Advanced Programming Advanced Statistical Methods AI in Pharma, Biotech and Clinical Data Science Career Development, Leadership & Soft Skills Data Standards Implementation (CDISC, SEND, ADaM, SDTM) Data Visualization & Interactive Analytics Emerging Technologies (R, Python, GitHub etc.)

ePosters Hands-On Training PK/PD/ADA and Quantitative Pharmacology Real-World Data (RWD) and Real-World Evidence (RWE) Study Data Integration & Analysis Submission Standards for Global Health Authorities Tools, Tech & Innovation

Advanced Programming

AP-011. Take CoMmanD of Your Log: Using CMD to Check Your SAS® Program Logs
Richann Watson, DataRich Consulting

AP-108. The Problems Surrounding Rounding
Jennifer McGrogan, Independent
Mario Widel, Independent

AP-116. ARMed AutoTable Macro Agents: An ARM-Driven Framework for Automated Analysis Table Generation
Chengxin Li, AutoCheng Clinical Data Services LLC

AP-124. SAS Packages – an Ask About Anything Game
Bart Jablonski, yabwon

AP-127. Implementing Laboratory Toxicity Grading for CTCAE Version 6 and Beyond
Keith Shusterman, Disc Medicine
Mario Widel, Independent

AP-128. Unleashing Open-Source Potential in SAS: The PharmaForest Ecosystem (proc pharmaforest data=open_source out=… 😉
Sharad Chhetri, Takeda
Ryo Nakaya, Associate Director

AP-136. 2026 Efficiency Techniques in SAS 9.4
Stephen Sloan, Dawson D R

AP-146. AI-Assisted Modular Design for R Markdown Report Generation A Hybrid Architecture for Enhanced Maintainability and Cross-Study Scalability
Song Liu, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Jingwei Xiong, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

AP-148. The Tipsy Hangover: Avoiding Indent Headaches in SAS Reports
Lisa Mendez, N/A
Richann Watson, DataRich Consulting

AP-158. Applications of PROC COMPARE to parallel programming and other projects
Jayanth Iyengar, Data Systems Consultants LLC

AP-159. Speeding Up Your Validation Process is As Easy As 1, 2 and 3
Alice Cheng, Independent

AP-208. Programming Challenges in Developing PRO Analysis Datasets Under FDA’s New Submission Guidance
Weiwei Guo, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Caizhi Huang, Merck & Co., Inc., Rahway, NJ, USA

AP-211. Schema-Preserving Generation of Clinical TLF Templates and Executable R Code via Iterative LLM-Guided Debugging
Jaime Yan, Kardigan Bio
Ming Yang, Kura Oncology

AP-220. Do One Task, Get Another Done for Free: Use DEFX Tags in Comments to Fill Out Your define.xml
Brendan Bartley, Harvard T.H. Chan School of Public Health
Megan Hinger, Rho Inc

AP-222. Finding Macros Called Within A Directory of SAS® Programs
Derek Morgan, N/A
Tatiana Kazakova, Parexel

AP-228. Timing, Masking, and Resolution: Understanding and Debugging SAS Macros
Carleigh Crabtree, SAS

AP-233. Detecting Abnormal Page Breaks Using Grayscale Pixel-Density Analysis in R Shiny
Yi Guo, Pfizer Inc.

AP-237. SAS® Programming techniques for efficiency and code optimization
Jayanth Iyengar, Data Systems Consultants LLC

AP-246. Appreciating PROC SUMMARY/MEANS in Many NWAYS vs Summary Function in R
Brian Varney, Experis

AP-251. Modernizing Clinical Research Analytics with Cloud‑Optimized SAS Procedures
Jim Box, SAS Institute
Mary Dolegowski, SAS

AP-256. Advanced SAS Graph Template Language (GTL) with Practical Examples from Oncology Trials
Ceng Qian, Gilead Sciences, Inc.
Xu Wen, Gilead Sciences
Wei Lei, Gilead Science
Ling Han, Gilead

AP-257. Patient-Level, Dose-Stratified Swimmer Plots for Comparative Adverse Event Time-Course Assessment in Clinical Trials Using SAS® PROC TEMPLATE
Qingwei Hu, VeraMed Inc
Zhaoyu Xie, VeraMed Inc
Ji Qi, BioPier LLC a Veramed Company

AP-258. From Tables to Tolerances: The Evolving Role of Statistical Programmers in Risk-Based Quality Management (RBQM)
Vihar Patel, PPD, part of Thermo Fisher Scientific

AP-267. The Log Whisperer: Still Reading SAS Logs? Start Ranking Them
Charu Shankar, SAS Institute

AP-271. Stop Guessing. Start Matching. High-Impact SAS PRX Patterns in 20 minutes
Charu Shankar, SAS Institute

AP-274. Experience of an R Programmer Incorporating R in a SAS Studio Flow
Shelby Taylor, SAS Institute

AP-295. User-defined Functions for Programming Population PK and PKPD Datasets
Zhongqing He, Regeneron
Man Li, Regeneron
Hong Yan, Regeneron pharmaceuticals Inc

AP-313. Having Your Cake and Eating It Too: Automated Log Analysis Without Losing the SAS EG Log Window
Steve Black, Neurocrine Biosciences

AP-342. Has your SAS being ‘MEAN’ to your data yet?
Ruth Rivera Barragan, Ephicacy Consulting Group
Isaac Vazquez, Ephicacy Consulting Group

AP-375. One Word Can Make All the Difference(s): Strengthening Validation Practices with PROC COMPARE
John LaBore, SAS Institute
Josh Horstman, PharmaStat LLC

AP-418. Code Hard and Put away Wet: Replacing Hardcoded SAS® Software Quality Checks with Data-Driven Design and Defensive Programming Techniques That Validate Code and Control Data
Troy Hughes, Data Llama Analytics

