San Diego, California
June 1-4, 2025
Advanced Programming
AP-002. Worried about that Second Date with ISO®? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates
Richann Watson, DataRich Consulting
AP-006. Calculating the Physical Length of a PDF File String with ‘Times New Roman’ Font by SAS
Yueming Wu, Astex Pharmaceuticals
Steven Li, Medtronic PLC.
AP-033. Four roads lead to Outputting Datasets Dynamically (ODDy) & Beyond
Jason Su, Daiichi Sankyo, Inc.
AP-035. Develop a SAS® Macro for Dataset/Program Timestamp Version Control
Chen Wang, Merck
AP-037. Listing Shell To Sas Program Automation Tool
Balaji Ayyappan, ICON PLC
Johnny Tai, Kite Pharma, Inc
AP-039. How Not to SAS: Avoiding Common Pitfalls and Bad Habits
Melodie Rush, SAS
AP-053. Implementing Data Checks for Patient Registries — A Modular Approach
*** BEST PAPER ***
John Gerlach, Navitas Life Sciences
Elizabeth Loisel, Sanofi
AP-059. Validate the Code, not just the data: A system for SAS program validation
Jayanth Iyengar, Data Systems Consultants LLC
AP-078. Writing SAS MACROs in R? R functions can help!
Chen Ling, AbbVie
Yachen Wang, AbbVie
AP-081. Efficiency Techniques in SAS® 9.
Stephen Sloan, Dawson D R
AP-097. Better, Faster, Stronger: A Case Study in Updating SAS Macro Code with Run-time Optimization in Mind
Valerie Finnemeyer, Harvard TH Chan School of Public Health
AP-121. SET Statement Considered Harmful
Bart Jablonski, yabwon
AP-141. A New Gateway to Open Source in SAS Viya
Jim Box, SAS Institute
Mary Dolegowski, SAS
AP-151. Sugar Rush: SQL Master Class for Pharma Professionals
*** BEST PAPER ***
Charu Shankar, SAS Institute
AP-157. Macro to Compare ADaM Spec Derivations Against Available SDTM Data
Ingrid Shu, Merck
Kexin Guan, Merck & Co., Inc.
Jeff Xia, Merck
AP-161. Get Tipsy with Debugging Tips for SAS® Code: The After Party
Lisa Mendez, Army MEDCOM
Richann Watson, DataRich Consulting
AP-162. Mining Data from PDF Files Using SAS
Michael Stout, Johnson & Johnson Medical Device Companies
Brian Knepple, J&J MedTech Orthopadics
AP-192. A Macro to Automatically Check SAS Logs for Common Issues
Hailin Yu, Clinical Outcomes Solutions
AP-211. You’ve Got Options: Five-Star SAS® System Option Hacks
Louise Hadden, Cormac Corporation
AP-213. Programmatic Annotation of Case Report Forms
Matthew Finnemeyer, Vertex Pharmaceuticals Inc.
AP-217. Automating SAS Program Header Updates with Macros
*** BEST PAPER ***
Kexin Guan, Merck & Co., Inc.
AP-226. Advanced ODS Excel Tricks: Password Protected Workbooks and Clickable Navigation
Jeffrey Meyers, Regeneron Pharmaceuticals
AP-238. When PROC SORT Isn’t Enough: Implementing Horizontal Sorting in SAS
Krutika Parvatikar, Merck & Co, Inc.
Jeff Xia, Merck
AP-263. Why SASSY?
David Bosak, r-sassy.org
AP-312. How Not to Drown in Code When Pooling Data
Scott Burroughs, Orbis Clinical
AP-347. Last Observation Carried Forward (LOCF) in Longitudinal Patient Studies: A Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS® Function Compiler
Troy Hughes, Data Llama Analytics
AP-367. SAS Macro to Calculate Standardized Mean Difference
Tong Zhao, LLX Solutions, LLC
Tian Gu, LLX Solutions, LLC
Artificial Intelligence and Machine Learning
AI-136. AI-Assisted Transition: from SAS to RStudio for PK Summary Analysis
Shiqi Lin, Merck & Co., Inc., Rahway, NJ, USA
AI-137. Traceability and AI for Improved Understanding, Communication and QC of Clinical Trials
Tomás Sabat Stofsel, Verisian
AI-194. Visualize High Dimension Data Using t-SNE
Jun Yang, Avidity Bioscience
AI-209. Integrating Generative AI into Medical Writing: Building an Interactive Drafting and Search Framework
Tadashi Matsuno, Shionogi & Co., Ltd.
AI-214. Generating Synthetic Clinical Trial Data with AI: Methods, Challenges, and Insights
*** BEST PAPER ***
Max Ma, Everest Clinical Research Corporation
Weijie Yang, Everest Clinical Research Inc.
Emily Ma, University of Toronto
AI-239. Gen AI Assisted Code Conversion: From SAS to R Standard ADaM Templates
Jeff Cheng, Merck & Co., Inc.
Srinivas Malipeddi, Merck & Co., Inc.
Gurubaran Veeravel, Merck & Co., Inc.
Jaime Yan, Merck
Suhas Sanjee, Merck
AI-240. Automation of Trial Design Domains generation using AI
Prasoon Sangwan, TCS
AI-242. Translation from SAS® to R Using ChatGPT®
David Bosak, r-sassy.org
Brian Varney, Experis
AI-246. Incorporating LLMs into SAS Workflows
Samiul Haque, SAS Institute
Sundaresh Sankaran, SAS Institute
AI-286. Get Started with ChatGPT and DeepSeek in SAS
James Austrow, Cleveland Clinic
AI-299. Leveraging Gen AI (ChatGPT, Gemini) API for Advanced Biometric Analysis in SAS, Python and R
Kevin Lee, Clinvia
AI-324. Code Smarter, Not Harder: The 5 C’s of ChatGPT for the SASsy Professional
Charu Shankar, SAS Institute
Kirk Lafler, sasNerd
AI-331. Streamlining and Accelerating Clinical Research through AI and GenAI driven Insights and safety review of Medical and Scientific Literature
Rohit Kadam, Mr.
