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PHUSE US 2022 Papers - Index

118 papers. Source: PHUSE (Pharmaceutical Users Software Exchange) US Connect conference proceedings.

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# Title
×		 Authors
×		 Abstract
×		 Keywords
×		 Extras Pages
1 'Verify Outputs' Product Demonstration: Validation of Statistical Outputs Using Automation Ilan Carmeli,
Yoran Bar		 Presentation trial elements, safety population, system organ class, per protocol, sample, data cleaning, analysis set source
video		 17
2 (eDISH) Evaluation of Drug-induced Serious Hepatotoxicity Using SAS Graph Jaimin Patel Presentation laboratory data, clinical trial, treatment arm, sample, scatter plot source 13
3 A Better Way: eCOA/ePRO Annotated Screen Reports (aSR) Provide Data Clarity from Data Collection to Submission Franklin E. Menius,
Monali Khanna,
Vincent Allibone		 With the adoption of electronic Clinical Outcome Assessments (eCOA) and electronic Patient Reported Outcomes (ePRO) for collection of questionnaire and patient clinical data there is a growing need to efficiently map raw data collection through the study life cycle on to submission and beyond. The proposed solution is the creation of annotated Screen Reports (aSR) for eCOA/ePRO. Like an annotated Case Report Form (aCRF) the annotated screen report file documents the location of collected data on a patient or clinician device to corresponding domains and variables included in intermediate and submitted datasets. The annotated screen report provides easy access to study metadata for programmers and statisticians plus can be submitted along with the aCRF to regulatory bodies to aid the reviewer. This presentation will highlight the many benefits of annotated screen reports for eCOA/ePRO, guidelines to creating them, as well as provide examples and use cases crf, clinical research, data cleaning, cdisc source
presentation source		 6
4 A Day on the Fast Track: How a Statistical Computing Environment Helps to Streamline Programming Jörn Bilow Presentation 21 cfr part 11, audit trail, data integrity, data science, data cleaning, access control, rest api source
video		 14
5 A Deep-learning-based Virtual Assistant for Better and Faster Clinical Insights Aditya Gadiko,
Nekzad Shroff		 deep learning source
presentation source		 10
6 A Duet of SAS and Python Generating XML File for Results Disclosure to ClinicalTrials.gov and EudraCT Linghui Zhang Presentation clinical trial, statistical programmer source
video		 16
7 A Practical Exploration of SEND for CBER Submissions Jack Baker Now that the Center for Biologics Evaluation and Research (CBER) division of the FDA has initiated support to receive SEND datasets in future submissions, sponsors are turning their attention to the requirement date of 15 March 2023. Industry understanding of how to report and leverage immunogenicity, biodistribution, and/or tumorigenicity data endpoints will be critical to the advancement of gene therapies, vaccines, and/or cell products in the fight against Cancer and other diseases. At Labcorp, we too are focused on our SEND readiness for submissions made to the OVRR, OTAT, and OBRR offices of CBER, and we would like to share our findings as we prepare SEND datasets for studies conducted by our Nonclinical Toxicology and Preclinical Oncology teams controlled terminology, flat file, sample, cdisc source
presentation source		 11
8 A Simple Way to Improve the Efficiency of Log Checking in SAS Enterprise Guide Danny Hsu sas enterprise guide, options statement source
video
presentation source		 3
9 Advancing RBQM Strategy with Enterprise-level Quality Risk Analytics, NLP/AI, and Immersive Technologies Vera Pomerantseva Presentation gcp, data governance, protocol amendment, resource allocation, outlier source 20
10 Agile Methodology in Pharma - Applications and Best Practices Maria Dalton Poster source 1
11 Aligning the Dots: Simplifying Table Presentation in R Maya Gans,
Michael Stackhouse		 Presentation source
video		 16
12 An open-source project to map lab terminology and standardize units for analysis Sunil Kumar Pusarla,
Kevin R. Viel,