Advanced Statistical Methods

AS-160. Oncology Solid Tumor Subcutaneous vs Intravenous Late-stage Study Analysis
Sumanjali Mangalarapu, Merck & Co., Inc., Rahway, NJ, USA
Chuqing Chen, Merck & Co., Inc., Rahway, NJ, USA
Anilkumar Anksapur, Merck & Co., Inc., Rahway, NJ, USA

AS-166. Quantifying Expression Divergence to Identify Candidate RNA-Binding Proteins Modulating Nonsense-Mediated Decay Across Human Tissues Using t-SNE Embedding Analysis
Liangwei He, University of Southern California

AS-190. Implementing Dynamic Time Warping in SAS 9.4 Using PROC IML: An Alternative Approach for Time-Series Model Evaluation
Yida Bao, University of Wisconsin Stout
Philippe Gaillard, Augusta University
Wei Yao, University of Wisconsin-Stout
Zheng Zhang, Murray State University
Rui Wang, 4707911632

AS-269. Tipping Point Analysis: An Illustration of Sensitivity Analysis on Non-Administrative Censoring for Progression-Free Survival (PFS)
Lihui Deng, Bristol Myers Squibb
Kylie Fan, BMS
Xiaoting Qin, Bristol Myers Squibb

AS-315. Machine Learning Models for Predicting Diabetes Using the PIMA Indians Dataset
Leon Davoody, Student

AS-359. Beyond Imitation: Selecting Synthetic Data with Purpose and Precision
Sundaresh Sankaran, SAS Institute
Pritesh Desai, sas
Sherrine Eid, SAS Institute

AS-365. A Faster Algorithm for the Finkelstein-Schoenfeld Test and Win Ratio in Hierarchical Composite Endpoint Analysis
James Austrow, Cleveland Clinic

AS-413. Construction and Evaluation of External Controls Using Propensity Score Methods
Bala Niharika Pillalamarri, LLX Solutions, LLC
Yayu Li, LLX Solutions
Hongbing Jin, LLX Solutions

AS-422. Linear versus Log–Log Confidence Intervals for Kaplan–Meier Survival Estimates: Statistical Rationale and Practical Implementation using SAS 9.4
Prayag Shah, Revolution Medicines

AI in Pharma, Biotech and Clinical Data Science

AI-101. How to Train Your Dragon – Embedding AI in Clinical Workflow. Illustrated through Oncology Swimmer Plots
Sri Pavan Vemuri, Not affiliated

AI-103. Data Without Borders: CDISC Data Hub for Multi-Language Clinical Analytics & AI
Mayank Singh, Johnson and Johnson MedTech (Neurovascular)

AI-123. Building a Model Context Protocol Server for AI-Driven Workflow Automation
Samiul Haque, Posit PBC

AI-125. Enhancing ADaM Specification Validation and Generation of SAS Codes Using LLM through Amazon Bedrock: A Practical Framework
Pavan Kumar Tatikonda, Takeda
Ryo Nakaya, Associate Director
Sravan Kongara, TAKEDA

AI-135. The Next Frontier of Statistical Programming: Vibe Coding with AI Coding Agents into SAS, R & Python
Kevin Lee, Clinvia
Nathan Lee, Clinvia

AI-141. Accelerating CDISC SEND Conversion with AI: From Raw Preclinical Data to Regulatory-Ready Datasets
Nattawit Pewngam, Ravis technology
Chotika Chatgasem, Ravis Technology
Titipat Achakulvisut, Department of Biomedical Engineering, Mahidol University

AI-157. Tips and Considerations for Preparing Health Data for Efficient and Accurate AI and LLM Modelling
Louise Hadden, Independent Consultant

AI-164. Agentic R in Clinical Trials: Empowering Statistical Programmers with Open Source LLM Packages & Positron Tools
Phil Bowsher, RStudio Inc.

AI-185. From Molecular Subtypes to Bedside Decisions: An AI Approach for Personalized Critical Care Recommendations
Xi Jiang, SAS Institute
Scott McClain, SAS Institute

AI-201. Eliminating QC Programming Duplication Through Claude AI-Assisted Independent Code Generation: A Practical Framework for Regulatory-Compliant Validation
Jaime Yan, Kardigan Bio
Jason Zhang, 126 E Lincoln Ave

AI-206. An Agentic AI Framework That Reads Statistical Analysis Plans and Generates TFL Table of Contents
Siqi Wang, Arcsine Analytics
Toshio Kimura, Arcsine Analytics
Songgu Xie, Regeneron Pharmaceuticals
Weiming Du, Alnylam Pharmaceuticals

AI-240. DoxySAS: An End-to-End AI-Powered SAS Documentation Pipeline
Saikrishnareddy Yengannagari, BMS

AI-259. AI-Augmented SDTM Review: A Practical Framework Enhanced by a Structured Prompt Library
Vihar Patel, PPD, part of Thermo Fisher Scientific

AI-278. AI-Driven Intelligent Platforms for ADaM Specification and Code: Empowering Clinical Data Analysis
Tingting Zeng, BeOne Medicines (formerly BeiGene)
Jia He, BeOne Medicines
Yaohui Zhu, BeOne Medicines
Shuang Gao, Beone Medicine
Jinling Li, BeOneMed
Nana Yang, BeiGene

AI-305. Improving AI SAS-to-R Code Migration via an Intermediate Design Document Layer
Junze Zhang, Merck Co., Inc
Amy Zhang, Merck & Co.

