process with Metadata Files |
Daphne E. Ewing |
source |
7 |
| SGF |
2010 |
SDTM Attribute Checking Tool |
Ellen Xiao |
source |
6 |
| SGF |
2010 |
Understanding the define.xml File and Converting It to a Relational Database |
Lex Jansen |
source |
20 |
| SGF |
2010 |
Using PROC CONTENTS Output to Perform Quality Control Checks on SDTM Data Sets |
Jennifer M. Srivastava |
source |
6 |
| SESUG |
2009 |
A SAS Macro to Automate the Process of Define.xml |
Wenyu Hu,
Liping Zhang |
source |
5 |
| SESUG |
2009 |
Exploring SAS PROC CDISC Model=ODM and its Undocumented Parameters |
Elena Valkanova |
source |
7 |
| SESUG |
2009 |
Mapping Nested e-CRF Data into SDTM Domains |
Venkata Sekhar Bhamidipati,
Kristi L. Garner |
source |
5 |
| PHUSE EU |
2009 |
A Framework for Acheiving an Industry-Driven, Open-Source Clinical Reporting System |
Dante Di Tommaso,
Ann Marie Martin |
source |
5 |
| PHUSE EU |
2009 |
Acceleration through Collaboration |
Carrie Eason |
source
presentation source |
7 |
| PHUSE EU |
2009 |
After a new CDISC SDTM version, how to update and manage ADS/SDS DEFINE files at company team level |
Nathalie Moro |
source |
5 |
| PHUSE EU |
2009 |
An Animated Guide: The Logical Cascade through the --ORRES Variable |
Russell M. Lavery |
source |
12 |
| PHUSE EU |
2009 |
An Evaluation of the ADaM Implementation Guide v1.0 and the Analysis Data Mode v2.1 |
Chris Price |
source
presentation source |
4 |
| PHUSE EU |
2009 |
Converting the define.xml to a Relational Database to Enable Printing and Validation |
Lex Jansen |
source
presentation source |
19 |
| PHUSE EU |
2009 |
ETL and the Clinical Programmer - They don't have to be Enemies! |
Chris Decker,
Christopher R. Olinger |
source |
11 |
| PHUSE EU |
2009 |
Experiences and lessons learned from a first SDTM submission project |
Paul Vervuren,
Bas van Bakel |
source
presentation source |
12 |
| PHUSE EU |
2009 |
From raw data to submission: A metadata-driven, repository-based process of data conversion to CDISC |
Dimitri Kutsenko |
source
presentation source |
7 |
| PHUSE EU |
2009 |
Generate Define.xml & Define.pdf from Metadata Environment |
Rohit Banga |
source
presentation source |
11 |
| PHUSE EU |
2009 |
Implementation of ADaM standards NOT driven by a submission |
Karin Fleischer |
source
presentation source |
7 |
| PHUSE EU |
2009 |
Implementation of CDISC Standards at Nycomed [presentation] |
Berthold Traub |
source |
31 |
| PHUSE EU |
2009 |
Insights into ADaM |
Matthew J. Becker |
source
presentation source |
9 |
| PHUSE EU |
2009 |
Kendle Implementation of CDASH [presentation] |
Elke Sennewald,
Gill Lawrence |
source |
32 |
| PHUSE EU |
2009 |
Metadata and Standard Programs |
Marianne Carames,
Martin Lindhard |
source
presentation source |
10 |
| PHUSE EU |
2009 |
SDTM Validation: How can we do it right? |
Peter Van Reusel |
source
presentation source |
8 |
| 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 |
Using SAS Clinical Data Integration Server to Implement and Manage CDISC Standards |
Julie A. Maddox |
source
presentation source |
8 |
| PHUSE EU |
2009 |
Using SAS Macros to simplify preparation and validation of SDTM data, Annotated CRFs and Define.xml in a metadata driven environment |