Dante Di Tommaso		 FDA requires LOINC codes, an international standard that uniquely and unambiguously identifies laboratory measurements(1), for lab data supporting new drug and licensing applications, in studies initiated in 2020, and 2021(2). The burden of preparing lab results for analysis drops whenever a laboratory provides LOINC codes. The FDA does recognize "inconsistencies in the specification and interpretation of LOINC codes submitted across tests, studies, and subjects."(3) Above and beyond analyte terminology, sponsors must convert results to standard analysis units. Moving forward, whether handling LOINC inconsistencies, or conducting studies that rely on lab results for which LOINC codes are not available, preparing laboratory results for robust and persuasive analyses will continue to present challenges of standardization and conversion. Sponsor variability is suboptimal in the context of public health policy lookup, data step, proc sql, data cleaning, laboratory data, data validation rules source
video
presentation source		 7
13 AnalysisMate: An Innovative Data Analytical Platform Unnat Patel Presentation source
video		 12
14 Applications of the R Package Validation Framework and {valtools} Ellis Hughes Presentation data cleaning, data governance, data science, clinical trial, validation documentation, r package source
video		 34
15 Automating Analysis Result Metadata Ghanshyam Jangid Presentation adam dataset, proc report, dataset, excel, proc step, raw data, cdisc source
video		 17
16 B Corp Accreditation in the Pharmaceutical Industry: What Is It and Why Is It Important for Business? Andrew Horden,
Stuart McGuire		 Presentation pharmaceutical industry, privacy source
video		 10
17 Bias in Machine Learning: Your Responsibilities as a Programmer Jim Box Presentation deep learning, machine learning, artificial intelligence, data science, excel source 34
18 Bivariate Analysis Dataset Structure (ADBIVAR): Analysis-ready Dataset Structure for Bivariate Analysis Based on BDS Principles Michael Pannucci,
Toshio Kimura		 Poster: "Analysis-ready" is a key concept of the ADaM-BDS framework whereby a formulation of a where-clause yields a dataset that can be passed to a statistical analysis or modeling procedure with minimal, if any, further manipulation. However, current BDS standards are limited to single-endpoint analysis; that is, an analysis or model that relates one endpoint to a set of factors such as covariates, strata, or other independent variable(s). Consider the case where the analysis is not an endpoint as a function of other factors, but rather an analysis simultaneously involving two distinct endpoints. A common example of this would be a correlation analysis. Within SAS, the existing BDS structure would not be "analysis-ready" when using the CORR procedure. A fair amount of data manipulation, including, but not limited to, Cartesian products and transpositions of data, is required before calling the procedure correlation, bivariate analysis source 1
19 CDISC Analysis Results Standards - Approach and Development Update Bess LeRoy,
Jeffrey M. Abolafia,
Bhavin Busa		 Presentation adam dataset, clinical data, clinical trial, data science, cdisc source 18
20 Choosing Your Tile: Quick Clinical Data Summary Visualizations using SAS Enterprise Guide 7.1 Graph Tasks (Tile Charts) Amber Frazier sas enterprise guide, outlier source
presentation source		 4
21 Circus of Python in Real-world Evidence Sucharita Pilli Presentation source 17
22 Clinical Data Standardization and Integration Using Data Warehouse and Data Mart Processes Clio Wu Presentation data mart, data warehouse, adam dataset, data standardization, liquidity gap, data transformation, clinical data, cdisc source 15
23 Clinical Statistical Reporting in a Multilingual World Michael S Rimler,
Michael Stackhouse		 Presentation survival analysis, hazard ratio, data cleaning source 11
24 Closing the Gap: Creating an End to End R Package Toolkit for the Clinical Reporting Pipeline Benjamin Straub,
Eli Miller		 Presentation source
video		 11
25 Collection, Standardization, and Reporting of Adverse Events with Toxicity Changes Using CDISC Standards in Oncology Clinical Trials Madhusudhan Reddy Papasani,
Swathi Kotla,