AI-316. A Practical Roadmap for the 2026 Enterprise Generative AI Stack: AI Agent Architectures, Frameworks, and Secure Deployment
Ryan Lafler, Premier Analytics Consulting, LLC

AI-328. Leveraging LLMs in Data Science Web Applications: Beyond the Chat Interface
Tyler Rowsell, AstraZeneca
Nandini Thampi, AstraZeneca
Dishank Jani, AstraZeneca Inc.
Hao Xu, astrazeneca

AI-332. A Human-in-the-Loop AI-Assisted Framework for ADaM Standardization
Chunqiu Xia, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Feiyang Du, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

AI-339. Automating Table Generation in Real-World Data Programming: An AI-Assisted Approach
Sachin Heerah, Pfizer
Darren Jeng, Pfizer

AI-344. Protocol Analysis, Optimisation and Generation: Artificial Intelligence Enables a Unified View
Sundaresh Sankaran, SAS Institute
Sherrine Eid, SAS Institute

AI-345. Beyond Today’s Evidence: How AI-Enabled RWE Will Transform Development Speed, Study Quality, and Real-World Impact
Sherrine Eid, SAS Institute

AI-352. Practical Lessons in AI-Assisted Metadata Conversion: From Database Specs to EDC and SDTM — Successes, Pitfalls, and Practical Implementation
Jianlin Li, Evermedix
Andy Shen, SJ Biopharm Solutions

AI-362. Using Large Language Models to Validate TLF Outputs Against Statistical Review Comments: An End-to-End Python Framework
Kishore Reddy Rollakanti, Cytel Inc

AI-420. A specification-driven approach to improve the reliability of AI-generated SDTM transformation programs
Rostislav Markov, Amazon

AI-431. AI-Powered Multiple-Agent Pipeline for Automating ADaM Dataset Generation
Lucas Liu, Yesod AI, Inc
Bo Ci, Yesod AI, Inc

AI-432. Evaluation of Azure OpenAI ChatGPT API as Code Assistance Tools for Statistical Programming in SAS, R and Python.
Ajay Gupta, Daiichi Sankyo
Misikir Tesfaye, Daiichi Sankyo Inc.

AI-438. Operationalizing Generative AI in Regulated Analytics: Applied Implementation Patterns for Enterprise Deployment
Lida Gharibvand, Loma Linda University

Career Development, Leadership & Soft Skills

LS-138. Perspectives on Leading Effectively in Platform Trials: Leadership and Technical Approaches
Zhen (Laura) Li, AstraZeneca

LS-149. Authentic Leadership for SAS Programming Leaders
Lisa Mendez, N/A

LS-173. From Programmer to Influencer: Strategic Leadership for Statistical Programmers in Clinical Development
Xiaohan Zou, BMS
Wei Shao, Bristol Myers Squibb
Yi Yan, Bristol Myers Squibb

LS-182. Soft Skills to Gain a Competitive Edge in the 21st Century Job Market
Kirk Lafler, sasNerd

LS-264. Drowning in Trackers? Let R Be Your Lifeboat!
Christine Reiff, Ephicacy Consulting Group, Inc.

LS-284. Early-Careers Essentials: Practical Checklists for Manual TLF Review
Ingrid Shu, Merck
Xinhui Zhang, Merck & Co. Inc

LS-319. Women Leadership in AI-Driven Clinical Programming: Navigating Intersectionality and Innovation
Lida Gharibvand, Loma Linda University

LS-347. Closing the Expectation Gap: A Leadership Framework for Clinical Programming Success
Yuka Tanaka-Chambers, Phastar

LS-393. AI-First Leadership in Biometrics: Redefining Strategy, Teams and Execution in the Agentic AI Era
Kevin Lee, Clinvia

LS-407. When Code Isn’t Enough: Communication and Leadership Skills for Statisticians and Programmers
John LaBore, SAS Institute
Josh Horstman, PharmaStat LLC
Robert Goodloe, Indiana University

LS-408. Navigating Career Transitions: From Programmer to Executive Leader
Steven Tan, Wu Consulting Group

LS-410. Delegation as a Quality Strategy: Building Accountable Biometrics Teams
Steven Tan, Wu Consulting Group

LS-411. Leading with Presence from Afar: Building Trust and Engagement in Distributed Biometrics Teams
Steven Tan, Wu Consulting Group

LS-424. From Statistical Programmer to Analytical Partner: Navigating the Future of Biostatistics
Shivani Gupta, Clymb Clinical

LS-441. Strategic AI Coaching for Life Sciences: A Framework for Industry Leaders and Managers
Priscilla Gathoni, Wakanyi Enterprises Inc.

LS-442. Effective Collaboration Between Business, Technical and Quality Units in Building GCP Systems
Ravi Tejeshwar Reddy Gaddameedi, Merck Inc
Tarek Ahammad, Merck & Co
Elizabeth Arnold, Merck Sharp & Dohme LLC

Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

DS-111. Ready for Next Level SDTMs and ADaMs Compliance with End-to-End Processing?
Sunil Gupta, Gupta Programming
Tomás Sabat Stofsel, Verisian

DS-131. CTCAE v6.0: The Good, the Bad, and the Ugly
Elizabeth Dennis, EMB Statistical Solutions, LLC
Grace Fawcett, Syneos Health

DS-134. Human Beings Still Needed: Manual ADaM Checks that AI Can’t Do
Sandra Minjoe, ICON PLC
Mario Widel, Independent

DS-144. Picking Up the Pieces: Implementation of (the forgotten) ADaM Naming Fragments
Richann Watson, DataRich Consulting
Karl Miller, IQVIA

DS-154. Navigating the Statistical Programming Strategies for Cytokine Release Syndrome (CRS) and ICANS in Oncology Clinical Trials.
Murali Kanakenahalli, Kite Pharma
Vamsi Kandimalla, Kite Pharma, A Gilead Company

DS-174. ISO 8601 and SAS®—and R! A Practical Approach
Derek Morgan, N/A
Marckenley Mercie, Bristol Myers Squibb

DS-196. Friction to Flow: LLM-Based Automation of Clinical Data Workflows
Pankaj Attri, SAS
Matt Becker, SAS

DS-265. SDTMIG v4.0: Are You Ready For It?
Kristin Kelly, Pinnacle 21 by Certara

DS-280. From Manual to Automated”: An SAS® and R-Based Toolkit for Scalable SDTM Generation
Hardik Sheth, Worldwide Clinical Trials
Eldho Alias, Worldwide Clinical Trials

DS-286. Approaches Integrating SAS LSAF and Pinnacle 21 Enterprise for SDTM/ADaM Dataset Validation
James Zhao, Eikon Therapeutics, Inc.
Joshua Lin, Eikon Therapeutics, Inc.