Niels Both |
source
presentation source |
10 |
| NESUG |
2009 |
A Complete Derivation of Duration and Display in ISO 8601 Using SAS Program |
Joyce Gui,
Helen Wang,
Sandy Wang |
|
8 |
| NESUG |
2009 |
A Practical Introduction to implementing the Clinical Data Acquisition Standards Harmonization (CDASH) standards |
Jennifer Price |
|
7 |
| NESUG |
2009 |
A Proposed SDTM Implementation of Response Data for Solid Tumor Trials in Oncology |
Mei Dey,
Elisabeth Pyle |
|
18 |
| NESUG |
2009 |
A Taste of SDTM in Real Time |
Changhong Shi,
Beilei Xu |
|
6 |
| NESUG |
2009 |
QC the Qualitative Part of Clinical Data in SAS Datasets |
Tse-Hua J. Shih,
Xitao Fan,
Cliff Meng,
Eugenia Henry |
|
5 |
| 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 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Peter Villiers |
|
13 |
| WUSS |
2009 |
BRIDGing CDASH to SAS: How Harmonizing Clinical Trial and Healthcare Standards May Impact SAS Users |
Clinton Brownley |
source |
6 |
| WUSS |
2009 |
CDISC for the Medical Device and Diagnostic Industry: An Update |
Carey G. Smoak |
source |
3 |
| WUSS |
2009 |
CDISC Implementation on a Rheumatoid Arthritis Project Partnership |
Patricia L. Gerend,
Oliver LeConte,
Michelle Zhang,
Chris Price |
source |
9 |
| 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 |
The CDISC Study Data Tabulation Model (SDTM): History, Perspective, and Basics |
Fred Wood |
source |
9 |
| WUSS |
2009 |
The Second CDISC Pilot Project: A Metastandard for Integrating Databases |
Gregory C. Steffens,
Ian Fleming |
source |
5 |
| PharmaSUG |
2009 |
A Framework For Achieving An Industry-Driven, Open-Source Clinical Reporting System |
Dante Di Tommaso,
Ann Marie Martin,
Paul OldenKamp,
Paul D. Hamilton |
|
6 |
| PharmaSUG |
2009 |
A Practical Introduction to Clinical Data Acquisition Standards Harmonization (CDASH) |
Jennifer Price |
|
5 |
| PharmaSUG |
2009 |
ARROW Clinical Data Analysis System: An Integration of Statistical Analysis and Reporting |
Cheng Jun Tian,
Denis Michel |
|
9 |
| PharmaSUG |
2009 |
Clinically Significant Data Integration Studio |
Chris Decker,
Stephen Baker |
|
12 |
| PharmaSUG |
2009 |
Converting CDISC Controlled Terminology to SAS Formats |
Sandeep Juneja,
Vivek Mohan |
|
5 |
| PharmaSUG |
2009 |
Converting the define.xml to a Relational Database to Enable Printing and Validation [presentation] |
Lex Jansen |
|
76 |
| PharmaSUG |
2009 |
Converting the define.xml to a Relational Database to Enable Printing and Validation |
Lex Jansen |
|
18 |
| PharmaSUG |
2009 |
Creating the Case Report Tabulation (CRT) for an NDA submission at the absolute last moment - NOT |
Christine Connolly,
Kevin King,
Amanda Tweed,
Steven Wong |
|
9 |
| 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 |
Data Conversion to SDTM: What Sponsors Can Do to Facilitate the Process |
Fred Wood |
|
6 |
| PharmaSUG |
2009 |
Implementation Plan for CDISC SDTM & ADaM Standards at MedImmune |
Alan Meier |
|
11 |
| PharmaSUG |
2009 |
Implementing CDISC When You Already Have Standards |
Sandra Minjoe |
|
10 |
| PharmaSUG |
2009 |
Nice SUPPQUAL Variables to Have |
Beilei Xu,
Changhong Shi |
|
5 |
| PharmaSUG |
2009 |