Elisabeth Pyle		 Understanding the temporal changes of toxicity is crucial for accurate comparison of safety profiles between the treatments or even multiple toxicities within a treatment. The National Cancer Institute's (NCI) Common Terminology Criteria for Adverse Events (CTCAE) is a widely used standard for reporting adverse event toxicity grades in oncology studies. Adverse events are evaluated against the NCI CTCAE guidelines and assigned toxicity grades. In this paper, we will carefully review the collection of adverse events and toxicity changes over time within-the study and rendering of the collected data in the SDTM Adverse Events (AE) and Finding About (FA) domains. Further evaluation includes using AE and FA domains to define treatment-emergent flags in the Analysis Dataset for Adverse Events (ADAE) for the events that are worsening in toxicity after treatment ctcae grade, adverse events, adam dataset, sdtm domain, cdisc source
video
presentation source		 12
26 Combining Multiple R Outputs into One HTML File with Bookmarks Baoqing Li,
Eric Zhang		 Documents in HTML format are popular in pharmaceutical companies. Statistical programmers might wish to combine multiple tables, listings and/or figures in RTF or HTML generated by R into one HTML file for reviews, topline reports, submissions, or other purposes. R markdown is one good program ming language to make reports in high quality document. We create R programs to generate the R markdown scripts, which achieve the combination of multiple R outputs with bookmarks into one HTML file. The generated R markdown scripts also can be edited by statisticians as needed before combining multiple R outputs. Then we run the R markdown scripts to generate the HTML file. The paper describes the method, capabilities, features, and usage of the combination of multiple R outputs analysis set, sample, excel source
presentation source		 5
27 Data Classification Automation Jeanne Lightbody,
Robert Musterer		 Presentation source 14
28 Data Standardization at Scale with the elluminate Clinical Data Cloud Nathan Johnson Presentation clinical research, clinical trial, sas programmer, data science source 19
29 Define and Explore Patient Cohorts Catharina Dahlbo,
Eva Kelty		 Presentation adverse events source 9
30 Design ADSL and ADBASE in Cell Therapy Ryan Krause,
Xiang Wang		 Presentation clinical programming, imputation, sample source
video		 24
31 Digital Biomarkers in Clinical Submissions Unnat Patel,
Vijay Pasapula		 Poster: Within the healthcare industry, there's a consensus on the utility of digital biomarkers; however, the categorization of these novel tools and terminology is still in debate. Classification criteria may include: Type: How does the patient interact with the device? Active or passive? Measurement: On what physiological system is the device used? Application: How is the biomarker used? Safety monitoring, patient enrollment, medication adherence or clinical efficacy? Feature: What type of event and population data is collected? Individual or population? Longitudinal or discrete timepoint? FDA device classification: What regulatory class will be used when seeking approval for the device to be used in health care? Device status relative to clinical insight: Has the device or the biomarker been validated previously? (see table to right) The biggest challenge to standardized nomenclature is the wide range of applications and types of devices source 1
32 Does My Skill Set Still Meet the Needs of the Market? Dmytro Skorba Presentation clinical trial, excel source
video		 22
33 DPS Helper: A Web Application to Create the Data Presentation Specifications Word Document in Clinical Trials Asavari Mehta,
Xiaoguang Yan		 Presentation analysis set, safety population, treatment arm, clinical trial, sas programmer, sample source
video		 37
34 Entering the Pharmaceutical Industry - A New Graduate Perspective Greg Silva Poster source 1
35 Expand Your Insights by Utilizing Open-source Data Visualizations within Power BI Christopher C. Hurley Poster data visualization, data science source 1
36 Explanations in the Study Data Reviewer's Guide: How's It Going? Kristin Kelly Presentation type i error, data cleaning source
video		 13
37 Fast and Curious: Reusability with Standardized Dashboards for Safety and Study Follow-up Jeroen Gielen,
Roman Radelicki		 Presentation clinical research source 21
38 FDA Study Data Technical Rejection Criteria (TRC): What You Need to Know! Jiang Xu,