DS-341. DOSEON: Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (PROC SQL, SAS Macro, DATA Step, and PROC FCMP)
Inka Leprince, InkaStat Solutions, LLC
Troy Hughes, Data Llama Analytics

DS-350. Analysis Concepts role within the CDISC 360i vision
Alyssa Wittle, Atorus Research
Brian Harris, AstraZeneca

DS-354. SUPP to NSV: Transforming Data Representation for Improved Reviewer Utility
Soumya Rajesh, IQVIA

DS-360. Improving Risk-Based QA in Outsourced Studies Using Cross-Domain ADaM Derivation Comparisons
Pallavi Sadhab, AstraZeneca

DS-364. Two Approaches to Phase-Specific TRTEMFL in ADAE: A Neoadjuvant–Adjuvant Case with Surgery Between Phases
Youlan Shen, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Leah Suttner, Merck & Co., Inc.

DS-368. Beyond WHODrug: Insight into Concomitant Medication Data Analysis
Song Liu, Novo Nordisk
Martin Nielsen, Novo Nordisk
Rambabu Sura, Novo Nordisk

DS-372. Handling multiple screenings and multiple enrollments in SDTM: CDISC and FDA Guidance
Laura Williams, Alira Health
Andrea Gardani, Alira Health

DS-401. Why Standards Matter More Than Code in the Age of GenAI
Bhavin Busa, Clymb Clinical

DS-440. From Specification to SDTM at Speed: Deploying the SDTM Engine in Production
Lynn Xiuling Zhang, Merck & Co., Inc.
Jacques Lanoue Lanoue, Merck
Ulf Nielsen, MSD

Data Visualization & Interactive Analytics

DV-105. A Standardized R Graph Library for Production-Ready Analysis Figures
Chunting Zheng, Genentech
Margaret Huang, Vertex Pharmaceuticals, Inc.
Xindai Hu, Vertex Pharmaceuticals Inc

DV-120. Swimmer Plots – Some Practical Advice
Ilya Krivelevich, Eisai Inc.

DV-151. The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets
Louise Hadden, Independent Consultant

DV-155. A Map to Success with Data Visualization Using ODS Statistical Graphics
Richann Watson, DataRich Consulting
Louise Hadden, Independent Consultant

DV-165. Voice-driven Data Science: Real-Time Data Analysis with R
Phil Bowsher, RStudio Inc.

DV-181. Ten Rules for Better Charts, Figures and Visuals
Kirk Lafler, sasNerd

DV-188. Boston Breakthroughs: A Dashboard-Driven Approach to Metadata and Audit Trails with SAS Clinical Acceleration
Frances Gillespie, SAS Institute
Laura Watson, SAS Institute

DV-214. Introduction to Plotting with the PROCS Package
David Bosak, r-sassy.org

DV-229. Python for Survival Analysis: Kaplan-Meier and Reverse KM Plots Made Easy
Girish Kankipati, Pfizer Inc
Bala Rajesh Jakka, Pfizer

DV-232. AI-Recommended Color Palettes with QC for R Shiny Figures
Yi Guo, Pfizer Inc.

DV-294. Composite TLFs – A Combined Approach to Data Visualization
Jesse Pratt, PPD, part of Thermo Fisher Scientific
Rayce Wiggins, Thermo Fisher Scientific

DV-298. Dynamic Patient Profile Plot Development with SAS Graph Template Language
Raghava Pamulapati, Merck
Guowei Wu, Merck & Co., Inc.
Danfeng Fu, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

DV-304. Path to Consistent Clinical Graphics: An R Shiny Gallery
Michelle Harwood, Quantitative Sciences, Alexion, AstraZeneca Rare Disease
Austin Taylor, AstraZeneca RDU

DV-308. Designing a modular and interactive visualization tool for DMC
Chen Li, Boehringer Ingelheim
Hong Wang, Boehringer Ingelheim
Shu Chen, Boehringer Ingelheim
Xuan Jiang, Brown University

DV-314. From Exploratory Data Analysis to Machine Learning – Continuing My Python Journey
Leon Davoody, Student

DV-357. Three Ways to Over-Engineer Your SAS Custom Steps
Mary Dolegowski, SAS
Robert Collins, SAS Institute

DV-371. Interactive Safety Data Visualization Platform: Transforming Adverse Event Analysis Review Through Dynamic Dashboards in Clinical Trials
Nishanth Chinthala, Astrazeneca Pharmaceuticals
Alexandr Hromcenco, AstraZeneca

DV-382. From Static to Dynamic: Leveraging R Shiny for Tumor Response Data Review
Reneta Hermiz, Pfizer Inc.
Jing Ji, Pfizer Inc
Amrit Pradhan, Pfizer Inc.
Martin Sandel, Pfizer Inc.

DV-383. Closing the Loop: An Interactive R Shiny Dashboard for EDC Data Visualization and Real-Time Review Tracking
Jun Yang, Organon LLC
Yuying Jin, Organon

DV-409. Be a Multi-Media Wizard: Make Your Output Dance and Sing
LeRoy Bessler, Bessler Consulting and Research

DV-419. From Word Clouds to Phrase Clouds to Amaze Clouds: A Data-Driven Python Programming Solution To Building Configurable Taxonomies That Standardize, Categorize, and Visualize Phrase Frequency
Troy Hughes, Data Llama Analytics

DV-434. The Best Data Dashboard Alternative: More Efficient But Equally Effective Performance Monitoring and Reporting
LeRoy Bessler, Bessler Consulting and Research

DV-443. From Static Outputs to Living the Data – A Visualization framework transforming Clinical Data into a Continuous Asset
Neharika Sharma, GlaxoSmithKline Pharmaceuticals

Emerging Technologies (R, Python, GitHub etc.)