RS01 The Second CDISC Pilot Project A Metastandard for Integrating Databases |
Gregory C. Steffens |
|
4 |
| PharmaSUG |
2009 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Supporting CDISC Standards |
|
13 |
| 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 |
| SGF |
2009 |
A SAS Programmer's Guide to Generating Define.xml |
Michael J. Molter |
source |
24 |
| 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 |
Implementing CDISC When You Already Have Standards: A Case Study |
Sandra Minjoe |
source |
10 |
| SGF |
2009 |
Mapping CDISC Metadata Attributes: Using DATA _NULL_ and PROC DATASETS in SAS |
Rita Tsang |
source |
8 |
| SGF |
2009 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Peter Villiers |
source |
13 |
| SGF |
2009 |
The Second CDISC Pilot Project: Standards for Integrating Databases |
Ian Fleming,
Gregory C. Steffens |
source |
4 |
| SGF |
2009 |
Using SAS Clinical Data Integration Server to Implement and Manage CDISC Standards |
Michael Kilhullen |
source |
7 |
| WUSS |
2008 |
Easy Ways to get SAS Enterprise Guide to Send Tables and Graphs to Microsoft Office Suite, Without Writing Code! |
William E. Benjamin Jr. |
source |
19 |
| SESUG |
2008 |
An Approach for Deriving a Timing Variable in SDTM Standards |
Shaoan Yu,
Joyce Gui |
source |
9 |
| SESUG |
2008 |
How to Create Variables Related to Age |
Joyce Gui,
Shaoan Yu |
source |
5 |
| PHUSE EU |
2008 |
An Animated Guide: The Logical Cascade through the --ORRES Variable |
Russell M. Lavery |
source |
13 |
| PHUSE EU |
2008 |
CDISC Implementation Strategies: Exploit your data assets while still giving the FDA what they want |
David Smith |
source |
9 |
| PHUSE EU |
2008 |
CDISC: Implementation Strategies for SDTM |
Brian Mabe |
source |
5 |
| PHUSE EU |
2008 |
Data Standardisation, Clinical Data Warehouse and SAS Standard Programs |
Jean-Marc Ferran,
Mikkel Traun |
source |
8 |
| PHUSE EU |
2008 |
Implementing CDISC at Boehringer Ingelheim |
Michael Knoessl,
Peter Leister |
source |
5 |
| PHUSE EU |
2008 |
In at the Deep-End (thoughts on mapping multiple studies into CDISC for an ISS/ISE) |
Andrew Noller |
source |
7 |
| PHUSE EU |
2008 |
Let SAS HELP Help You |
Catriona O'Hare |
source |
8 |
| PHUSE EU |
2008 |
Practical application of SAS Clinical Data Integration Server for conversion to SDTM data |
Mark Lambrecht,
Peter Van Reusel |
source |
9 |
| PHUSE EU |
2008 |
The application of SDTM in a disease (oncology)-oriented organization |
Angelo Tinazzi,
Enrica Paschetto |
source |
8 |
| PHUSE EU |
2008 |
Using SAS 9 in Clinical Research |
Gregory S. Barnes Nelson |
source |
11 |
| PHUSE EU |
2008 |
Using the SAS XML Mapper and ODS to create a PDF representation of the define.xml |
Lex Jansen |
source |
21 |
| NESUG |
2008 |
An Animated Guide: the Logical cascade when entering Orres data |
Russell M. Lavery |
|
11 |
| NESUG |
2008 |
An Approach to CDISC SDTM Implementation for Clinical Trials Data |
William Chen,
Margaret M. Coughlin |
|
5 |
| NESUG |
2008 |
Motivating Clinical SAS Programmers |
Daniel J. Boisvert,
Andy Illidge |
|
8 |
| NESUG |
2008 |
Using the SAS XML Mapper and ODS PDF to create a PDF representation of the define.xml (that can be printed) |
