Understanding AI/ML in the Drug Development Lifecycle


FDA Convening

Understanding AI/ML in the Drug Development Lifecycle

Meeting Objective

Artificial Intelligence (AI), including machine learning (ML), is becoming more integrated in all phases of drug development—from drug discovery and clinical research to post-marketing surveillance. This expert workshop focused on AI/ML innovations in different phases of drug development, with an emphasis on those areas that have the greatest need for regulatory clarity. Discussion will be rooted in specific examples from various phases in the drug development process.

Funding Acknowledgement

This workshop is supported by the Food and Drug Administration (FDA) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award U01FD006807 totaling $2,575,023 with 100 percent funded by FDA/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by FDA/HHS, or the U.S. Government.

Duke-Margolis Planning Team

Erin Soule Headshot

Erin Soule, PhD

Assistant Research Director


Christina Silcox, PhD

Research Director, Digital Health
Adjunct Assistant Professor
Senior Team Member
Margolis Core Faculty