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Unleash the Potential of Synthetic Data and Digital Twins Using AI to Accelerate Drug Development
Session Chair(s)
Di Zhang, PhD
Associate Director of RWE Statistics
Teva, United States
This session aims to explore the potential and innovative applications of these technologies in the realm of drug development, featuring speakers from health authorities, academia and industry.
Learning Objective : Describe what synthetic data and digital twins are; Apply AI to generate synthetic data and digital twin; Illustrate the potential of synthetic data and digital twins in medical product development.
Speaker(s)
Academic Perspective
Khaled El Emam, PhD
University of Ottawa, Canada
Professor
Industry Perspective
Arman Sabbaghi, PhD, MA
Purdue University, United States
Associate Professor of Statistics
Statistical Challenges
Representative Invited
FDA, United States
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