Lex Jansen |
presentation |
20 |
| PharmaSUG |
2008 |
A SAS based solution for define.xml |
Monika Kawohl |
|
18 |
| PharmaSUG |
2008 |
A Toolkit for CDISC Implementation |
Robert T. Stemplinger |
|
6 |
| PharmaSUG |
2008 |
Automated SAS Macro for Adverse Event Logistic Regression Analysis |
Suhas R. Sanjee |
|
8 |
| PharmaSUG |
2008 |
Case Study: Analysis and Metrics of End-to-End Legacy Data Conversions into SDTM, ADaM, and Define.xml |
Robert T. Stemplinger |
|
5 |
| PharmaSUG |
2008 |
Cost-Effective Solution to Automating the Creation of CDISC define.xml: Using SAS Data _Null_ with Relational Data Model via SAS/AF Application |
Annie S. Guo |
|
12 |
| PharmaSUG |
2008 |
Experiences Submitting CDISC SDTM and Janus Compliant Datasets |
Carol Vaughn,
Gregory Ridge,
William Friggle |
|
10 |
| PharmaSUG |
2008 |
Generating a List of Macro Variables for Lab Data through a Simple Macro Call |
Huijuan Xu |
|
3 |
| PharmaSUG |
2008 |
Managing The Change And Growth Of A Metadata-Based System |
Jeffrey M. Abolafia,
Frank C. DiIorio |
|
11 |
| PharmaSUG |
2008 |
Mission Possible: A Proposed SDTM Domain for the Medical Device and Diagnostic Industry |
Carey G. Smoak |
|
2 |
| PharmaSUG |
2008 |
SAS, CDISC and Clinical Data Integration |
Peter Villiers |
|
27 |
| PharmaSUG |
2008 |
SDTM, Plus or Minus |
Barry R. Cohen |
|
6 |
| PharmaSUG |
2008 |
The CDISC Study Data Tabulation Model (SDTM): History, Perspective, and Basics |
Fred Wood |
|
8 |
| PharmaSUG |
2008 |
Using the SAS XML Mapper and ODS PDF to create a PDF representation of the define.xml (that can be printed) |
Lex Jansen |
|
20 |
| PharmaSUG |
2008 |
Validating CDISC SDTM-Compliant Submission-Ready Clinical Datasets with an In-House SAS Macro-Based Solution |
Bhavin Busa,
Sheila Vince,
Jameelah Aziz |
|
12 |
| SGF |
2008 |
CDISC: Pains and Pitfalls of Data Set Creation |
Steven L. Michaelson,
Janet E. Stuelpner |
source |
5 |
| SGF |
2008 |
Managing The Change And Growth Of A Metadata-Based System |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
11 |
| SGF |
2008 |
Practical Methods for Creating CDISC SDTM Data Sets from Existing Data |
Robert W. Graebner |
source |
11 |
| SGF |
2008 |
Standard Management-Approved Report Templates: The SMART System |
Gary S. Stevens |
source |
7 |
| SGF |
2008 |
The Evolution of SAS in Life Sciences Research and Development |
David Handelsman |
source |
10 |
| SGF |
2008 |
Using Excel XP to Display SDTM Metadata and More |
Christine S Teng,
Shaoan Yu |
source |
8 |
| NESUG |
2007 |
Benefits of Using Excel File in CDISC SDTM Data Mapping |
Hong Wang |
|
8 |
| NESUG |
2007 |
Relationships Between CDISC Variables Concerning Day and Date (CDISC Variable Relationships Part 2 of 3) |
Susan Fehrer,
Russell M. Lavery |
|
10 |
| NESUG |
2007 |
Relationships Between CDISC Variables Linking Domains (relrec) (CDISC Variable Relationships Part 3 of 3) |
Susan Fehrer,
Russell M. Lavery |
|
12 |
| NESUG |
2007 |
Relationships Between ORRES and Other CDISC Variables (CDISC Variable Relationships Part 1 of 3) |
Susan Fehrer,
Russell M. Lavery |
|
9 |
| PHUSE EU |
2007 |
A SAS based solution for define.xml |
Monika Kawohl |
source |
18 |
| PHUSE EU |
2007 |