Saurabh Das, Tata Consultancy Services
Rajasekhar Gadde, Tata Consultancy Services
Niketan Panchal, Mr.
Alejandra Guerchicoff, Phd
AI-345. Productive Safety Signal Detection and Analysis using In-context Learning
Sundaresh Sankaran, SAS Institute
Samiul Haque, SAS Institute
Sherrine Eid, SAS Institute
AI-349. Harnessing AI & CDISC ARS for Effortless Statistical Reporting & CSR Writing
Bhavin Busa, Clymb Clinical
Navin Dedhia, Clymb Clinical
AI-356. Application of advanced GenAI tools in sample size estimation – questions and thoughts
Igor Goldfarb, Accenture
Ella Zelichonok, Naxion
AI-362. AI-Powered Data Issue Tracker for Efficient Data Issue Tracking and Resolution
Bharath Donthi, Statistics & Data Corporation
Data Standards
DS-028. Name That ADaM Dataset Structure
Nancy Brucken, IQVIA
DS-063. The Winding Road to ADSL
Elizabeth Dennis, EMB Statistical Solutions, LLC
Grace Fawcett, Syneos Health
DS-065. Which ADaM Data Structure Is Most Appropriate? Gray Areas in BDS and OCCDS.
Veronica Gonzalez, Biogen Inc
DS-067. Multiple Imputation Techniques in the Context of ADaM Datasets
Shunbing Zhao, Merck & Co.
Linping Li, Merck & Co.
DS-075. Controlling attributes of .xpt files generated by R
Yachen Wang, AbbVie
Chen Ling, AbbVie
DS-079. BDS Dataset with PARQUAL and PARQTYP Variables for Time-to-Safety Events Analysis
Kang Xie, AbbVie
DS-103. Time-to-Deterioration for Patients Reported Outcomes
Christine Teng, Merck
DS-105. ADaM Pet Peeves: Things Programmers Do That Make Us Crazy
Sandra Minjoe, ICON PLC
Nancy Brucken, IQVIA
DS-109. Impact of Drug Accountability on Drug Compliance and Dose Intensity in Clinical Trials
Vishal Gandhi, Merck & Co.
Milan Adesara, Merck & Co.
DS-123. Decoding Laboratory Toxicity Grading: Unlocking the Potential and Overcoming Challenges of CTCAE
Xiaoting Wu, Vertex Pharmaceuticals
Lei Zhao, Vertex Pharmaceuticals
DS-126. ADaM Fundamental Principles vs. Rules: Which to Follow, When, and Why?
Sandra Minjoe, ICON PLC
Mario Widel, IQVIA
DS-169. A discussion of the new ADaM guidance (ADNCA and ADPPK) for pharmacokinetics.
Luke Reinbolt, Navitas Data Sciences
DS-256. What comes first, the chicken (ADSL) or the egg (ADNCA)? Modularize your covariate creation to support flexible analysis dataset implementation!
David Izard, Merck
DS-316. Cytokine Release Syndrome (CRS) – Data Collection, Clinical Database Integration and Analyses in a Dose Escalation Cell Therapy Trial
*** BEST PAPER ***
Cyrille Correia, PPD
Venky Chakravarthy, Takeda
DS-336. Creating JSON Transport Data for Regulatory Life Sciences
Mary Dolegowski, SAS
Matt Becker, SAS
DS-338. Efficient CDISC Controlled Terminology Mapping: An R-Based Automation Solution
Yunsheng Wang, ClinChoice
DS-346. Getting under the ‘umbrella’ of Specimen-based Findings Domains!
Soumya Rajesh, CSG Llc. – an IQVIA Business
Kapila Patel, IQVIA
Data Visualization and Reporting
DV-018. Visually Exploring Kaplan-Meier Curves Using SAS GTL and R survminer
Yang Gao, Pfizer Inc.
DV-029. Jazz Up Your Profile: Perfect Patient Profiles in SAS® using ODS Statistical Graphics
Josh Horstman, PharmaStat LLC
Richann Watson, DataRich Consulting
DV-034. A Case Study on Visualization Methods in R
Margaret Huang, Vertex Pharmaceuticals, Inc.
Chunting Zheng, Vertex Pharmaceuticals, Inc.
Lei Zhao, Vertex Pharmaceuticals, Inc
Todd Case, Vertex Pharmaceuticals, Inc
DV-071. Visualizing oncology data through 3D bar charts in R and Python
Girish Kankipati, Pfizer Inc
Venkatesulu Salla, Seagen
DV-148. Risk Mitigation Solution for Kaplan-Meier Plot in Drug Labeling
Bingjun Wang, Merck &Co.
Jane Liao, Merck & Co., Inc.
Suhas Sanjee, Merck
Jeff Xia, Merck
DV-150. Amazing Graph Series: Advanced SAS® Visualization to Wake Up Your Data – From Static to Fantastic
Tracy Sherman, Optimal Analysis Inc.
Aakar Shah, Acadia Pharmaceuticals Inc.