ET-140. Unleash the R-volution: A Blueprint for Building Package Validation Capabilities in our own organization
Kevin Lee, Clinvia

ET-162. Accelerating Open-Source AI with AWS Bedrock: Architecting LLM Integration with Posit Workbench & Positron
Phil Bowsher, RStudio Inc.

ET-163. Current Review of Open Source in New Drug Applications: R & Python
Phil Bowsher, RStudio Inc.

ET-178. Easy Code Generation in R: The “macro” package
David Bosak, r-sassy.org

ET-179. Building ADaM Datasets from Scratch using R: A SAS programmer’s Perspective
Patel Mukesh, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Nilesh Patel, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

ET-189. Breaking the Shell: Validated R Workflows To Meet FDA Standards
Danielle Stephenson, Atorus Research
Audrey Chin, Atorus Research
Madeleine Penniston, Atorus Research

ET-192. Transitioning from SAS to R: Implementing Reproducible R Workflows for TLF Validation
Poornima Alavandi, Pfizer

ET-195. Creating Reproducible Clinical Output with SASSY- Reporter Package
Vicky Yuan, Incyte Coperation

ET-197. Automated Delta Detection: A Scalable R-Shiny Framework for Comparing Clinical Datasets
Prabhakara Rao Burma, Ephicacy Consulting Group Inc.
Latha Donapati, Ephicacy Consulting group

ET-205. The Open Source Advantage: Powering Innovation in the 21st Century
Kirk Lafler, sasNerd
Ryan Lafler, Premier Analytics Consulting, LLC
Joshua Cook, University of West Florida (UWF)
Stephen Sloan, Dawson D R
Anna Wade, Emanate Biostats

ET-207. Enhancing Your SAS Viya Workflows with Python: Integrating Python’s Open-Source Libraries with SAS using PROC PYTHON
Ryan Lafler, Premier Analytics Consulting, LLC
Miguel Bravo Martinez del Valle, Premier Analytics LLC

ET-212. A Novel Approach to Inter-Collaboration using IDEs and GitHub
Sydney Hyde, Bristol Myers Squibb
Tamara Martin, Bristol Myers Squibb

ET-215. Reproducing the SAS DATE and TIME formats with {fmtr} package in R
Chen Ling, AbbVie
David Bosak, r-sassy.org

ET-218. Regression Analysis Made Easy Using R
Zheyuan Yu, Walter
Kirk Lafler, sasNerd
Zichun Gao, Stevens Institute of Technology
Jiaxin Xu, Franklin and Marshall College
Zeqi Li, Columbia University
Ruochen Shao, High School Student

ET-223. The Evolution of Open-Source Technologies in the Pharmaceutical Industry: Python as a Cost-Effective Solution for Clinical Statistical Programming
Ramesh Potluri, Servier Pharmaceutical

ET-252. Reviewing and identifying issues in TFL macro parameter values with R shiny tool
Mydhili Chelikani, Merck & Co., Inc.
Ajay Kumar Tirkey, Merck & Co., Inc.

ET-279. Goodbye SAS, Hello R: Practical Workflows for CDISC Standards
Madeleine Penniston, Atorus Research
Alyssa Wittle, Atorus Research

ET-283. An Innovative solution for Interactive Dashboards Using Python Flask Framework for Clinical Data Analytics
Manish Bhagchandani, Ephicacy Lifescience Analytics Pvt Ltd

ET-285. mkheader: An R Package for Automated Generation and Management of Program Headers in Clinical Trial Programming
Gabriela Piasecki, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Laura Frederick, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

ET-292. Engineering secure and reproducible R based clinical programming systems using open source DevSecOps practices.
Indraneel Chakraborty, Ephicacy Lifescience Analytics Pvt Ltd

ET-296. Building for the Long Haul: Managing Scope, Refactoring, and CI/CD in Internal R Packages
Huijun An, Fred Hutchinson Cancer Center
Blazej Neradilek, SCHARP at Fred Hutch
Chenchen Yu, Fred Hutch Cancer Center
Shannon Grant, SCHARP at Fred Hutch

ET-300. Modern Data Science with SAS Viya Workbench: Unified Development with SAS, Python, and R
Shelby Taylor, SAS Institute

ET-301. R-Based Translation of Japanese Characters in Clinical Datasets for Regulatory Reporting
Hardik Sheth, Worldwide Clinical Trials
Roshan Stanly, Genpro Research Inc.

ET-327. Building Better Data Science Workflows: Best Practices with Git, GitHub, and Data Version Control (DVC) for Effective Collaboration
Ryan Lafler, Premier Analytics Consulting, LLC

ET-358. Automating Git Workflows in SAS with Git Functions
Lleyton Seymour, SAS

ET-370. Challenges for small-mid size organization to build a GxP Compliant R Environment (CRE)
Peng Zhang, CIMS Global
Tai Xie, CIMS Global
Peilin Zhou, CIMS Global
Christine Matakovich, CIMS – Gobal.com

ET-374. A Governed Git Workflow Using Azure Repos for GxP Compliant Statistical Programming
Jing Yu, Novo Nordisk

ET-378. AI-Enhanced R Shiny App for Real-Time Clinical TLF Coding and Preview
Dickson Wanjau, Merck & Co., Inc.