A systematic review of PHUSE |
Angelo Tinazzi,
Anna Compagnoni |
source |
5 |
| PHUSE EU |
2007 |
All roads lead to SDTM - which one shall we take? |
Ian Fisher,
Donna Thompson |
source |
9 |
| PHUSE EU |
2007 |
Considerations for CDISC Implementation |
Robert T. Stemplinger,
Jackie Lane |
source |
4 |
| PHUSE EU |
2007 |
DQC checker |
Ryan Finch |
source |
7 |
| PHUSE EU |
2007 |
Electronic submissions - the role of the programmer |
Simon Dundas |
source |
8 |
| PHUSE EU |
2007 |
MAKS: A validated SAS Macro Library for data in SDTM structure |
Rolf Meinert,
Katrin Bhalla-Muller |
source |
3 |
| PHUSE EU |
2007 |
Relationships between CDISC variables concerning day and date |
Susan Fehrer,
Russell M. Lavery |
source |
10 |
| PHUSE EU |
2007 |
Relationships between CDISC variables linking domains (relrec) |
Susan Fehrer,
Russell M. Lavery |
source |
12 |
| PHUSE EU |
2007 |
Relationships between ORRES and other CDISC variables |
Susan Fehrer,
Russell M. Lavery |
source |
9 |
| PHUSE EU |
2007 |
Runtime funtime: Vertical data reporting using runtime formats |
Michael Auld |
source |
11 |
| PHUSE EU |
2007 |
Standard Management Approved Report Templates |
Gary S. Stevens |
source |
7 |
| PHUSE EU |
2007 |
Standardization of submission data sets and analysis data sets |
Yvane Boudraa |
source |
4 |
| PharmaSUG |
2007 |
A Harmonized, Report-Friendly SDTM and ADaM Data Flow |
Aileen L. Yam |
|
4 |
| PharmaSUG |
2007 |
A Scalable Platform For Clinical Trials - Interoperability And Automation In A Web-Based Environment |
John R. Gerlach,
Maulik Shah |
|
11 |
| PharmaSUG |
2007 |
Best Practices for Working with CDISC Metadata in the SAS Data Integration Server |
Michael Kilhullen |
|
10 |
| PharmaSUG |
2007 |
CDISC for the Medical Device and Diagnostic Industry |
Carey G. Smoak |
|
4 |
| PharmaSUG |
2007 |
CDISC Implementation Step by Step: A Real World Example |
Sy J. Truong |
|
19 |
| PharmaSUG |
2007 |
CDISC: Pains and Pitfalls to Dataset Creation |
Janet E. Stuelpner,
Steven L. Michaelson |
|
5 |
| PharmaSUG |
2007 |
Considerations for CDISC Implementation |
Robert T. Stemplinger |
|
4 |
| PharmaSUG |
2007 |
Customizing SAS Data Integration Studio to Generate CDISC Compliant SDTM 3.1 Domains |
Tatyana Kovtun,
John Markle,
Christopher Treglio |
|
12 |
| PharmaSUG |
2007 |
Developing Reporting & Analysis Methodologies |
Amy Gillespie,
Mary N. Varughese |
|
5 |
| 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 |
From CRF Data to DEFINE.XML: Going "End to End" with Metadata |
Frank C. DiIorio,
Jeffrey M. Abolafia |
|
20 |
| PharmaSUG |
2007 |
Implementing CDISC Data Models in the SAS Metadata Server |
Michael Kilhullen |
|
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 Contents In Excel Using SAS - XML |
Sandeep Juneja |
|
5 |
| PharmaSUG |
2007 |
Relationships Among CDISC Variables (Part I) |
Susan Fehrer,
Russell M. Lavery |
|
9 |
| PharmaSUG |
2007 |
SDTM, Plus or Minus |
Barry R. Cohen |
|
6 |
| 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 SAS to Send Bulk Emails With Attachments |
Wenjie Wang,
Simon Lin |
|
13 |
| SGF |
2007 |
Extending SAS Data Integration Studio with Java: Custom GUIs and SAS Server Interactions |
Christopher Treglio |