DV-158. Efficiently Creating Multiple Graphs on One Page utilizing SAS: Comparing PROC GREPLAY and ODS LAYOUT Approaches
Jenny Zhang, Merck & Co., Inc
DV-160. An Integrated R Shiny Solution for Dynamic Subgroup Adjustments and Customizations
Yi Guo, Pfizer Inc.
DV-188. Beyond Basic SG Procedures: Enhancing Visualizations in SAS Graphic
Vicky Yuan, Incyte Coperation
Fengying Miao, Incyte Coperation
DV-219. Zero to Hero: The Making of a Comprehensive R Shiny Figures App
*** BEST PAPER ***
Yi Guo, Pfizer Inc.
Matthew Salzano, Pfizer Inc.
Nicholas Sun, Pfizer Inc.
DV-222. Enhance Safety Data Analysis Using SafetyGraphic R Package
Vicky Yuan, Incyte Coperation
DV-244. Shining a Light on Adverse Event Monitoring with R Shiny
Abigail Zysk, PPD, part of Thermo Fisher Scientific
Joe Lorenz, PPD, part of Thermo Fisher Scientific
DV-251. Integrated R scripts to Power BI
Jun Yang, Avidity Bioscience
DV-268. A Customizable Framework in R for Presenting BICR Data in a User-Friendly Format
Reneta Hermiz, Pfizer, Inc.
Jing Ji, Pfizer, Inc.
DV-297. Swanky Sankey Enhancements: Transforming a Graph with Pretty Curves to a Research Tool uncovering Deeper Scientific Insights
Siqi Wang, Arcsine Analytics
Toshio Kimura, Arcsine Analytics
DV-335. Unleashing Oncology Revenue Insights: Advanced Forecasting Frameworks in Action
Naquan Ishman, SAS Institute
Dave Kestner, SAS Institute
DV-337. Combined Waterfall and Swimmer Plot using R for Visualization of Tumor Response Data
Akshata Salian, Ephicacy LifeScience Analytics Pvt Ltd
DV-357. Breaking Down Silos: Empowering Pharma Commercial Teams Through Integrated Data Insights
Hector Campos, DataPharma, LLC
Naquan Ishman, SAS Institute
Mike Turner, SAS
DV-381. Breaking Barriers in Clinical Trials: Insights into Platform Designs
Chetankumar Patel, GSK
DV-394. Clinical Data Explorer: Transforming Clinical Data into Actionable Insights
Karma Tarap, BMS
Oriana Esposito, BMS
Maheshkumar Umbarkar, Bristol Myers Squibb Hyderabad
Ramnath Dhadage, Ephicacy Life Science and Analytics
Tamara Martin, Bristol Myers Squibb
e-Posters
PO-052. ADaM implementation for Anti-drug Antibody Data
Jiannan Kang, Merck
Luke Reinbolt, Navitas Data Sciences
PO-062. A Macro to Automate Data Visualization using SAS Graph Template Language (GTL)
Ming Yang, Keros Therapeutics
PO-095. Understanding HIV: At-Risk Populations, Treatment, Prevention and Standardized Data Representation in HIV Studies
Jyoti (Jo) Agarwal, Gilead Sciences
PO-133. Checking SDTM Datasets from Biostatistical Perspective
Inka Leprince, PharmaStat, LLC
Elizabeth Li, PharmaStat, LLC
PO-140. Considerations of R submission in Japan
Yuichi Nakajima, GlaxoSmithKline K.K.
Yasutaka Moriguchi, GlaxoSmithKline K.K.
PO-172. In-house Data Monitoring Committee Report Programming
Lingjiao Qi, Alnylam
Amanda Plaisted, Alnylam Pharmaceuticals
Sreedhar Bodepudi, Alnylam Pharmaceuticals
PO-208. Our Second Brain: A Guide to Building Note System for SAS Programmer in Clinical Trial
Zeyu Li, Arrowhead Pharmaceuticals
PO-212. Embracing an Extra Step as the Ultimate Shortcut: Leveraging ADDATES for Enhanced Efficiency and Traceability in Oncology Studies
Chia-Lu Lee, AstraZeneca
Wanchian Chen, AstraZeneca
Anna Chen, AstraZeneca
PO-235. 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, Emergent BioSolutions, Inc.
PO-236. From Tides to Transformation: Making Waves with Your Move to Viya
Morgan Halleen, SAS
Tania Morado, SAS
PO-252. Methodology for AI-driven Outcome Prediction for Patients with Atrial Fibrillation After Transcatheter Aortic Valve Implantation (TAVI)
*** BEST PAPER ***
Felix Just, Daiichi Sankyo
Krishna Padmanabhan, Cytel
Parth Jinger, Cytel
Amanda Borrow, Daiichi Sankyo
Rüdiger Smolnik, Daiichi Sankyo
Eva-Maria Fronk, Daiichi Sankyo
PO-261. Avoiding the Ouch: Mastering Time to Pain Progression Analysis
Kavitha Boinapally, Pfizer
Sai Krishna Pavan Nakirikanti, Pfizer
Hank Dennis, Pfizer
Yang Wang, Pfizer
PO-271. Streamlining Your Workflow: Creating Portable and Automated SAS® Enterprise Guide Project Using Project Name
Chary Akmyradov, Arkansas Children’s Research Institute
PO-274. Automating Recurring Data Reconciliation for Serious Adverse Events Using SAS
Patrick Dowe, PROMETRIKA
Gina Hird, PROMETRIKA, LLC.
PO-311. Statistical Programming Outputs Comparison and Reporting Using Python
Vinayak Mane, Inference Inc.
Adel Solanki, Inference Inc.
Anindita Bhattacharjee, Inference Inc.
