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Session 2: Synthetic Controls and Causal Inference
Session Chair(s)
Hana Lee, PhD
Senior Statistical Reviewer, OB/OTS/CDER
FDA, United States
Ruthie Davi, PhD, MS
Vice President, Data Science and Statistician
Medidata, a Dassault Systèmes Company, United States
This session will explore the use of propensity scores or other balancing algorithms to create synthetic or external controls to aid in medical product development. Examples include
- alignment of a synthetic control to a single arm trial early in development to facilitate go/no-go decisions
- utilizing a synthetic control arm for enhanced understanding of a treatment effect observed in a single arm trial to support an accelerate approval submission
Learning Objective : - Define what a synthetic control is
- Describe how a synthetic control may enhance the interpretation of a single arm trial
- Identify uses of synthetic controls in the regulatory and nonregulatory spaces
Speaker(s)
Use of a Synthetic Control Arm in Medical Product Development
Xiang Yin, PhD
Medidata Solutions, A Dassault Systèmes Company, United States
Vice President, Statistics and Regulatory Sciences
Regulatory Review Experience of Single-Arm Studies Utilizing External Trial Information
Yeh-Fong Chen, PhD
United States
Mathematical Statistician (Team Lead), Office of Translational Sciences, CDER
Real-world Evidence to Support Regulatory Decision-making for Medicines: Considerations for External Control Arms.
Mehmet Burcu, PhD, MS, FISPE
Merck & Co., Inc., United States
Senior Director, Epidemiology
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