source |
15 |
| SGF |
2007 |
The Electronic Project: Effectively Using Metadata throughout the Project Life Cycle |
Jeffrey M. DiIorio,
Frank Abolafia |
source |
18 |
| PHUSE EU |
2006 |
Contours of a Drug Development Data Warehouse |
Paul Vervuren |
source |
8 |
| PHUSE EU |
2006 |
The Submission Data File System Automating the Creation of CDISC SDTM and ADaM Datasets |
David Edwards,
Marcus Bloom |
source |
6 |
| 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 |
| SESUG |
2006 |
A Relational Understanding of SDTM Tables |
John R. Gerlach |
source |
10 |
| 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 |
| WUSS |
2006 |
New CDISC Training Initiative |
Dana Rafiee |
source |
2 |
| WUSS |
2006 |
Step by Step PROC CDISC and More |
Sy J. Truong |
source |
19 |
| NESUG |
2006 |
ISO 8601 - An International Standard for Date and Time Formats |
Shi-Tao Yeh |
|
5 |
| NESUG |
2006 |
It's About Time! A Primer on Time-Slotting of Data Using SAS |
Maria Y. Reiss |
|
13 |
| NESUG |
2006 |
Standard SAS Macros for Standard Date/Time Processing |
Qin Lin,
Timothy D. Kelly |
|
18 |
| NESUG |
2006 |
Supporting a Global SAS Programming Environment? Real World Applications in an Outsourcing Model |
Mark Penniston,
Karen Curran |
|
6 |
| NESUG |
2006 |
Using PROC CDISC |
Chauthi Nguyen |
|
5 |
| NESUG |
2006 |
Using SAS Data Integration Studio to Convert Clinical Trials Data to the CDISC SDTM Standard |
Barry R. Cohen |
|
8 |
| PharmaSUG |
2006 |
CDISC Implementation, Real World Applications |
Sy J. Truong |
|
26 |
| PharmaSUG |
2006 |
CDISC Submission and Compliance Training, The New Virtual Learning Methodology |
Dana Rafiee,
Michael C. Palmer |
|
2 |
| PharmaSUG |
2006 |
Cost Effective Ways to Generate DEFINE.PDF & DEFINE.XML |
Sy J. Truong |
|
7 |
| PharmaSUG |
2006 |
Evolution and Implementation of the CDISC Study Data Tabulation Model (SDTM) |
Tom Guinter,
Fred Wood |
|
6 |
| PharmaSUG |
2006 |
External Data Utility (EDU), a SAS Tool to Manage Data from Acquisition to Database Release |
Margaret Hung,
Mohit Goel,
Sheila Moody |
|
11 |
| PharmaSUG |
2006 |
Implementing CDISC Data Models in the SAS Metadata Server |
Michael Kilhullen |
|
7 |
| PharmaSUG |
2006 |
Imputing ISO8601 Dates From Character Variables Containing Partial Dates |
John R. Gerlach |
|
4 |
| PharmaSUG |
2006 |
Mapping Clinical Data to a Standard Structure: A Table Driven Approach |
Nancy Brucken,
Paul K. Slagle |
|
7 |
| PharmaSUG |
2006 |
MDMAP - An innovative application utilized in the management of clinical trial metadata |
Gregory Ridge,
Neeru Bhardwaj |
|
9 |
| PharmaSUG |
2006 |
Preparing CTD (Common Technical Document) for FDA Submission |
Charlie Xu |
|
7 |
| PharmaSUG |
2006 |
PROC FORMAT is Our Friend |
Erin M. Christen |
|
20 |
| PharmaSUG |
2006 |
SAS Drug Development: Bringing Innovation to Life Sciences |
David Handelsman |
|
12 |
| PharmaSUG |
2006 |
Update: CDISC Interchange Abstract Harmonizing CDISC Models - SDTM & ADaM |
Edward D. Helton,
Stephen J. Ruberg,
Cathy Barrows,
Musa Nsereko,
Greg Anglin |
|
3 |
| PharmaSUG |
2006 |
Using SAS ETL Studio to Convert Clinical Trials Data to the CDISC SDTM |
Barry R. Cohen |
|