Tanusree Bhattacharyya, Inference Inc.
PO-350. A Novel ADEFF Design with Varying Baseline Type Selections
Tingting Tian, Merck
Chao Su, Merck
Fan Wang, MSD China, Beijing, China
Pengfei Zhu, MSD China, Beijing, China
PO-361. Efficient Strategies for Handling Data Issues in Clinical Trial Submissions
Kate Sun, Mirum Pharmaceuticals
PO-366. Slamming Datasets Together, Without Hurt, Using SAS, R and Excel
David Franklin, TheProgrammersCabin.com
PO-382. The World is Not Enough: Base SAS Visualizations and Geolocations
Louise Hadden, Cormac Corporation
PO-391. ExCITE-ing! Build Your Paper’s Reference Section Programmatically Using Lex Jansen’s Website and SAS
Louise Hadden, Cormac Corporation
PO-402. Association of Alzheimer’s Disease with Cardiovascular Disease and Depression in Older Adults: Findings from the 2018 Nationwide Inpatient Sample
Prayag Shah, Drexel University
Hands-On Training
HT-012. SAS® Macro Programming Tips and Techniques
Kirk Lafler, sasNerd
HT-115. Route Sixty-Six to SAS Programming, or 63 (+3) Syntax Snippets for a Table Look-up Task, or How to Learn SAS by Solving Only One Exercise!
Bart Jablonski, yabwon
Quentin McMullen, Siemens Healthineers
HT-187. The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets
Louise Hadden, Cormac Corporation
HT-190. AI Performing Statistical Analysis: A Major Breakthrough in Clinical Trial Data Analysis
Toshio Kimura, Arcsine Analytics
Siqi Wang, Arcsine Analytics
Weiming Du, Alnylam Pharmaceuticals
Songgu Xie, Regeneron Pharmaceuticals
HT-353. What’s black and white and sheds all over? The Python Pandas DataFrame, the Open-Source Data Structure Supplanting the SAS® Data Set
Troy Hughes, Data Llama Analytics
HT-377. Scoring Real-World Data Reliability for Clinical Investigations
James Joseph, EDA CLINICAL
HT-397. Trying Out Positron: New IDE for Statistical Programming
Phil Bowsher, RStudio Inc.
HT-398. Hands-on Training: eTFL Portal & TFL Designer Community
Bhavin Busa, Clymb Clinical
HT-399. Introduction to SAS Viya
Jim Box, SAS Institute
Leadership and Professional Development
LS-010. A Quick Start Guide to Writing a Technical or Research Paper
Kirk Lafler, sasNerd
LS-043. From Null to Notable: Creating a Brand on Social Media
Inka Leprince, PharmaStat, LLC
LS-082. Building Resilient Teams
Patrick Grimes, Parexel
Sajin Johnny, Parexel
LS-093. Bridging the Gap: Leadership of Statistical Programmers in Clinical Trials
Allison Covucci, Bristol Myers Squibb
Xiaohan Zou, BMS
LS-100. Strategies for Thriving During Change and Uncertainty
Maria Dalton, Takeda Pharmaceuticals
LS-118. Unveiling Paradoxical Pathways: A Counterintuitive Compass for Strategic Decision-Making
Anbu Damodaran, Alexion Pharmaceuticals
LS-134. Empowering the Next Generation of Professionals: Merck’s Approach to Rising Talent Engagement and Leadership Development in Statistical Programming
Aston Smith, Merck & Co., Inc., Rahway, NJ, USA
Sarah Alavi, Merck
Jeff Xia, Merck
Tarak Patel, Merck & Co.
LS-139. Active Social Engagement in Remote Working Environments
Christine Reiff, Ephicacy Consulting Group, Inc.
LS-149. Mastering Modern Leadership Through Authenticity, Empathy, Purpose, and Influence
Jyoti (Jo) Agarwal, Gilead Sciences
LS-156. Essential Elements for an Effective New-Hire Training Handbook
Ingrid Shu, Merck
Xinhui Zhang, Merck
LS-170. Optimized Resourcing Strategies in Statistical Programming within CROs and Considerations for AI Integration in Resource Management
Vihar Patel, PPD, part of Thermo Fisher Scientific
LS-232. AI is coming for you: New Biometric Leadership in the era of Gen AI
*** BEST PAPER ***
Kevin Lee, Clinvia
LS-248. Embracing Continuous Learning in the Life Sciences Ecosystem
Iuliana Constantin, CoE Pharma
LS-249. Leading Through Change: Motivating Programming Teams During Mergers and Integrations
Shefalica Chand, Pfizer, Inc.
LS-266. Rising Above Artificial Intelligence: Feeling Confident With Your Human Intelligence
Priscilla Gathoni, Wakanyi Enterprises Inc.
LS-285. Programming Challenges in Master Protocols
Vijaya Jonnalagadda, Revolution Medicines
LS-291. Middle Manager’s Playbook: How to Build and Lead a Strong Remote Team
Yuka Tanaka-Chambers, Phastar
LS-315. Follow the Yellow Brick Road: Finding the Critical Path for a Study’s Lifespan
Jake Gallagher, Catalyst Clinical Research, LLC
LS-360. Data management and biostatistics synergy: how to achieve and what can be expected
Diana Avetisian, IQVIA
LS-365. Proc LIFE-REFLECT: Surviving the Leadership Journey
Steve Nicholas, Atorus Research
Metadata Management
MM-023. Enhancing Dictionary Management and Automation with NCI EVS: A Deeper Dive for the CDISC Community
Anthony Chow, CDISC
MM-083. 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, Sycamore Informatics
MM-085. Use Gen AI to program rules in R & Python to generate and validate metadata for data standards and study specifications.
