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Causal Inference Methodology in Drug Development
Session Chair(s)
Pallavi Mishra-Kalyani, PhD, MS
Deputy Division Director, DBV, OB, CDER
FDA, United States
This session will explore special topics in causal inference. Presenters will describe trial design and analysis issues in drug development, related to both randomized trials and real-world data (RWD), that may benefit from statistical methodology to allow for better and more accurate generation of evidence with respect to drug treatment effects.
Learning Objective : Describe various statistical approaches to handle complex design and analysis issues in drug development. Explain use case examples for illustration for causal inference methods.
Speaker(s)
Causal Inference in Clinical Drug Development: Industry Update
Antara Majumdar, PhD
GlaxoSmithKline, United States
Director, Oncology Statistics
Methodological Challenges and Potential Solutions When Conducting External Control Studies Intended for Causal Inference
Shia Kent, PhD
Amgen, United States
Epidemiologist, Pharmacovigilance Epi and Causal Inference Team
Regulatory Considerations and Case Studies of Externally Controlled Trials
Pallavi Mishra-Kalyani, PhD, MS
FDA, United States
Deputy Division Director, DBV, OB, CDER
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