Best in Stream

Industry

PP05: GitLab vs GitHub: The Battle of the Repositories

Amaya Opalka, Roche

Collaboration

PP19: Representing Virtual Control Animal Data in SEND

Gitte Frausing, Data Standards Decisions, Frank Bringezu, Merck, Christy Kubin, Charles River Laboratories & William Houser, Bristol Myers Squibb

Analytics & Statistics

Multiple Imputation in Composite Endpoints - It’s Not That Hard!

Ashley Mao

Analytical Risk-based Monitoring

Risk Based Quality Management (RBQM) in Clinical Data Management

Anna Górecka & Marcin Kot

Data Handling & Engineering

Demystify the Handling and Mapping of External Data to CDISC Standards in Clinical Trials

Vamsi Kandimalla & Murali Kanakenahalli

Data Standards, Governance & Implementation

End-to-End Therapeutic Area Data Standards Development and Governance – A Case Study Involving CRS and ICANS

Yaling Teng

Emerging Trends

Automating SAS and R Code Interpretation and Debugging: A Practical Pipeline for Statistical Programmers

Jaime Yan & Tingting Tian

Machine Learning, AI & Large Language Models

Scaling Up: Accelerating Self-Hosted Open-Access LLMs to Compete with the Big Three (ChatGPT, Claude, Gemini)

Kostiantyn Drach & Iryna Kotenko

Open Source Technologies

Unleashing the Power of {teal}: New Features and Cross-Industry Collaboration

Nina Qi & Dony Unardi

Poster Presentations

From Topline to Triumph: Visualising the Pathways to Regulatory Approval

Jasperlynn Kao

Professional Development

Harmonising Heterogeneity: Orchestrating Innovation Through Interdisciplinary Collaboration and Strategic Alignment

Dorothy Dlamini & Srinivas Veeragoni

Real-world Evidence

Real-World Data – Analysis-Ready Datasets: A Standardised, Specialised and Innovative Data Solution for Efficient Real-World Data Analysis

Nayan Chaudhary & Navdeep Pal

Scripts, Macros & Automation

Using Large Language Models for Consistency Checking of Tables, Listings and Graphs

Yingying Wei

Submissions & Agencies

From Application to Approval: Exploring the FDA’s Review Process

Kiran Bonda

Application Development

AD04: Advancing Kidney Assessments for Transplants with AI-driven Applications

Federica Citterio & Soundarya Palanisamy, SAS

Analytical Risk-based Monitoring

AR03: Quality Tolerance Limits: Understanding the Added Value and Statistical Need of Implementing QTLs to Assure Subject Safety and Data Quality

Nathalie van Borrendam & Agnes Verhoeven, Johnson & Johnson

Analytics & Statistics

AS04: Comparison of the Wilcoxon-Signed Rank Test with the Hodges-Lehmann Estimator in SAS, R and StatXact as Part of the PHUSE CAMIS Project

Agnieszka Tomczyk & Lyn Taylor, PAREXEL

Coding Tips & Tricks

Getting a Prompt Response Using ChatGPT and SAS

Stephen McCawille, Daiichi Sankyo

Data Handling & Data Engineering

DH14: Transcriptomics – A Demanding Data Analysis that Expands the Limits of Regulated Clinical Data Handling

Lea Hildebrandt, Novo Nordisk

Data Standards & Governance

DS13: Estimands: How to Make ADaM Implementation Your Friend

Jaclyn Amberg & Dennis Kusian, Metronomia Clinical Research

Data Visualisation

DV05: Interactive Reporting Using FDA Standard Safety Shells and the CDISC Analysis Results Standard

Megan Harries & Steve Mallett, Veramed

Leadership Through Innovation

LI05: Trustworthy and Responsible AI in Healthcare and Life Sciences From a Leadership Perspective

Mark Lambrecht, SAS

Machine Learning, AI and Large Language Models

ML18: Hi. I Am a Chatbot. How Can I Help You? Enhancing the Reliability and Traceability of Large Language Models

Vicky Poulsen & Anya Vrecer, Novo Nordisk

Open Source Technologies

OS07: Two Hats, One Noggin: Working as a Developer and as a User of the Admiral R Package for Creating ADaM

Edoardo Mancini, Roche & Ben Straub, GSK

Professional Development

PD09: Four Languages, Three Years: An Agile Approach to Data Science

Shannon Haughton, GSK

People Leadership & Management

PM03: Dealing with the Poor Performer

Stephen Prust, elderbrook solutions

Poster Presentations

PP07: Building CORE Strength: An Implementation Exercise

Stine Bertelsen & Addie Olsen, Novo Nordisk

Real-world Evidence

RE03: Future Clinical Data Submission Standards: CDISC, FHIR, OMOP, or Hybrid Model

Jeffrey Abolafia, Pinnacle 21 by Certara, Sarah Ferko & Ingeborg Holt, IBM

Submissions & Agencies

SA06: Harmonising FDA and PMDA Submission Requirements

Luca Semeraro, Alira Health

Standards Implementation

SI04: Mapping a Veeva SDS Specification to ODM-XML

Jørgen Iversen, Novo Nordisk

Scripts, Macros & Automation

SM03: Optimising Workflow and Collaboration in a Pooled Coding Environment for Clinical Development

Louise Nørgaard, Novo Nordisk

Trends & Technology

TT02: Working with Omics Data – A Statistical Programmer’s Perspective

Adrian Czaban, Novo Nordisk

Industry

PP18: Bridging the Gap – Enhancing Analysis Results Generation with the CDISC ARS Model and the Community TFL Designer

Bhavin Busa, Clymb Clinical

Collaboration

PP03: SEND (Standard for Exchange of Nonclinical Data) Industry Feedback Survey: 2024 Results

Vanessa Chavez, Labcorp & Lindsy Eickhoff, Inotiv

FDA

PP23: A Framework Enabling LLMS into Regulatory Environment for Transparency and trustworthiness and its Application to Drug Labelling Document

Shraddha Thakkar, FDA

Analytical Risk-based Monitoring

AR01: My Data Is Too Good to Be True! Should I Worry About Fraud or Sloppiness?