Priyanka Sawant, Sycamore Informatics
Kairav Tarmaster, Sycamore Informatics
MM-132. Accelerating Data Discovery and Governance: Unlocking Insights with Metadata Management, Data Catalogs, and LLM Integration for Streamlined Regulatory Approval in Clinical Trials
Pritesh Desai, sas
Samiul Haque, SAS Institute
MM-147. The Many Use Cases of Standardized Data and Metadata
Sanjiv Ramalingam, Biogen Idec
MM-227. Does SDTM Validation Really Require Double Programming?
Sunil Gupta, Gupta Programming
Tomás Sabat Stofsel, Verisian
MM-265. AI Empowered Metadata Governance
*** BEST PAPER ***
Prasoon Sangwan, TCS
MM-277. Automating Define-XML Updates: A SAS-Based Framework for Submission Readiness
Qiong Wei, BioPier LLC (a Veramed Company)
Lixin Gao, BioPier LLC (a Veramed Company)
MM-384. The Model Maketh the Metadata
Carlo Radovsky, Independent Consultant
MM-401. Enhancing Health Equity Outcomes through Comprehensive Data Collection of Marginalized Populations including Sexual Orientation, Gender Identity and Intersex Status (SOGI)
Donna Sattler, SGM Alliance
R, Python, and Open Source Technologies
OS-007. Benefits, Challenges, and Opportunities with Open Source Technologies 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
OS-024. An End-to-End Workflow for TFL Generation using R: MMRM Applications and Comparative Insights with SAS
Kai Lei, Vertex Pharmaceuticals, INC
Jiaqiang Zhu, Vertex Pharmaceuticals, Inc
Margaret Huang, Vertex Pharmaceuticals, Inc.
OS-048. Unlocking Insights: Comparative Analysis of CRF Changes with R Shiny
Mayank Singh, Johnson and Johnson MedTech
OS-049. Reach for R Low Hanging Fruit for Faster Results
Sunil Gupta, Gupta Programming
OS-076. TLFQC: A High-compatible R Shiny based Platform for Automated and Codeless TLFs Generation and Validation
Chen Ling, AbbVie
Yachen Wang, AbbVie
OS-077. Comparing SAS® and R Approaches in Reshaping data
Yachen Wang, AbbVie
Chen Ling, AbbVie
OS-094. Unlocking Success: Lessons from Building R-Based Statistical Packages in Pharma
Sydney Hyde, Bristol Myers Squibb
Yirong Cao, Bristol Myers Squibb
OS-096. A Gentle Introduction to creating graphs in Python, R and SAS
Dane Korver, RTI International
OS-107. Clinical Data Quality Assurance: An Interactive Application for Data Discrepancy Detection
Yushan Wang, Merck
OS-111. Integrating Collaborative Programming with Automated Traceability and Reproducibility in Pharma Studies and Real-World Data Projects by Adapting DevOps Best-Practices
Ariel Asper, Graticule
Sundeep Bath, Graticule
Jennifer Dusendang, Graticule
Yuval Koren, Graticule
Silvia Orozco, Graticule
OS-120. Streamlining BIMO and Patient Profile Generation: A Python-Based Semi-Automated Approach Integrated with CSR Development
Dmytro Skorba, Intego Clinical
Mykyta Vysotskyi, Intego Clinical
OS-122. Streamlining Validation Review and SAS® Program Management with R
Huei-Ling Chen, Merck & Co.
OS-128. How to compute common clinical trials statistics in R
Oleksandr Babych, Intego Group LLC
OS-145. Code Switching: Parallels between Human Languages and Multilingual Programming
Danielle Stephenson, Atorus Research
Laura Mino, Atorus Research
OS-164. Catch Page Overflow Issues Quick and Easy – A Simple Python Solution
Junze Zhang, Merck Co., Inc
Huei-Ling Chen, Merck & Co.
OS-167. Advanced Programming with R: Leveraging Tidyverse and Admiral for ADaM Dataset Creation with a Comparison to SAS
Joshua Cook, University of West Florida (UWF)
Richann Watson, DataRich Consulting
OS-179. Slice, Dice, Analyze: Revolutionizing SDTM cuts with datacutr package
Diego Madrigal Viquez, Intego Clinical
OS-182. Interactive Longitudinal Data Analysis and Visualization in Clinical Research Using R.
Maria Gomez Ramirez, Intego Clinical
OS-195. Building a Scalable Training Platform for R: Empowering Analytics Excellence in Corporate Initiatives
Michelle Page-Lopez, Syneos Health
Martyn Walker, Syneos Health
OS-203. R Programming in SAS® LSAF: How to Generate Clinical Reports Using an R Session
Praneeth Adidela, ICON plc
OS-215. {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, Genentech
OS-229. Identifying Breaking Changes in R Packages: pkgdiff
David Bosak, r-sassy.org
OS-255. Debugging Options in R: Applications and Usage in Clinical Programming
Madhusudhan Ginnaram, Merck
Bingjun Wang, Merck &Co.
Jeetender Chauhan, Merck & Co., Inc.