Lina Cong		 Presentation data cleaning, clinical trial, trial summary, clinical data, data validation rules source
video		 26
39 Finding a New Home-Work Balance: The Importance of Disconnecting Yourself in an Online World Annelies Van Zeveren,
Goele Aerts		 Presentation clinical research source
video		 19
40 Generating Statistical Figures for Regulatory Submission: Comparison of SAS and R Girija Javvaji,
Sivasankar Konda		 forest plot, sas syntax source
video
presentation source		 11
41 GxP-compliant Traceability for Any Open-source Software Henrik Steudel Poster proc sql, access control source 1
42 Harmonizing Your Traditional Workflow with R Michael Stackhouse,
Nicholas Masel		 Presentation source 13
43 High-quality COVID Vaccine Submission at Lightning Speed Helen Yang,
Kiran Challagali		 Presentation clinical research, regulatory submission, clinical programming, sample source 9
44 How Disclosure Teams Are Collaborating and Embracing the Changes Imposed by Global Transparency Regulations Elliot Zimmerman Presentation clinical trial, sample source 12
45 How Rapid SDTM Data Conversion Enabled Early Insights into Vaccine Safety and Efficacy in COVID-19 Trials Gilbert Hunter,
Rachael Yates		 Presentation sdtm domain, cdisc source
video		 16
46 Implementation of Real-world Structured/ Unstructured Clinical Data in Real-world Evidence Trials (RWEs) for Regulatory Submissions Ravi Mokkarala,
Yan Shen		 Presentation data cleaning, unstructured data, stage 1, stage 2 source 12
47 Incorporating Immunogenicity Data from Various Analyzing Labs Elisabeth van Son-Palmen,
Gunasekaran Subramaniam		 Presentation sample, clinical trial, merge statement, data merging, raw data, sdtm programming, structured data, cdisc source 19
48 Integration of SAS LSAF and Veeva Using REST APIs Ben E. Bocchicchio,
Pritesh Desai		 Presentation proc step, proc http, proc lua, life sciences, data science, laboratory data, rest api source 16
49 Interactive Leadership Discussion Forum Alison Batty,
Brian Hermann		 Presentation data science source 13
50 Introducing Reporting Packages in R for TFLs Pavan Reddy,
Thomas Kalfas		 Presentation sample, clinical data, data science, clinical trial, create table, demographics table, regulatory submission source
video		 12
51 Intuitive Querying of a Graph Database Catharina Dahlbo,
Eva Kelty		 Presentation adverse events source 10
52 Jumping on the Real-world Data (RWD)/Real-world Evidence (RWE) Bandwagon? A Guide for Statistical Programmers to Understand Payer Claims Data Rachana Agarwal Presentation data mart, overall survival, service provider, statistical programmer, sample source
video		 13
53 Just Say No to Data Listings! Maria Dalton Poster: Maria Dalton - Mercidita Navarro - navarro, Nancy Brucken - Aiming Yang - * Greg Ball - https://phuse.s3.eu-central-1.amazonaws.com/Deliverables/Safety+Analytics/WP061.pdf regulatory submission, data visualization source 1
54 Lessons from QTL Process Installation in a Big Pharma Company Nathalie van Borrendam,
Rohan Shirolkar		 Presentation source 7
55 Leveraging an MDR: More than a Repository Carlo Radovsky Presentation clinical research, label statement, proc http, regulatory programming, proc step source 13
56 Leveraging the OHDSI Methods Library and SAS Viya for Clinical Decision-Making Using Real-world Data (RWD) Samiul Haque,
Sherrine Eid		 Presentation sas viya source 18
57 Machine Learning in R to Predict Outcomes from Biomarker Data Benno F. Kurch,
Prakash Dev		 Presentation machine learning, proc hpsplit, predictor variable, regression analysis, response variable, data cleaning, proc princomp source
video		 21
58 Make SAS RENAME Function Work for You Ryan Krause,
Xiang Wang		 Poster dataset, catalog source 1
59 Maximizing Your Potential and Achieving Your Professional and Personal Goals Munish Mehra Presentation source 11
60 Mesa: A Shiny-based Web Application for Drag-and-drop Creation of Metadata-driven Statistical Summary Tables Qiaobing Bergsma,
Tim Bergsma		 Presentation label statement, group by, safety population source
video		 4
61 Metadata-driven Case Report Tabulation for Regulatory Submissions Jacques Lanoue,
Rajashekar Thota		 raw data, sdtm programming, sdtm domain, sdtm programmer, cdisc source
presentation source		 8
