October 13-14 | UC Berkeley
2026 Annual Symposium on Risks and Opportunities of AI in Pharmaceutical Medicine
Accelerating Drug Development Through Agentic AI
About the Symposium
The 2026 Annual Symposium on Risks and Opportunities of AI in Pharmaceutical Medicine is jointly sponsored by the American Statistical Association, Amgen, Genentech, Northeastern University, Novo Nordisk, Pfizer, and the University of California at Berkeley. The symposium will take place October 13–14 at the University of California at Berkeley.
Where Will the AI Revolution Take Pharmaceutical Science?
Our world increasingly relies on data and computing to create knowledge, to make critical decisions, and to better predict the future. Data science has emerged to support these data-driven activities by integrating and developing ideas, concepts, and tools from computer science, engineering, information science, statistics, and domain fields. Data science now drives fields as diverse as biology, astronomy, material science, political science, and medicine—not to mention vast tracts of the global economy, key government activities, and quotidian social and societal functions.
The pharmaceutical enterprise has been slower to respond, especially to the rapid developments in AI, but tectonic shifts are underway in approaches to the discovery, development, evaluation, registration, monitoring, and marketing of medicines for the benefit of patients and the health of the community.
While there is much discussion about the potential of AI and modern machine learning tools to transform the drug development paradigm, there is a growing recognition of the paucity of research about the opportunities, inevitable pitfalls, and unintended consequences of the digital revolution in this important area of application. As we move toward personalized and truly evidence-based medicine, the use of AI and machine learning to optimize drug deployment raises a whole different set of challenges.
This forum is, therefore, expected to serve as a platform for distinguished statisticians, data scientists, regulators, and other professionals to address the challenges and opportunities of AI in pharmaceutical medicine; to foster collaboration among industry, academia, regulatory agencies, and professional associations; and to propose recommendations with policy implications for proper implementation of AI in promoting public health.
Key Details
Program Co-Chairs
Demissie Alemayehu, Pfizer
David Madigan, Northeastern University
Mark van der Laan, University of California, Berkeley
Contact Us
For program-related queries, please reach out to Demissie Alemayehu, Demissie.Alemayehu@pfizer.com.
Date & Time
October 13–14, 2026
Day 1: 12:00 pm-5:00 pm PT
Day 2: 7:00 am-8:00 pm PT
Location
University of California, Berkeley
Day 1
Tutorials
Day 2
Meeting
Reception
Keynote Speakers
Narimon Honarpour
Senior Vice President, Global Development, Amgen
“AI in Pharma”
View Bio
Robert Tibshirani
Professor of Biomedical Data Science and Statistics, Stanford University
“Personalized Medicine and Treatment Optimization”
View Bio
Special Guest Speaker
Jennifer Tour Chayes
Dean, College of Computing, Data Science, and Society, University of California at Berkeley
View Bio
Call for Posters
The AIPM poster session provides an opportunity for students and early-career researchers to present emerging research in topics related to AI research related to pharmaceutical medicine.
Important Dates
Poster abstract submission deadline: June 30, 2026
Notification of acceptance: August 15, 2026
Poster session: October 14, 2026
Submission Guidelines
Please complete the AIPM poster intake form by June 30, 2026. Submit an abstract of 150–300 words via a PDF file. Outline the objectives, methods, and key contributions of your work.
Poster Format: Accepted presenters will be asked to prepare a poster (recommended size: 36” x 48”, portrait or landscape). Further details will be provided upon acceptance.
Submission and Inquiries: Contact Larry Han or Javier Cabrera.