Sarad Nepal, Merck
OS-288. Putting the ‘R’ in RWD: Leveraging R and Posit to enhance Real World Data Programming
Darren Jeng, Pfizer
Sachin Heerah, Pfizer
OS-290. Packing PDF TFL with Table of Contents and Bookmarks Using Python
*** BEST PAPER ***
Jun Yang, Avidity Bioscience
Yan Moore, Avidity Bioscience
OS-293. Achieving Reliable Data Verification with R: Proven Tools, Best Practices, and Innovative Workflows
Valeria Duran, Statistical Center for HIV/AIDS Research and Prevention at Fred Hutch
Xuehan Zhang, Fred Hutch Cancer Center
OS-323. Python with Hermione: Unleash Your Inner Coding Witch & Dragon
Charu Shankar, SAS Institute
Jim Box, SAS Institute
OS-330. The {teal} Adoption Playbook: Strategies, Tools, and Learning Paths for Open Source
Vedha Viyash, Appsilon
OS-351. Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS® and Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More!
Troy Hughes, Data Llama Analytics
OS-364. Building Extensible Python Classes for Analysis and Research : It’s Easier Than You Think!
Sundaresh Sankaran, SAS Institute
Samiul Haque, SAS Institute
OS-395. Shiny & LLMs: Landscape and Applications in Pharma
*** BEST PAPER ***
Phil Bowsher, RStudio Inc.
Real World Evidence and Big Data
RW-042. Leveraging Health Technology Assessment (HTA) for Market Access: A Statistical Programming Perspective on German HTA Submission
*** BEST PAPER ***
Rachana Agarwal, Servier Pharmaceutical
Wendy Wang, Servier Pharmaceuticals
RW-057. Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source.
Jayanth Iyengar, Data Systems Consultants LLC
RW-110. Beyond Tokenization: Considerations for Linking Healthcare Data Sets for Scientific Research
Jennifer Dusendang, Graticule
Yuval Koren, Graticule
RW-154. Addressing early challenges in RWD data standardization for analysis and reporting of RWE studies
Xingshu Zhu, Merck
Li Ma, Merck
Bo Zheng, Merck
RW-184. Addressing Challenges in Real-World Evidence Generation: The AI-SAS for Real-World Evidence Approach
Takuji Komeda, Shionogi Co., Ltd.
Yuki Yoshida, Shionogi & Co., Ltd.
Yohei Komatsu, TIS Inc.
Yoshitake Kitanishi, Shionogi & Co., Ltd.
RW-234. Going from PROC SQL to PROC FedSQL for CAS Processing – Common mistakes to avoid.
Vijayasarathy Govindarajan, SAS Institute
RW-289. Practical Process in SAS of Using External Controls
Hui Mao, BioPier Inc.
Na Wang, BioPier
Lixin Gao, BioPier
RW-328. An Introduction to Using PROC S3 in SAS to Access and Manage Objects in Amazon S3
Kevin Russell, SAS
Russ Tyndall, SAS
RW-340. You don’t have to handle the truth! Three Things to Know about Synthetic Data
Catherine Briggs, SAS
Robert Collins, SAS Institute
Sundaresh Sankaran, SAS Institute
RW-352. Time to Event Analysis from Sample Size Considerations to Results Interpretation in Simple Words
Iryna Kotenko, Intego Group LLC
RW-374. The Many Ways to Build Cohorts to Effectively Generate Real World Evidence and Bring Drugs to Patients Faster
Sherrine Eid, SAS Institute
Mary Dolegowski, SAS
Solution Development
SD-044. Running the CDISC Open Rules Engine (CORE) in BASE SAS©
Lex Jansen, CDISC
SD-054. Automated Word Report Generation for Standardized CMC PC Study with Programmatically Inserted Contents in R
*** BEST PAPER ***
Song Liu, Merck & Co., Inc
Jiannan Kang, Merck
SD-098. A Method to Add Additional Necessary Datasets to Existing Define.XML
Jeff Xia, Merck
Sandeep Meesala, Merck & Co. Inc.
SD-116. Use of SAS Packages in the Pharma Industry – Opportunities, Possibilities and Benefits
Bart Jablonski, yabwon
SD-131. Enhance your Coding Experience with the SAS Extension for VS Code
Jim Box, SAS Institute
SD-138. Using SAS with Microsoft 365: A Programming Approach
Chris Hemedinger, SAS
SD-142. Share your Macros and Programs with SAS Studio Steps and Flows
Jim Box, SAS Institute
Pritesh Desai, sas
SD-143. Low-Code Solutioning in SAS Viya for Automated Clinical Data Quality, Decisioning and Harmonization
Mary Dolegowski, SAS
Scott McClain, SAS Institute
SD-155. Integrating SAS DDE to Automate Excel Task Tracking in Pharmaceutical Statistical Programming
Amy Zhang, Merck & Co.
Huei-Ling Chen, Merck & Co.
SD-176. AI Search LOG
Zhuo Chen, BridgeBio Pharma
Martha Cao, BridgeBio Pharma, LLC
Ted Lystig, BridgeBio Pharma, LLC
Sateesh Arjula, BridgeBio Pharma, LLC
SD-177. Bridging RStudio and LSAF: A Framework for Faster and Smarter Task Execution
Jake Adler, Alexion Astrazeneca Rare Disease
Ben Howell, SAS
Lindsey Barden, Alexion
SD-196. Optimizing SAS Programming Pipelines Using the %Unpack and %SearchReplace Macros for Version Control and Customization
Ning Ning, PROMETRIKA LLC
Assir Abushouk, PROMETRIKA, LLC
SD-218. How to get your SAS’Python’R workout on a new SAS Viya Workbench.
Pritesh Desai, sas
Samiul Haque, SAS Institute
SD-220. Building Robust R Workflows: Renv for Version Control and Environment Reproducibility
Junze Zhang, Merck Co., Inc
Joshua Cook, University of West Florida (UWF)
SD-228. A SAS® System 7-zip macro that creates a zip archive and a file archive macro: versioning in the context of a private library of programs.