62 Navigation of Professional Development Planning Through the Performance Appraisal Process Parag Shiralkar Presentation bds, adam dataset, cdisc source
video		 13
63 Necessity is the Mother of Invention! Experiences and Innovation from Studies in COVID-19 Amanda Lopuski,
Matt Jones		 Presentation data cleaning source
video		 7
64 Non-Random Circular Jittering Algorithm Using Trigonometric Functions for Scatter Plots of Ordinal Outcomes with Overlapping Points Michael Pannucci Presentation scatter plot, bubble plot, box plot, in= source 22
65 Organizational Transition from SAS to Open-source Programming for the whole department Kevin Lee,
Manikandan Jeeva		 Poster source 1
66 Our Technical Implementation of Scrum and Kanban Ari Siggaard Knoph,
Kristian Troejelsgaard Nielsen		 Presentation output delivery system, excel source 21
67 Pan-pharma Industry Collaboration - New Horizon, Success Stories Tadeusz Lewandowski Presentation clinical trial, imputation, adam dataset, pharmaceutical industry, multiple imputation, quality control, sensitivity analysis, cdisc source
video		 21
68 Patient Registries - Challenges and Opportunities Sophia Zilber Presentation clinical programming, clinical data, data science, statistical programmer source 20
69 PHUSE Education - Connecting the Dots Sascha Ahrweiler Poster source 1
70 Practical Challenges in Handling Unstructured Data Using Artificial Intelligence Farha Feroze Presentation clinical trial, csr, artificial intelligence, efficacy summary, unstructured data source
video		 11
71 Preparing Vaccine Studies for Regulatory Submissions Kristin Kelly Presentation source 30
72 Programming and Reporting on a Master Protocol in Cell and Gene Therapy Rabia Ahmad,
Amit Jain		 adverse events, dose source
video
presentation source		 10
73 R and its Application in Clinical Trial Data Analysis Santosh Kumar Davuluri Presentation clinical trial, data science, clinical data, waterfall chart, change from baseline, box plot, scatter plot source
video		 21
74 R Got This! Delivering a Complete Statistical Package Using R Alice Ehmann,
Michael S Rimler		 Presentation audit trail, data integrity, independent qc source
video		 10
75 RBM - The New Normal Vigilante for CROs With AI and ML Vidya Muthukumar Presentation protocol deviations, adverse events, data integrity, clinical trial, database lock, clinical research, verbatim term source 18
76 Real-time Interactive Dashboard for Clinical Trials Kris Liu Presentation system organ class, randomization, adverse events, clinical data, open label, full analysis set, data visualization source 9
77 Real-world Evidence of Mental Health During and After COVID-19 Jaganadha Rao Gundu Presentation clinical programming source 24
78 Reassure Your Assumptions Using Sensitivity Analysis Vadym Kalinichenko Presentation missing value, imputation, sensitivity analysis, treatment effect, treatment arm, change from baseline, proc mi source
video		 29
79 Reflections on Our Experience Moving to Open-source Pan-pharma Code Collaboration on Clinical Trial Reporting Tools James Black Presentation clinical trial source 20
80 Reflective Logic in a Graph Database Catharina Dahlbo,
Eva Kelty		 Poster source 1
81 RStudio Pharma Updates: 2021 Year in Review and Beyond Philip Bowsher Presentation data cleaning source
video		 18
82 Safety ADaM Automation from Design to Implementation Chengxin Li,
Toshio Kimura		 Presentation macro parameter, imputation, crossover study, datetime variable, flag variable, class variable, ordinal variable, cdisc source
video		 18
83 Safety First, Agility Comes: Challenges and Solutions to Fulfilling IND Safety Requirements Hong Wang,
Ke Xiao		 randomization, adverse events source
presentation source		 7
84 SAS Features We Underestimate Andrii Borzenkov Presentation cpu time, hash table, output delivery system source
video		 23
85 See No Data, Hear No Risk ... Cathal Gallagher Presentation source 16
