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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)
Antara Majumdar, PHD
Director, Oncology Statistics, GlaxoSmithKline, United States
Causal Inference in Clinical Drug Development: Industry Update
Shia Kent, PHD
Epidemiologist, Pharmacovigilance Epi and Causal Inference Team, Amgen, United States
Methodological Challenges and Potential Solutions When Conducting External Control Studies Intended for Causal Inference
Pallavi Mishra-Kalyani, PHD, MS
Deputy Division Director, DBV, OB, CDER, FDA, United States
Regulatory Considerations and Case Studies of Externally Controlled Trials
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