ET-381. Bridging the Gap A Python-Word Integration for Detecting Ghost Page Breaks in SAS-Generated RTFs
Jun Yang, Organon LLC
Robert Stemplinger, Organon

ET-390. A Practical Roadmap for Modernizing Legacy Clinical Applications
David Ward, Triam Ltd

ET-397. Trusting Your R Packages: A Practical, Risk-Based Approach to External Package Validation
Radhika Etikala, Statistical Center for HIV/AIDS Research and Prevention (SCHARP) at Fred Hutch
Valeria Duran, Statistical Center for HIV/AIDS Research and Prevention at Fred Hutch

ET-399. Chatting with Your Data, Wherever It Lives: Unlock Insights through Duck DB and Open File Formats
Sundaresh Sankaran, SAS Institute
Mary Dolegowski, SAS

ET-412. An Experience Using R, SASSY and Tidyverse For Clinical Trial Analysis, From A SAS Programmer Perspective
David Franklin, TheProgrammersCabin.com

ET-416. It’s a Wonderful Lifecycle: Translating Statistical Programming into Modern Analytics Development
Steve Nicholas, Atorus Research

ePosters

PO-007. DefinePageChecker: A Python Tool for Verifying Page Number Hyperlinks in Define.xml
Xianhua Zeng, Taimei Intelligence Pharmaceutical

PO-009. Word2PDF: A Python Tool for Converting and Merging Word or PDF Files into a Single PDF
Xianhua Zeng, Taimei Intelligence Pharmaceutical

PO-117. From Learner to Innovator: A Journey in R Empowered by AI to Enhance Narrative Review in Clinical Studies
Shih-Che (Danny) Hsu, Pfizer

PO-122. Implementation of Quality Tolerance Limits in Statistical Programming
Yang Gao, Pfizer Inc.

PO-143. Consolidation of CDISC ADaM
Cindy Stroupe-Davis, Data Dynamo
Trevor Mankus, Pinnacle 21
Tatiana Sotingco, J & J Inovative Medicine
Alyssa Wittle, Atorus Research

PO-187. An Alternative Option to Create XPT Files with a SAS Function
Jose Hernandez Rivero, Principal Statistical Programmer
Ruth Rivera Barragan, Ephicacy Consulting Group

PO-194. Managing Unblinded Activities Internally: The Independent Statistical Analysis Team (iSAT) Model
Hong Wang, Boehringer Ingelheim
Shu Chen, Boehringer Ingelheim
Chen Li, Boehringer Ingelheim

PO-213. %Compare_counts: A Macro for Speeding Up the QC Process When Proc Compare Slows it Down
Michael Garside, Phastar

PO-221. One Study, Many Regulators: Submission-Ready Data Package for Multi-Region Filings
Himanshu Patel, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Chintan Pandya, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

PO-230. Automating Character Variable Length Updates Using SAS Macros
Carleigh Crabtree, SAS

PO-244. Dynamic table generation for ongoing studies with unstable or changing cohorts
Haoran Li, ClinChoice
Junruo Xia, ClinChoice Canada Inc.
Yixuan Zhang, Clinchoice,LLC

PO-270. SAS viya dynamic visualization of data
Jumin Geng, Teva Pharmaceutical Industries, Ltd

PO-287. Maintaining a Multi-Lingual Code Inventory in Real-World Evidence
Joshna reddy Nimmala, Merck & Co., Inc., Rahway, NJ, USA and its affiliates
Yu Feng, Merck & Co., Inc., Rahway, NJ, USA and its affiliates

PO-331. Hero-in-the-Loop: A Super Squad Approach to SDTM Creation & Validation
Julie Ann Hood, Pinnacle 21 by Certara

PO-377. Pharmacometric Analysis Dataset Generation Process: Data, Roles & Tools from a programmers Perspective
Srinivas Bachina, Astrazeneca
Dheeraj Rupani, AstraZeneca PLC
Hasi Mondal, AstraZeneca
Kiran Kumar Kode, AstraZeneca

PO-386. Case Study: Integrating ADPPK CDISC Standards into Pharmacometric Programming and Analysis Workflows
Praseeda Rajan, Bristol Myers Squibb
Renuka Hegde, Bristol Myers squibb
Erin Dombrowsky, Bristol Myers Squibb
Neelima Thanneer, Bristol-Myers Squibb
Yue Zhao, Bristol Myers Squibb

PO-392. Running Python from SAS: A Practical Comparison of Available Approaches
David Ward, Triam Ltd

PO-395. Implementing AI Agent-Driven Tools to Accelerate Clinical Research Workflows
Nathan Lee, Clinvia

PO-406. Smarter, Faster, Better: GenAI‑Driven Authoring for Data Reviewer’s Guides
Christina Scienski, Pfizer
Christine Rossin, Pfizer

PO-415. Traceability in Real World trials- just an aERD away.
Ashwini Yermal Shanbhogue, None

PO-433. Enhancing CDISC Standards Implementation (SDTM and ADaM) with PROC FCMP, PROC IML and Macro Loop Integration in Oncology Clinical Trials.
Ajay Gupta, Daiichi Sankyo
Misikir Tesfaye, Daiichi Sankyo Inc.

Hands-On Training

HT-369. “Virtual Data, Real Standards – Leveraging Data Simulation for Smarter Clinical Trials”
Sangeeta Shabadi, Jazz pharmaceuticals
Nitesh Patil, Cytel Inc
Jonathan Henshaw, Jazz Pharmaceuticals

HT-447. Following Your Footsteps: Maintaining Traceability in ADaM Datasets
Nancy Brucken, IQVIA
Karl Miller, IQVIA

HT-448. SAS Macro Debugging Techniques for Mere Mortals
Kirk Lafler, sasNerd

HT-449. SAS Performance Tuning Techniques (From Slow to Scalable)
Kirk Lafler, sasNerd

HT-450. Getting Started with R Clinical Programming
Brian Varney, Experis

HT-451. Accelerating Code Translation and Generation with ChatGPT
Brian Varney, Experis
David Bosak, r-sassy.org

HT-452. Vibe Coding: Coding with Agentic AI ( Hands-On Tutorial)
Kevin Lee, Clinvia
Nathan Lee, Clinvia

HT-453. Understanding Administrative Healthcare Datasets using SAS programming tools.
Jayanth Iyengar, Data Systems Consultants LLC

HT-454. SQL – The Grammar behind A.I.
Charu Shankar, SAS Institute

HT-466. Introduction to Positron & AI Tooling in Clinical Reporting
Phil Bowsher, RStudio Inc.