86 SPACE - Launching GSK Biostatistics towards new horizons Eileen Ching In today's data-centric environment, having a modern fit-for-future technical landscape for statistical computing and data science is a critical success factor in the pursuit of bringing the best medicines and vaccines to patients faster and at a lower cost. Like many in the industry, GSK embarked on a journey to design and implement such a landscape in 2020, in the form of a large and ambitious program called SPACE (Statistical & Programming Analytics Computing Environment). Unlike the traditional approach to programs like this, GSK chose to adopt an agile delivery framework which also meant a shared learning curve. The aim of the program was focused on delivering capabilities for interactive data visualization, a modern Statistical Computing Environment (SCE), and planning, publishing, and sharing of results. SPACE is seen as the key enabler for transforming Biostatistics at GSK data science, clinical trial, data cleaning, clinical research, clinical programming source
presentation source		 10
87 Standards Governance Strengthened by MDR Technology Kenneth Stoltzfus,
Maria Sekac		 Presentation data validation rules, metadata management source 22
88 Statistical Programming Operational Review Dashboard Kathleen J. Harkins,
Shuqi Zhao		 Presentation clinical programming, csr, dataset, excel, clinical trial, interim analysis, regulatory submission source
video		 16
89 Staying Ahead of the Curve: The Future Direction of Modernization of Statistical Analytics (MSA) Peter Mesenbrink Presentation analytics platform, clinical data, group sequential design, data cleaning, clinical research, clinical trial, regulatory submission source 19
90 Table Mining: The Barrier for Automation Ilan Carmeli,
Mor Ram-On		 Presentation per protocol, sample, analysis set, safety population, data science, output delivery system source 16
91 The Art of Work Flowing Your Clinical Submission Scripts Brian K. Varney As more subject data flows into a clinical database, series of programs in development will likely need to be run repeatedly to keep an eye on table, listing, and figure results. For many years, pharmaceutical companies have been using SAS functionality of either driver programs and/or SAS Enterprise Guide project flows. In R, there are a few options that parallel what has traditionally been performed in SAS. This paper intends to explore how to make use of R and RStudio to assist with the management of driver programs, as well as alternative project workflow methodologies. We will compare the benefits of using a typical driver script with the "make" style of programming using the 'targets' package. In addition, we will explore the best practices when developing a workflow that is intended only for yourself, and a workflow that is intended to be shared across a wide group of users sas enterprise guide, macro variable source
video
presentation source		 5
92 The Bioresearch Monitoring Data Reviewer's Guide (BDRG) Julie Maynard,
Sopan Dharma Kaith		 Presentation clinical trial, crf, data cleaning, adverse events, clinical data, pharmaceutical industry, data validation rules source 25
93 The Complexity and Magnitude of Participant Reactogenicity Data Gunasekaran Subramaniam,
Katrien Van der Donck		 Presentation ctcae grade, missing value, secondary endpoint, data cleaning, data science source
video		 21
94 The Conversion of an SAS Macro to R Franklin E. Menius Presentation data science, length statement, format statement, macro definition source
video		 9
95 The Decentralized Trials Data Problem: Foundations for the Future of Clinical Trials Raj Indupuri Presentation data governance, outlier, data pipeline, clinical data, clinical endpoint, clinical trial, data review source
video		 11
96 The Emerging Use of Automation to Address the Challenge of Cross-Table Consistency Checking of Output Used in the Reporting of Clinical Trial Data Hugh Donovan,
Naama Feilchenfeld		 Presentation adverse events, safety population, trial elements, sample, per protocol, csr, serious adverse event source
video		 16
97 The Finding is a Date Lea Nørgreen Gustafsson,
Rasmus Kragh Nielsen		 Presentation statistical programmer, clinical programming source 26
98 The Future is Now Amy Gillespie,
Ellen L. Asam		 Presentation clinical programming source 23
99 The RBM to RBQM Transformation: More Than the Method or the Tool Alison Banda,
Jason Konn		 Presentation clinical trial, interest rate, define-xml, cdisc source 12
100 Thinking Outside of the Box: Real-world Data for Ultra-rare Disease Studies Lisa Kaye Brooks Presentation source 32
101 Timber! Creating Logs and Addins for Audit-ready R Code Benjamin Straub Presentation clinical programming, informat statement source 8