Kevin Viel, Navitas Data Sciences
SD-230. A SAS® System PowerShell macro to report directory-level metrics by Owner (programmer).
Kevin Viel, Navitas Data Sciences
SD-257. Enhancing Clarity and Efficiency in Clinical Statistical Programming Task Management: An Automated Integrated Task Reporting Solution with Excel and Python
Xinran Hu, Merck
SD-334. A codelist generator for define.xml using a SAS Studio macro and RStudio function
Valerie Cadorett, Pfizer Inc.
SD-339. Improve Your CRF Review Process: A Python-Based Approach to Capturing CRFs via Browser Automation
*** BEST PAPER ***
Andrew Herndon, Spark Therapeutics
SD-371. SAS Program for Backup Zipping
Tong Zhao, LLX Solutions, LLC
SD-400. Unleash Your Coding Potential: SAS PRX Functions for Next-Level String Manipulations
John LaBore, SAS Institute
Statistics and Analytics
SA-004. Promising Zone Designs for Sample Size Re-estimation in Clinical Trials: Graphical Approaches Using SAS
Zhao Yang, Bicara Therapeutics
Shivani Nanda, HUTCHMED
SA-101. Sensitivity Analysis for Overall Survival
Binal Mehta, Merck & Co.
Patel Mukesh, Merck & Co INC
SA-108. Automating Superscript Display for Upper and Lower Limit of Quantification Values in Pharmacodynamic Tables
Anu Eldho, Kite Pharma
SA-124. A Step-by-Step Guide to Calculating Relative Dose Intensity in Solid Tumor Studies
Yan Xu, Abbvie
Pingping Xia, AbbVie
Jagadesh Mudapaka, AbbVie
SA-130. An Introduction to Obtaining Test Statistics and P-Values from SAS® and R for Clinical Reporting
Brian Varney, Experis
SA-168. The Allowable Total Difference Zone: A construction method using the ATDzone SAS® Macro
Jesse Canchola, Roche Diagnostics Solutions
Natasha Oza, Roche Diagnostics Solutions
SA-171. Super Learner for Predictive Modeling and Causal Analysis
Honghe Zhao, SAS Institute
Clay Thompson, SAS Institute
Michael Lamm, SAS Institute
SA-173. Calculating exact posterior probabilities and credible intervals from Bayesian borrowing robust mixture priors for binary, count and continuous outcomes in R and SAS
*** BEST PAPER ***
Darren Scott, AstraZeneca
Armando Turchetta, AstraZeneca
SA-183. “Leveraging Python for Statistical Analysis in Public Health: Techniques and Visualizations for Life Sciences Professionals”
Michael Carnival, University of West Florida
SA-189. Deciphering Exposure-Response Analysis Datasets: A Programmer’s Perspective for Oncology Studies
Sabarinath Sundaram, Pfizer
SA-198. A SAS Macro Calculating Confidence Intervals of the Difference in Binomial Proportions from Stratified Analysis using the Miettinen & Nurminen Method with Cochran-Mantel-Haenszel Weights
Mikhail Melikov, Cytel
Brian Mosier, EMB Statistical Solutions
SA-205. Programming Perspectives for Efficient and Accurate C-QTc Analysis
Lingjie Zhang, Merck
Lata Maganti, Merck
Richard Moreton, Merck
Runcheng Li, Merck
SA-207. Clopper Pearson CI? get your data ready for it!
Ruth Rivera Barragan, Ephicacy Consulting Group
Isaac Vazquez, Ephicacy Consulting Group
SA-231. Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis
Yuxin Wang, LLX Solutions, LLC
Kelly Chao, LLX Solutions, LLC
Wenqing Yu, LLX Solutions, LLC
Hongbing Jin, LLX Solutions, LLC
SA-245. Practical considerations for Intercurrent Events and Multiple Imputation
David Bushnell, Cytel
SA-267. Handling Missing Data in External Control Arms: Best Practices, Recommendations, and SAS Code Examples
Yutong Zhang, LLX Solutions, LLC
SA-270. Simulating Optimal Sample Sizes for Canine Jaws Using SAS®
Chary Akmyradov, Arkansas Children’s Research Institute
Lida Gharibvand, Loma Linda University
SA-287. Roadmap to Efficacy Analysis for Early Phase Oncology studies
Dhruv Bansal, Catalyst Clinical Research
Christiana Hawn, Catalyst Clinical Research
Chris Kelly, Catalyst Clinical Research
SA-321. Efficacy Endpoints Related to CNS in Oncology Studies within ADaM
Lihui Deng, Bristol Myers Squibb
Kylie Fan, Bristol Myers Squibb
SA-343. Implementation of the inverse probability of censoring weighting (IPCW) Model in Oncology Trials
Mei Huang, Exelixis, Inc
Shibani Harite, Exelixis Inc.
Haijun Ma, Exelixis, Inc.
Linsong (Athena) Zhang, Exelixis Inc.