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 - What is CDISC and Why Standards? |
Laurie Rose,
Becky Kush |
source |
41 |
| PHUSE EU |
2005 |
Customer oriented CDISC implementation |
Edelbert Arnold,
Ulrike Plank |
source
poster source |
13 |
| 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 |
Pharmacovigilance Using SAS Technology , Analytics and CDISC Data Standards, including the SDTM-ADaM Submission Relationship |
Edward D. Helton |
source |
39 |
| 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 Future of CDISC |
Becky Kush |
source |
50 |
| PHUSE EU |
2005 |
Visions of a Drug Development Data Warehouse |
Paul Vervuren |
source |
7 |
| WUSS |
2005 |
A Macro Mapping Date and Time Variable to CDISC Date and Time Variable |
Song Liu,
Brett Sellars |
source |
5 |
| WUSS |
2005 |
Data Integrity through DEFINE.PDF and DEFINE.XML |
Sy J. Truong |
source |
14 |
| WUSS |
2005 |
Transforming Data for CDISC and ISS |
Sy J. Truong |
source |
11 |
| NESUG |
2005 |
A Macro to Create Data Definition Documents |
Aileen L. Yam |
|
6 |
| NESUG |
2005 |
MDMAP - An innovative application utilized in the management of clinical trial metadata |
Gregory Ridge,
Neeru Bhardwaj |
|
9 |
| PharmaSUG |
2005 |
Automated Excel-lent Validation |
Janet E. Stuelpner |
|
9 |
| PharmaSUG |
2005 |
CDISC for electronic submissions - A Table Translation Program |
John H. Adams,
Boehringer Ingelheim |
|
15 |
| PharmaSUG |
2005 |
Implementation of the CDISC SDTM at the Duke Clinical Research Institute |
Jack Shostak |
|
12 |
| PharmaSUG |
2005 |
Pharmacovigilance and Drug Safety Reporting Algorithms (Content and Process) |
David Olaleye,
Michael Kilhullen,
Gail Kongable,
Tanyss Mason,
Eugenia Bastos,
Edward D. Helton |
|
8 |
| PharmaSUG |
2005 |
Program Flow Design for Efficient CRT Programming |
Sam Mao |
|
10 |
| PharmaSUG |
2005 |
SAS Dataset Content Conversion to CDISC Data Standards |
Anthony L. Friebel,
Thomas Cox,
Edward D. Helton |
|
10 |
| PharmaSUG |
2005 |
Some Statistical Programming Considerations for e-Submission |
Hang Pang |
|
6 |
| 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 |
XML Basics for SAS Programmers |
Yong Li |
|
5 |
| WUSS |
2004 |
Successful FDA Advisory Meetings by using Analysis Datasets |
Sandy Chang,
Steven Wong |
source |
10 |
| WUSS |
2004 |
The Path to Data Standards |
Sy J. Truong |
source |
10 |
| PharmaSUG |
2004 |
A Simplified Way to Create Flags for the Three-Dimensional Prior, Concomitant, and Post Medication Classification |
Aileen L. Yam |
|
5 |
| PharmaSUG |
2004 |
An FDA-Requested XML Replacement for SAS Version 5 Transport Files in U.S. Regulatory Submissions |
Michael C. Palmer |
|
5 |
| PharmaSUG |
2004 |
Data Standards with and without CDISC |
Sy J. Truong |
|
8 |
| PharmaSUG |
2004 |
Defining and Validating CDISC Data Standards to XML in SAS Technology |
Anthony L. Friebel |
|
6 |
| PharmaSUG |
2004 |
Using SAS to Speed up Annotating Case Report Forms in PDF Format |
Dirk Spruck |
|
7 |
| SUGI |
2004 |
Data Management in Analyzing Clinic Trial Data - Metadata Application |
Julia Z. Zhang,
David C. Chen |
source |
6 |
| SUGI |
2004 |
XML in the DATA Step |
Michael C. Palmer |
source |
13 |
| WUSS |
2003 |
XML in the DATA Step |