PK/PD/ADA and Quantitative Pharmacology

PK-216. Early Unblinding to Pharmacometrics (PMx) Data: Challenges, Practices, and Benefits
Shweta Vadhavkar, Genentech-Roche
Jing Su, Merck & Co., Inc

PK-234. Visualizing PK and ADA Data at Scale: A Parameter-Driven SAS Macro for Box Plot Generation
Prasannanjaneyulu Narisetty, Prasannanjaneyulu Narisetty
Anilkumar Anksapur, Merck & Co., Inc., Rahway, NJ, USA

PK-250. Navigating Early Career Challenges in PK/ADA Statistical Programming
Diyu Yang, Merck
Sandeep Meesala, Merck & Co. Inc

PK-272. An End-to-End R-Based Pharmacokinetics (PK) Workflow for Regulatory Submission: The INAVO120 Study
Qi Liu, Genentech
Shweta Vadhavkar, Genentech-Roche

PK-276. SAS and R for Expanding Data for Pharmacometrics Analysis (PMx) Analysis Data Sets
Jeffrey Rathbun, Simulations Plus
Rebecca Humphrey, Simulations Plus, Inc.

PK-282. From Chaos to Clarity: A Programmer’s Perspective on Standardizing Population Pharmacokinetic (PopPK) Data for Regulatory Success
Naveen Muppalla, Exelixis, Inc
Shibani Harite, Exelixis Inc.

PK-310. Enhancing ADaM PK Datasets to Automate PK TFLs Generation
Jianli Ping, Gilead Sciences Inc
Karthik Sankepelli, Gilead

PK-334. Two Paths, One PK Journey: The Art of Balancing ADPC and ADNCA
Ashok Abburi, Exelixis, Inc.
Rakhe Jacob, Exelixis
Shibani Harite, Exelixis Inc.

PK-361. Early Restricted Unblinded PK Data Access (ERUPA): Framework to Accelerate PopPK and ERES Deliverables Through Data-Centric, Firewalled Workflows
Dheeraj Rupani, AstraZeneca PLC
Srinivas Bachina, Astrazeneca
Kiran Kumar Kode, AstraZeneca

PK-387. A systematic approach for imputing missing dose information in population pharmacokinetic analysis datasets
Prema Sukumar, Bristol Myers Squibb
Renuka Hegde, Bristol Myers squibb
Erin Dombrowsky, Bristol Myers Squibb
Neelima Thanneer, Bristol-Myers Squibb

Real-World Data (RWD) and Real-World Evidence (RWE)

RW-126. Streamlining Workflows in Real-World Evidence Studies with an R-Based Automation Tool
Lihai Song, Merck & Co.

RW-186. Corticosteroids in severe COVID-19 across molecular endotypes and vaccination status: an Emulated Target Trial approach to benchmark to and extend upon findings from RECOVERY
Xi Jiang, SAS Institute
Scott McClain, SAS Institute

RW-210. dbLoadTable: A Robust and Efficient Solution for Bulk Data Transfer in Real-World Evidence Analytics
Li Liu, Merck & Co., Inc.

RW-248. Real World Data and CDISC – An Evolving Journey
Shuo Cao, Ephicacy
Venkat Rajagopal, Ephicacy Consulting Group

RW-253. Embracing Novel Approaches to Automated Causal Inference Framework
Laura Watson, SAS Institute
Sherrine Eid, SAS Institute

RW-343. From Automation to Evidence: Governing LLMs and AI Agents in Real-World Outcomes Research
Sherrine Eid, SAS Institute

RW-367. PSMATCH: Propensity Score Matching of Clinical Trial Data with External Control Arms
Ginger Barlow, Prilenia Therapeutics

RW-379. Contrast Effects in Curated Observational Data
Shankar Srinivasan, Bayer
Helen Guo, Bayer
Yvonne Buttkewitz, Evidenze Germany GmbH

RW-384. Assessing Quality of Real-World Data Sources
Robert Collins, SAS Institute

RW-429. Biostatistical Foundations 201: Privacy Preserving Patient Linkage Across Real World Data Sources
Anbu Damodaran, Alexion, AstraZeneca Rare Disease

RW-435. Operationalizing Real World Data for External Control Arms: An End to End Framework for Rare Disease and Oncology Trials
Anbu Damodaran, Alexion, AstraZeneca Rare Disease

Study Data Integration & Analysis

SI-109. Insights and Experience Sharing with Patient-Reported Outcome Data Analysis in FDA’s Submission
Jingyuan Chen, Genentech

SI-227. A Statistical Programmer’s Guide to Tipping Point Analysis in SAS
Ang Xu, Boehringer-ingelheim

SI-293. From Data to Dossier: Lessons from Cross-Company Regulatory Submissions
Nikita Joseph, AstraZeneca
Gayathri Mahadevan, Daiichi Sankyo, Inc

SI-306. An Approach for Generating Tumor Biopsy Datasets for Drug Development
Ryan Hernandez-Cancela, Merck & Co., Inc., Rahway, NJ, USA
Jeff Cheng, Merck & Co., Inc.
Sandeep Meesala, Merck & Co. Inc

SI-348. Algorithms to align the distribution of follow-up across independently collected cohorts when comparing time to event endpoints using conventional Kaplan Meier and Cox regression methods.
Shankar Srinivasan, Bayer
Yvonne Buttkewitz, Evidenze Germany GmbH
Regina Uttenreuther, Evidenze Germany GmbH
Baldeep Chani Talwar, Syneos Health
Manjari Dissanayake, Bayer Corporation

SI-373. From Chaos to Consistency: Standardizing External Clinical Data with Excel Power Query
Isaac Vazquez, Ephicacy Consulting Group
Jose Hernandez Rivero, Principal Statistical Programmer

SI-414. Harmonizing History: A Framework for Deriving Line of Therapy in Complex Integrated Summaries.
Bhargav Koduru, Medidata Solutions
Kavitha Guddam, Dassault systemes
Santosh Reddy Lekkala, Medidata Inc

Submission Standards for Global Health Authorities

SS-114. Statistical Programmer’s role in using Lorenz eValidator to validate contributions to eCTD
Sampath Madanu, astrazeneca

SS-193. Structure for Success: Delivering a Complex, Accelerated NDA with Evolving Scope
Tingting Tian, Merck
Chao Su, Merck
Erica Davis, Merck

SS-209. Lessons to Guardrails: Operationalizing Early Checks for FDA Submission Readiness
Jeff Xia, Merck & Co.