102 Title: AI Application for Authoring Clinical Study Reports Eric Weising,
Farha Feroze		 Presentation csr, clinical trial, audit trail source
video		 9
103 Transformation from Prescriptive Clinical Data Analyses to Dynamic Data-driven Analytics through the Adoption of Modularized Cloud Components Andy Ratcliffe,
Chris Decker		 Presentation data science, dataset, data validation rules, sas studio, proof of concept, data integrity, big data source 35
104 Trial Design Datasets in Oncology Clinical Trials Anastasiia Drach Presentation proc sql, trial summary, proc step, macro definition, trial design model, proc export, excel, cdisc source
video		 23
105 Trial Summary SDTM Domain Made Easy for Regulatory Submissions Kishore Pothuri Presentation trial summary, clinical trial, adaptive design, label statement, controlled terminology, database lock, clinical research, cdisc source 16
106 Using AI-based Technology to Accelerate Clinical Trial Data Sharing and Reuse Ron Kaine,
Thomasin Element		 Presentation csv, medical history, regulatory submission, clinical trial, patient-year, machine learning, phase iii source
video		 33
107 Using Cutting-edge Open-source Tools to Drill into Clinical Safety Data: A Look into Recent Developments in Tplyr and safetyGraphics Eli Miller Presentation source
video		 2
108 Using odmlib to Create ODM and Define-XML Tools in Python Samuel Hume This paper introduces the odmlib Python library for working with ODM and its extensions and spotlights using odmlib to generate a Define-XML v2.1 document. The odmlib library provides an object-oriented interface that simplifies creating and processing ODM or Define-XML documents. It supports serializations in XML and JSON and provides the means to easily create custom ODM or Define-XML extensions. Odmlib also supports conformance checks and schema validation to ensure quality and standards compliance. The odmlib library is available on GitHub under the MIT license. ODM models have been created for ODM v1.3.2, Define-XML v2.0 and v2.1, Dataset-XML v1.0, CT- XML v1.1.1, and Library-XML v1.0. The odmlib project is open to collaborators interested in making contributions such as new features, example programs, additional models, tests, or documentation data cleaning, vital signs, cdisc source
presentation source		 6
109 Using the Geometric Properties of Datasets to Analyze the Accuracy of COVID-19 Forecasting Models Irina Kotenko,
Kostiantyn Drach		 Presentation time series analysis, neural network, statistical programmer, confidence interval, clinical data, clinical programming, clinical sas source 30
110 Using the Nest-map-unnest Workflow in R for Sub-group Analysis in Clinical Trial Reporting Mia Qi,
Sheng-Wei Wang		 Presentation model training, proc phreg, hazard ratio, forest plot, adtte, survival analysis, adam dataset, cdisc source
video		 12
111 Vaccine Trials: The Basics You Need to Know Prashanthi Selvakumar Presentation sample, adam dataset, sdtm domain, cdisc source 11
112 Volcano Plot for Adverse Event Analysis in R Kamleshkumar Patel Presentation volcano plot, p-value, adverse events, odds ratio, relative risk, scatter plot, trial elements source
video		 15
113 We R in SPACE (Statistical Programming And Computing Environment). And We R Not Alone! Alastair Scarlett,
Sumesh Kalappurakal		 Presentation clinical programming, data science, clinical data, clinical trial, sas grid, sas studio, statistical programmer source 7
114 When to CASL and Not to CASL - SAS Programming in the SAS Viya Platform Pritesh Desai Presentation sas viya, sas 9, proc step, data step, by group processing, proc sql, sas studio source 15
115 Where in the Cloud is My Data Coming From? Presentation on How to Extract Cloud Provider Audit Trails to Maintain Data Custody Pritesh Desai Presentation audit trail source 20
116 Which Side of the Fence Are You On? A Head of Statistical Programming's Perspectives Working for Sponsors and CROs Clio Wu Presentation clinical programming source 15
117 With Our Heads in the Cloud Jeroen Gielen,
Roman Radelicki		 Presentation source 18
118 Working Smarter with Data to Optimize Onsite Monitoring Jackie Gough Presentation clinical trial source 9

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