SA-368. Incorporating Frailty into Time-to-Event Analysis: A Practical Approach with R frailtypack
Sunil Kumar Pusarla, Omeros Corporation
Avani Alla, Omeros Corporation
SA-372. Landmark Analysis: A Method for Accurate Prediction of Time-Dependent Clinical Risks and Their Effect on Patient Outcomes
Sunil Kumar Pusarla, Omeros Corporation
Avani Alla, Omeros Corporation
Strategic Implementation & Innovation
SI-046. The Current State of Teaching Biostatistics in Academia: Challenges and Software Solutions
Lida Gharibvand, Loma Linda University
SI-061. Generative AI in Biometrics: Transforming Clinical Trials with Supercharged Efficiency an Innovation
Kevin Lee, Clinvia
SI-064. Strategies to Encourage Adoption and Innovation in Statistical Programming
Archana Gundamraju, Biogen
SI-066. Navigating Compliance Excellence: ISO Standards & Data Privacy Implementation
Ashwini Kanade, Ephicacy Consulting Group
Syamala Schoemperlen, Ephicacy Consulting Group
SI-084. Approaches to Developing Multiple Imputation ADaM Datasets
Kang Xie, AbbVie
SI-112. Decoding the Role of Statistical Programming – A Decade of Keytruda Submissions and Approvals
Mary Varughese, Merck & Co., Inc.
Hong Qi, Merck & Co., Inc.
SI-159. Navigating the transition of legacy processes for SDTM creation
Jyothi Ketavarapu, Consultant, AbbVie
SI-180. SDTM Transformation through Artificial Intelligence (AI) and Human in the Loop (HITL): Lessons Learnt from Abbvie Case Study
Aman Thukral, Abbvie
Sanjay Bhardwaj, Abbvie
SI-206. Build vs. Buy: Strategic Considerations for Implementing AI Solutions in Pharma and Biotech Companies
Rajesh Hagalwadi, MaxisIT Inc
SI-224. Elevating Clinical Research: Strategic Implementation of CDASH and SDTM Standards
Hayden Patel, DaiichiSankyo
SI-225. Stop Making More Physical Copies of Your Data: A Modern Approach to Traceability and Fidelity
Anthony Chow, CDISC
SI-253. Transitioning External Clinical Studies to Internal: A Framework for Knowledge Transfer and Operational Excellence
Chunqiu Xia, Merck & Co., Inc.
Hong Zhang, Merck & Co
Xiaohui Wang, Merck & Co., Inc.
SI-292. Integration Contemplation: Considerations for a Successful ISS/ISE from Planning to Execution
Jennifer McGrogan, Biogen
Mario Widel, IQVIA
SI-294. A Game Changer for Efficient SAS Programming using ChatGPT
*** BEST PAPER ***
Jyoti (Jo) Agarwal, Gilead Sciences
SI-342. Comparing SQL and Graph Database Query Methods for Answering Clinical Trial Questions with LLM-Powered Pipelines
Jaime Yan, Merck
SI-359. An Introduction to the Role of Statistical Programming in Medical Affairs
Nagadip Rao, Alnylam Pharmaceuticals, Inc.
SI-380. Towards an Integrated Submission-Ready Data Pipeline: Unifying Compliance, Automation, and Open-Source Innovation
Shivani Gupta, Clymb Clinical
Bhavin Busa, Clymb Clinical
Submission Standards
SS-070. Identification of Domains Containing Screen Failure Participants in SDTMs and ADaMs for Reviewer’s Guides
Sumanjali Mangalarapu, Merck
SS-087. A collaborative and agile approach for end to end Standards Governance and Release
Kairav Tarmaster, Sycamore Informatics
Pratiksha Wani, Sycamore Informatics
SS-127. PDFs Done Right: The Statistical Programmer’s Guide to Flawless Regulatory Submissions
Srivathsa Ravikiran, Agios Pharmaceuticals
Sri Raghunadh Kakani, Agios Pharmaceuticals
SS-135. Evaluation of the Process to Create CLINSITE define.xml: Macro Approach vs. ADCLIN Spec
Yizhuo Zhong, Merck
Yunyi Jiang, Merck & Co., Inc.
Christine Teng, Merck
SS-146. Handling Health Regulatory Information Requests: Best Practices and Strategies
*** BEST PAPER ***
Himanshu Patel, Merck & Co.
Chintan Pandya, Merck & Co.
SS-165. 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, Emergent BioSolutions, Inc.
SS-254. Key guidelines, Tricks and Experiences for PMDA and comparison with FDA and CDE submission
Ramesh Potluri, Servier Pharmaceutical
SS-258. The Show Must Go On: Best Practices for Submitting SDTM Data for Ongoing Studies
Kristin Kelly, Pinnacle 21 by Certara
SS-269. Exploring the Upcoming Integrated cSDRG!
Srinivas Kovvuri, ADC Therapeutics USA
Christine McNichol, Fortrea Inc.
Randi McFarland, Ephicacy Consulting Group, Inc.
Kiran Kundarapu, Eli Lilly and Company
Satheesh Avvaru, Alexion AstraZeneca Rare Disease
SS-276. Updating Define-XML packages: Tips and A Comprehensive Checklist
Qiong Wei, BioPier LLC (a Veramed Company)
Ji Qi, BioPier LLC (a Veramed Company)
Lixin Gao, BioPier LLC (a Veramed Company)
SS-306. ADaM and TFLs for Drug-induced Liver Injury (DILI) Analysis
Song Liu, Novo Nordisk
Rambabu Sura, Novo Nordisk
SS-314. Checking Outside the Box: A Framework for Submission Success
Julie Ann Hood, Pinnacle 21 by Certara
Seiko Yamazaki, Pinnacle 21 by Certara
SS-333. Leveraging previous study data for Extension studies: Structuring Subject and Participant Level Analysis datasets using CRF data
Priyanka Thumuganti, GlaxoSmithKline plc
SS-344. Ensuring Data Integrity: Techniques for Validating SDTM Datasets in Clinical Research
Amy Welsh, Catalyst Clinical Research
SS-348. Common Issues in BIMO Clinical Site Dataset Packages
Michael Beers, Pinnacle 21 by Certara