Program

Generative AI in Medical Research & Drug Development: Hype or Reality?

Day 1 (June 10, 2024)

12:30 PM – 1:00 PM

Registration  

1:00 PM – 5:00 PM

Tutorials
(Coordinator, Nareen Katta, AbbVie)

1:00 PM – 3:00 PM       
Tutorial 1:
AI/ML in Pharma. Claire Zhao (Pfizer Inc.) and Haoda Fu (Eli Lilly)

3:00 PM – 3:15 PM

Break

3:15 PM – 5:15 PM
Tutorial 2:
RWE in Drug Development. Hana Lee (FDA) and Susan Gruber (
Putnam Data Sciences, LLC)

 

Day 2 (June 11, 2024)

7:30 AM – 8:30 AM

Registration and Breakfast 

8:30 AM – 8:35 AM
Day 2 Welcome
(David Madigan, Northeastern University; Ron Wasserstein, American Statistical Association)
8:35 AM – 8:40 AM
Opening Remarks and Introduction of Keynote Speaker
(Kannan Natarajan)
8:40 AM – 9:35 AM      
Keynote Address
Patrizia Cavazzoni, MD, Director, Center for Drug Evaluation and Research, U.S. Food & Drug Administration.
(Moderator, Kannan Natarajan) (50 min with Q&A)

9:35 AM – 10:00 AM

Break/Posters

10:00 AM – 11:15 AM

Day 2 Plenary Session 1 (Chair, Margret Gamalo, Pfizer Inc.)

  • “Empowering Insights in the All of Us Research Program: A Statistical Perspective on the Transformational Role of AI and ML”, Qingxia ‘Cindy’ Chen, Biomedical Informatics, and Ophthalmology & Visual Sciences at Vanderbilt University Medical Center (25 min)
  • The Generalist Medical AI Will See You Now”, Pranav Rajpurkar, Ph.D., Harvard University (25 min)
  • Lessons from pre-trained observational large longitudinal models in OHDSI (APOLLO),  Marc Suchard, UCLA  (25 min).

11:15 AM 11:25 AM

Break/Posters

11:25 AM – 12:40 PM

 

Day 2 Plenary Session 2 (Chair, Bingzhi Zhang, Sanofi)

  • “Generative Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes”, Yuanjia Wang, Columbia University   (25 min)
  • Machine Learning for Causal Inference”, Stefan Wager, Stanford University (25 min)
  • “Leveraging the Power of Large Language Models (LLMs) by Statisticians for Pharmaceutical Research & Development”, Junshui Ma, Head of the Biometrics Research Department, Merck Research Lab.  (25 min)

12:40 PM – 1:30 PM

Lunch

1:30 PM – 3:10 PM

 

Day 2 Plenary Session 3 (Chair, Emre Kiciman, Microsoft)

  • The Role of Targeted Machine Learning in a Causal Roadmap for Generating High-Quality Real-World Evidence, Lauren Elizabeth Eyler Dang, National Institute of Allergy and Infectious Diseases Biostatistics Research Branch (25 min)
  • The multitude of group affiliations: Algorithmic Fairness, Loss Minimization and Outcome Indistinguishability”, Omer Reingold, Stanford University (25 min)
  • Modeling Covid-19 Immunological Reactions and Clinical Susceptibility in the Context of Long-Term Follow-up of a Prospective Cohort of Healthcare Workers, Noam Barda, Ben-Gurion University. (25 min)
  • “Drugs in Clinical Trials Out of Generative AI”, Petrina Kamya, Insilico Medicine (25 min)

3:10 PM – 3:25 PM

Break

3:25 PM – 4:50 PM

 

Panel Discussion: Generative AI in Drug Development

Moderator, David Sontag, MIT

  • Robert Ball, US FDA
  • Brian Caffo, Johns Hopkins University
  • Subha Madhavan, Pfizer Inc.
  • Anthony Philippakis, MIT  
  • Hoifung Poon, Microsoft Inc

 

4:50 PM – 5:00 PM

Closing Remarks & Acknowledgments, Demissie Alemayehu, Pfizer Inc. 

6:00 PM – 8:00 PM

Networking Reception