Michael C. Palmer |
source |
6 |
| NESUG |
2003 |
ODS RTF: Practical Tips |
Cindy Tong |
|
6 |
| PharmaSUG |
2003 |
10 Things Every Programmer Should Know About Electronic Submissions |
Greg Silva |
|
4 |
| 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 |
CDISC: Why SAS Programmers Need to Know |
Victor Sun |
|
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 |
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 |
Using RTF, EPS and PDFMARK to Automate the Creation of Your DEFINE.PDF Document for Electronic Submissions |
Dirk Spruck,
Aventis Behring |
|
6 |
| SUGI |
2003 |
A Table-Driven Solution for Clinical Data Submission |
Jim Sattler |
source |
6 |
| NESUG |
2002 |
Focusing on Our New Deliverables--CRT and Analysis Data Sets |
Phebe Joseph |
|
8 |
| NESUG |
2002 |
PC TVS - - Say What' |
Stephen J. Rhoades |
|
6 |
| PharmaSUG |
2002 |
Data Exploration in the Pharmaceutical Industry |
Andrew T. Fagan |
|
8 |
| PharmaSUG |
2002 |
It's Easy If You Know How: Importing, Processing, and Exporting CDISC XML with SAS |
Michael C. Palmer |
|
4 |
| PharmaSUG |
2002 |
Streamlining SAS Data Listings to Match CRF Data Flow for Use in Limited Internal Audits |
Michael Acra,
Greg Henkle,
Glaxo Smith Kline |
|
2 |
| 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 |
Various Techniques for Processing CDISC ODM XML |
Christopher R. Olinger |
|
34 |
| NESUG |
2001 |
Developing and Implementing Programming Standards Without Stifling Programmer Creativity |
Paul Doucette |
|
5 |
| WUSS |
2001 |
A Method to Import, Process, and Export Arbritrary XML Files with SAS |
Michael C. Palmer,
Cecilia A. Hale |
source |
5 |
| SESUG |
2001 |
SAS and Electronic Mail: Send E-mail Faster, and DEFINITELY More Efficiently |
Roy I. Fleischer,
Sodexho Marriott |
source |
5 |
| SCSUG |
2001 |
SAS and Electronic Mail: Send e-mail Faster, and DEFINITELY more efficienctly |
Roy I. Fleischer |
|
5 |
| SEUGI |
2001 |
Send in the Clones [presentation] |
Philip Whittall |
source |
22 |
| PharmaSUG |
2001 |
A Method to Import, Process, and Export Arbitrary XML Files with SAS |
Michael C. Palmer,
Cecilia A. Hale |
|
4 |
| PharmaSUG |
2001 |
ESUB11, an Application to Automate the Production of Item 11 For NDA Electronic Submissions |
Margaret Hung |
|
8 |
| PharmaSUG |
2001 |
The Changing Nature of SAS Programming in the Pharmaceuticals Industry |
Steven Light |
|
4 |
| SUGI |
2001 |
SAS and Electronic Mail: Send E-mail Faster, and DEFINITELY More Efficiently |
Roy I. Fleischer |
source |
5 |
| NESUG |
2000 |
Using Batch MVS SAS.... To Send Email Via A UNIX.... Email Server |
Stephen M. Englert |
|
5 |
| SUGI |
2000 |
Using Batch MVS SAS Software to Send Email Via a UNIX Email Server |
Stephen M. Englert |
source |
5 |
| SUGI |
1999 |
Annotated Case Report Form Automation System |
Anthony M. Cavaliere,
Shi-Tao Yeh |
source |
5 |
| SESUG |
1996 |
Using SAS To Load a Data Warehouse, Write HTML, and Send Analyses to the World-Wide Web - All in Real Time |
Jay Jacob Wind |
|
10 |
| PNWSUG |
1996 |
Using SAS View to Enhance Software Quality, Improve Data Security and Reduce Data Replication |
Adam Hendricks |
|
27 |
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