Michael Walega, Bristol Myers Squibb & Johann Proeve, Cyntegrity

Analytics & Statistics

AS05: Spline Analysis to Understand the Non-linear Relationship in Clinical Research

Anwaya Joshi, Cytel

Data Handling & Engineering

DH02: Eliminating SDTM Double Programming by Using a Validation Tool and Dummy Data

Glenn Borgmans & Tine Seeuws, SGS Health Science

Data Standards & Governance

DS05: Approaching End-to-End Analysis Standardisation in Global and Therapeutic Areas Level

Rudra Sheth & Xiaohan Zou, Bristol Myers Squibb

Data Visualisation

DV05: Statistical Monitoring Report: A Path Forward to Interactive Data Analysis and Quantitative Decision-Making

Debopriya Ghosh & Xiang Li, Johnson & Johnson

Emerging Trends

ET08: AI Exploration and Innovation for the Clinical Data Scientist

Cole Arendt & Phil Bowsher, Posit

Open Source Technologies

OS03: NEST: How Could We Generate and Deliver Clinical Insights Even Faster?

Vincent Shen, Roche

People Leadership & Management

PM03: Leadership Insights – Let’s Learn How to Lead the Leaders

Rachna Mittal, Genentech

Poster Presentations

PP07: Sowing Seeds of Inspiration: Letters to a Pre-Scientist

Julie Ann Hood, Pinnacle 21 by Certara

Professional Development

PD03: Recruiting the Best Talent and Developing them within the Organisation

Madhusudhan Reddy Papasani & Naveen Kommurur, Merck

Real-world Evidence

RE03: Future Clinical Data Submission Standards: CDISC, FHIR, OMOP, or Hybrid Model

Jeffrey Abolafia, Pinnacle 21 by Certara

Scripts, Macros & Automation

SM10: A Practical Approach to Automating SDTM Using a Metadata-Driven Method that Leverages eCRF Specifications and SDTM Programming Standards

Xiangchen (Bob) Cui & Min Chen, CRISPR Therapeutics

Standards Implementation

SI02: Automating ADaM Creation in Clinical Trials Part 2

Rie Ichihashi & Lyubov Sushchenko, Sanofi

Submissions & Agencies

SA03: Demystifying Submissions to NMPA China

Dyuthi Yellamraju & Hiral Raval, Genentech

Therapeutic Areas Specific Topics

TA04: Are Platform Trials the Need of the Hour for Oncology Trials?

Vidya Muthukumar, IQVIA

Application Development

AD15: Janssen DATA4YOU Platform Approach for Clinical Data Review

Erik Lemmens & Paul Foole, Johnson & Johnson

Analytical Risk-based Monitoring

AR07: Risk-Based Monitoring in Clinical Trials with Machine-Learning-Powered Anomaly Detection

Ece Kavalci & Zaid Al-Jubouri, Lindus Health

Analytics & Statistics

AS10: Comparison of Power Between Different Recurrent Events Analysis Methods Using Simulation

Soumitra Kar, Novo Nordisk

Coding Tips & Tricks

CT05: Dynamic Testing for Empty Datasets

Timothy Lachlan-Cope, AstraZeneca

Connected Health & Machine Learning

CM06: Unleashing the Power of Large Language Models for Clinical Data Approaches: Will AI Chatbots such as ChatGPT/Bard Replace Statistical Programmers and Statisticians Over Time?

Ercan Suekuer, Roche

Data Handling & Data Engineering

DH02: How Can Python Be Used in Clinical Trials?

Pierre Dostie & András Kása, UCB Biosciences

Data Standards & Governance

DS07: Automated Pipelines for Non-CRF Value-Level Metadata: A Meta-Programming Approach

Selena Baset & Philipp Thomas Ernst, Roche

Data Visualisation

DV01: Will R/Shiny Provide a Novel Way for Study Teams to Review Clinical Data?

Gustav Söderström, AstraZeneca

Leadership Through Innovation

LI03: Road to Rome or Roaming – A Reprise

Christian Müller, Roche & Francis Kendall, AstraZeneca

Professional Development

PD05: Mastering the Art of Adaptation: Innovative Strategies for Effective Change Management

Mark Bynens, Johnson & Johnson

People Leadership & Management

PM06: Statistical Programming – Hiring Mission Made Possible

Christoph Ziegler & Donald Paterson, Johnson & Johnson

Poster Presentations

PP16: CDISC’s ADTTE Domain: Time-to-Event Analysis From a Programmer’s Point of View

Vitali Gering & Sophia Praeger, Chrestos Concept

Real-world Evidence

RE06: The Curious Case of Observational Studies – A Programmer’s Dilemma

Vikas Shokeen, Novartis

Submissions & Agencies

SA07: Development Safety Update Report (DSUR)/Periodic Safety Update Report (PSUR)

Phillip Spowart, Fortrea

Software Demonstrations

SD04: Digitalisation of Specifications – Enabling the Next Generation of Clinical Trials

Rebecca Bates & Nekzad Shroff, Saama Technologies

Standards Implementation

SI02: Oak Garden – Metadata-Driven SDTM Automation in R

Magdalena Krochmal & Amy Franklin, Roche

Scripts, Macros & Automation

SM02: Same But Different: Leveraging R for Comparing Clinical Study TFL Versions

Tiina Kirsilä, Novartis & Anna Wiksten, Bristol Myers Squibb