SS-243. Efficiency in Action: Automating Bookmarking for CRFs and Other Regulatory Submission Documents
Srivathsa Ravikiran, Agios Pharmaceuticals
Sri raghunadh Kakani, Agios Pharmaceuticals
Yang Xu, Agios Pharmaceuticals

SS-254. A Practical Approach to Multiple-Period CLINSITE Preparation
Liyuan Huang, Alnylam Pharmaceuticals, Inc.
Amanda Plaisted, Alnylam Pharmaceuticals
Sreedhar Bodepudi, Alnylam

SS-255. Investigator-Initiated Trials: Navigating Statistical Programming Challenges with Practical Solutions
Vikas Patil, Servier Pharmaceuticals
Ramesh Sundaram, Servier

SS-261. Closing the Loop: Validating AI-Generated SDTM Mappings using CDISC CORE and Synthetic Data
Pietro Belligoli, Technical University of Munich (TUM)
Constantin Weberpals, TUM
Yarhy Flores Lopez, Technical University of Munich

SS-268. Post-DBL Programming Update Tracker: Automating Revision Capture to Strengthen Audit Readiness, Oversight, and Compliance Across Programs and ADaM Specifications
Yunyi Jiang, Merck & Co., Inc., Rahway, NJ, USA
Christine Teng, Merck

SS-277. Optimizing Clinical TFL Review with Python and Power BI: A Reproducible Workflow to Reduce QC Time and Improve Traceability
Vijaya Lakshmi Cherakam, Ephicacy Consulting Group
Latha Donapati, Ephicacy Consulting group

SS-307. From Data Flood to Insight: Efficient SDTM Validation for High-Frequency Sources
Seiko Yamazaki, Certara

Tools, Tech & Innovation

TT-102. Sync & Scale: Empowering Cloud Hub & Team Synergy with SAS Bridge
Mayank Singh, Johnson and Johnson MedTech (Neurovascular)

TT-106. Automating Bioresearch Monitoring (BIMO) Listings Using R
Weishan Song, Vertex Pharmaceuticals
Wanting Jin, University of North Carolina at Chapel Hill
Weiyu Zhou, Vertex Pharmaceutical
Margaret Huang, Vertex Pharmaceuticals, Inc.

TT-118. Automated Quality Checks for SDTM and ADaM Datasets Using R Shiny
Shih-Che (Danny) Hsu, Pfizer
Wei Qian, Pfizer, Inc

TT-121. R Package Management in LSAF: Challenges and Solutions
Praneeth Adidela, ICON plc
Sagar Koona, ACL Digital inc

TT-130. My DIY Swiss Army Knife of SAS® Procedures: A Macro Approach of Forging with My Favorite PROCs
Jason Su, Daiichi Sankyo, Inc.

TT-132. A fully automated PDF solution using SAS without third-party PDF tools
Zhongan Chen, Pfizer

TT-139. From ChatGPT to Copilot: Evolving AI Support in SAS and Beyond
Jyoti (Jo) Agarwal, Gilead Sciences

TT-147. Bridging the Gap: Table-Driven SAS Programming as a Pathway to AI in Clinical Trials Statistical Programming
James Sun, Constat System
Vijaya Nadella, Rocket Pharmaceuticals
Daniel Qi, Rutgers University

TT-152. aCRF In Full: A Complete Solution for Relatively Little Work
Carlo Radovsky, Immanant

TT-156. SAS to R: A Practical Bridge for Programmers
Jyoti (Jo) Agarwal, Gilead Sciences

TT-175. Enhancing Quality and Efficiency in Clinical Programming with a Python-Based Automated File Comparison Tool
Ratheesh Gunda, Kite Pharma, a Gilead company

TT-204. From SAS Servers to AI Agentic SCEs: Integrating Agentic AI into GxP-Compliant Biometrics Workflows
Kevin Lee, Clinvia

TT-241. TOON Format: A Token-Efficient Data Exchange Solution for AI-Enhanced Clinical Programming
Saikrishnareddy Yengannagari, BMS

TT-263. Boolean Rhapsody: 50 shades of true Is this the real code? Is this just fantasy?
Charu Shankar, SAS Institute

TT-275. SAS for Microsoft 365: Integrating SAS Programs, Data, and Reports Across the Microsoft 365 Ecosystem
Shelby Taylor, SAS Institute

TT-309. Global Macro for Master Tracker
Zhuo Chen, BridgeBio Pharma
Ted Lystig, BridgeBio
Xiaofan Cao, BridgeBio
Tuan Nguyen, BridgeBio Pharma

TT-312. Trust but Verify: How ChatGPT and SAS Can Be Comrades!
Steve Black, Neurocrine Biosciences

TT-391. Taming Polyglot Analytics: Simplifying Cross-Language Workflows in a Unified IDE
David Ward, Triam Ltd
Troy Wolfe, Triam

TT-394. Structure-Preserving Preprocessing of Clinical Documents for Large Language Model Analysis
Zun Wang, R&G US Inc
Juntao Yan, Eli Lilly and Company

TT-403. From SAP to CSR: A Metadata-Driven TFL Workflow
Bhavin Busa, Clymb Clinical

TT-417. A Fantasy in Three with PROC FCMP: Memoization of Resource-Intensive Calculations, in-Memory Hash-Object Storage and Retrieval Operations, and Disk-Based Persistent Data Set Modification and Preservation
Troy Hughes, Data Llama Analytics

TT-439. From Suspicion to Evidence: Automating Character Truncation Risk Audits with a Parameterized SAS Macro and Review-Ready Excel Output
Xinran Hu, Merck