Back to: FDA Regulatory Education for Industry (REdI) 2024 Conference – Plenary and Drugs Track
Presenter
Tala Fakhouri, PhD, MPH
Associate Director for Policy Analysis
Office of Medical Policy (OMP)
Center for Drug Evaluation and Research (CDER)
US Food and Drug Administration (FDA)
Tala H. Fakhouri, PhD, MPH, is the Associate Director for Policy Analysis at the Food and Drug Administration. Dr. Fakhouri manages a team tasked with developing, coordinating, and implementing medical policy with a focus on the use of Artificial Intelligence (AI) in drug development. She also contributes to the development of medical policy related to real-world evidence (RWE) for medical product development. In 2023, She was selected by the Office of Management and Budget to serve on the Federal Committee for Statistical Methodology for her expertise in statistical methods.
Prior to joining FDA, Dr. Fakhouri served as Chief Statistician for the CDC’s flagship population survey, the National Health and Nutrition Examination Survey (NHANES), which is recognized as the premier source of nationally representative data on the health of the nation. Prior to NHANES, she served as an Epidemic Intelligence Service Officer with the CDC, and deputy lead for health surveys at ICF-Macro International. Dr. Fakhouri published over 30 government reports, peer-reviewed papers, and book chapters.
Dr. Fakhouri earned a Ph.D. in Oncological Sciences from The Huntsman Cancer Institute at the University of Utah, an MPH in Epidemiologic and Biostatistical Methods from the Johns Hopkins University School of Public Health, and a postdoctoral fellowship in molecular biology and genetics from Harvard University, and holds a BSc Medical Technology form the Jordan University of Science and Technology
Abstract
In this presentation and Q&A session, Tala Fakhouri discusses the Food and Drug Administration’s (FDA) perspective on the use of artificial intelligence (AI) and machine learning (ML) in drug development. She explains that AI is being utilized across all stages of the drug development lifecycle, from initial discovery and non-clinical research to clinical trials, pharmaceutical manufacturing, and post-market safety surveillance, noting its potential to accelerate processes. The FDA has seen a significant increase in regulatory submissions incorporating AI/ML components, particularly in clinical research and across various therapeutic areas like oncology. The agency’s goal is to promote the responsible adoption of these emerging technologies to facilitate the development of safe and effective therapies. Driven by a recent Executive Order, the FDA is actively working on developing a risk-based regulatory framework for AI in drug development, collaborating across medical product centers and engaging with external stakeholders through workshops and discussion papers. A draft guidance document is anticipated this year to provide clarity, informed by the agency’s experience with submissions and feedback on key issues like data quality, model performance, transparency, and harmonization needs.