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Unleash the Potential of Synthetic Data and Digital Twins Using AI to Accelerate Drug Development
Wednesday June 18, 2025 1:45pm - 2:45pm EDT
TBD
Component Type: Session
Level: Basic

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 Objectives

Describe what synthetic data and digital twins are; Discuss ways to apply AI to generate synthetic data and digital twin; Illustrate the potential of synthetic data and digital twins in medical product development.

Chair

Di Zhang, PhD

Speaker

Academic Perspective
Khaled El Emam, PhD

Industry Perspective
Arman Sabbaghi, PhD, MA

Statistical Challenges
Ye Li, PhD


Speakers
KE

Khaled El Emam

Professor, University of Ottawa, Canada
Dr. Khaled El Emam is the Canada Research Chair (Tier 1) in Medical AI at the University of Ottawa, where he is a Professor in the School of Epidemiology and Public Health. He is also a Senior Scientist at the Children’s Hospital of Eastern Ontario Research Institute, and Scholar-in-Residence... Read More →
YL

Ye Li

Mathematical Statistician, OTS, CDER, FDA, United States
Dr. Ye Li is a mathematical statistician in the Office of Biostatistics, Center for Drug Evaluation and Research, FDA. In this role, she performs statistical reviews on submissions of neurology products. Dr. Li worked in Office of Quality Surveillance, Center for Drug Evaluation and... Read More →
AS

Arman Sabbaghi

Head of Biostatistics Research, Unlearn, United States
AS

Arman Sabbaghi

Associate Professor of Statistics, Purdue University, United States
Dr. Arman Sabbaghi is a creative and principled statistical scientist with over a decade of experience at the intersection of AI and statistical innovation. He has been recognized for pioneering the combination of AI/ML algorithms with causal, Bayesian, and experimental design methods... Read More →
DZ

Di Zhang

Associate Director of RWE Statistics, Teva, United States
Di Zhang is the Associate Director of RWE Statistics and Data Science at Teva Pharmaceuticals. Her research interests include causal inference, RWE study designs and methods, the utilization of machine learning in clinical trials and real-world applications and leveraging real-world... Read More →
Wednesday June 18, 2025 1:45pm - 2:45pm EDT
TBD Walter E. Washington Convention Center 801 Allen Y. Lew Place, NW Washington, DC 20001-3614 USA
  11: Statistics-Data Science, Session |   03: Data-Tech, Session

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