| Time | Events |
|---|---|
| 7:30 AM Registration | Short Course |
| 9:00 AM – 4:30 PM Short Course Full Day |
(SC 1) Information Extraction and Document
Preparation in Clinical Trial Development using RAG-based
LLMs Instructors: Zhaohua Lu; Daichi Sanko; Arina Shen, Biomedical Data Science Masters Student at Stanford University School of Medicine (SC 4) CGM-AI: Causal Generalist Medical AI Instructors: Hongtu Zhu, UNC; Qiao Liu, Yale |
| 9:00 AM – 12:00 PM Short Course Morning Session |
(SC 2) Trust by Design: Applied AI
Governance for Pharma with Hands-On Application
Exercises Instructors: Rebecca D. Jones-Taha, AIGxPLabs (SC 5) Python for Clinical Development with AI Applications Instructors: Yilong Zhang, Meta; Pingye (Eric) Zhang, Eikon Therapeutics; Yuting Xu, Merck |
| 1:30 PM – 4:30 PM Short Course Afternoon Session |
(SC 3) Personally Identifiable Information
Redaction Agent: LLM as Judge, REGEX Instructors: Andrew Semmes, Moderna |
| Time & Session | Presentations |
|---|---|
|
7:30 AM – 8:45 AM Registration & Breakfast |
All Conference Attendees |
|
8:45 AM – 9:05 AM Opening Remarks |
New England Statistical Society Leadership |
|
9:05 AM – 9:45 AM Keynote Speech |
Andrew Garrett, PhD (Executive VP, ICON) Keynote Speaker |
|
9:45 AM - 10:15 AM Keynote Panel Discussion |
Prof. Hou, Peking University TBD Pending |
| 10:15 AM - 10:30 AM: Break | |
|
Session 1: 10:30 AM - 12:00 PM AI in Pharma: Regulatory Perspectives & Safety Applications |
• AI Applications in Drug Development and Regulatory Review:
China Landscape (Peking University & Merck) • Agentic MedDRA Coding: Automated AE Term Standardization (Moderna) • Quantitative Safety Evaluation: AI Agents and Causal Inference in PV (Merck) |
|
12:00 PM – 1:30 PM Lunch and Poster Presentation |
|
|
Session 2: 1:30 PM – 3:00 PM Advanced Methods for Outcomes Prediction and Patient Stratification |
• Improving Interim Decision Making: Predictive Modeling of
Censored Survival Outcomes with Machine Learning
(Servier) • TorchSurv: Deep survival analysis made easy (Novartis) • Identifying High-Risk Asthma Patient Subgroups Using Predictive + Unsupervised Learning (IQVIA) Session 2: Advanced Methods for Outcomes Prediction and Patient Stratification |
|
3:00 PM – 4:45 PM Session 3: Transforming R&D Infrastructure with GenAI |
• Beyond Macros and Mappings: LLMs as the New Co-Programmer
in Clinical Data Standards (BeOne) • Reinventing R&D: Building an AI-Powered Biopharma Future (Sanofi) • Shaping an AI-Native Biometrics Group (Meta) Session 3: Transforming R&D Infrastructure with GenAI |
| 4:45 PM – 5:00 PM: Break | |
|
5:00 PM – 6:00 PM Mixer & Poster Session |
All Conference Attendees |
|
6:30 PM – 7:45 PM Banquet Keynote Session |
Junshui Ma, Merck, Our Journey in Building an AI-Ready
Workforce, Merck Research Laboratories Keynote Speaker |
| Time & Session | Speakers |
|---|---|
|
7:30 AM – 8:45 AM Registration & Breakfast |
All Conference Attendees |
|
9:00 AM – 10:30 AM Session 4: Operationalizing AI in Clinical Development: Execution, Automation & Planning |
• AI in Clinical Operations: Risk-Based Management Systems
(ZS) • Accelerating Protocol Development: Standardization, Digital Reuse, and AI Copilots (BeOne) • AI-assisted Literature Review Tool to Boost Evidence Generation for ctDNA (Sanofi) Session 4: Operationalizing AI in Clinical Development: Execution, Automation & Planning |
| 10:30 AM – 10:45 AM: Break | |
|
10:45 AM – 12:15 PM Session 5: Digital Twins & Synthetic Evidence Generation |
• Digital Twins in Clinical Trials: Concepts, Applications,
and Future Directions (BMS) • FedECA: Federated External Control Arms for Causal Inference with Time-to-Event Data (Sanofi) • Assumption-Lean Synthetic Individual Patient Data Generation (HopeAI) Session 5: Digital Twins & Synthetic Evidence Generation |
| 12:15 PM – 1:30 PM: Lunch | |
|
Session 6: 1:30 PM – 3:00 PM Optimizing Statistical Workflows: Trial Design, Planning & Reporting Automation |
• A Collaborative Workflow for Efficient Exploratory
Biomarker Planning Using Statistical Optimization Tools
(BMS) • AI Reading and Understanding the SAP to Automatically Generate the TFL TOC (SAP parsing, AI agents, hybrid AI + programming) (Alnylam) • Table-Gen RAG: A Retrieval-Augmented Generation Framework for Automated Clinical Trial Table Shells (Rutgers, Student Presentation) |
| 3:00 PM – 3:30 PM: Break, Awards, & Closing |
*Session timeslots subject to change