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C4 – Adaptive Platform Trials: From Concept to Completion

Chair: Hwanhee Hong, PhD (Duke University)

Instructors:
Joe Marion, PhD (Berry Consultants)
Liz Lorenzi, PhD (Berry Consultants)
Lindsay Berry, PhD (Berry Consultants)

Course Description:
Platform trials are a key innovation in clinical trial design that have changed the landscape of drug development in a variety of disease areas. At the core of an adaptive platform trial is a “master protocol” which provides the common design and protocol under which multiple therapies can be simultaneously evaluated. This short course aims to describe key methodological features and statistical/operational efficiencies of these designs through real world examples of adaptive platform trials. The examples will include the COVID-19 platform trial REMAP-CAP, the HEALY ALS platform trial for Amyotrophic Lateral Sclerosis, the ATTACC-CAP trial in community-acquired pneumonia, and the STEP platform trial for ischemic stroke. These trials range from early design phase to trials with thousands of patients enrolled and multiple results reported. They also are examples with a variety of trial design innovations in platform trials, including factorial designs, designs addressing heterogeneous treatment effects and enrichment, and trials that have been implemented under an IND with heavy regulatory interactions. Part of the discussion will focus on lessons learned, particularly focused on 1) key considerations for the design phase of the trial, 2) interactions with regulators, 3) insights gained during the implementation of ongoing platforms, and 4) the reporting of results from a platform trial. Upon completion of the course, participants will have a greater understanding of adaptive platform trials from design to implementation. 

Instructors:
Joe Marion, PhD
Senior Statistical Scientist
Berry Consultants

Joe Marion, PhD

Joe Marion is a Senior Statistical Scientist for Berry Consultants, where he specializes in designing Bayesian and adaptive clinical trials in a broad range of disease areas. Joe is particularly passionate about clinical trials in rare pediatric diseases. These heterogeneous diseases offer opportunities to create customized, disease-specific analyses that are more precise and powerful than traditional approaches. He also has substantial experience with platform trials and has been involved in the design and implementation of platform trials in diseases areas including oncology, neurology, and psychiatric disorders. Joe is interested in the technical and methodological side of statistics and brings a mathematical perspective to understanding and evaluating clinical trials. Joe earned his Ph.D. in Statistics from Duke University in 2018.

Liz Lorenzi, PhD
Statistical Scientist
Berry Consultants

Liz Lorenzi, PhD

Liz Lorenzi is a Statistical Scientist at Berry Consultants where she designs Bayesian and adaptive clinical trials. She has particular interest in applying innovative statistical approaches to challenging scientific questions and working with clients to find a unique solution to their study question. She has experience designing large platform trials, including the international COVID-19 trial, REMAP-CAP, as well as smaller specialized trials in a variety of disease areas. Prior to Berry Consultants, she received her PhD from Duke University in the Department of Statistical Sciences in 2019.

Lindsay Berry, PhD
Statistical Scientist
Berry Consultants

Lindsay Berry, PhD

Lindsay Berry is a Statistical Scientist at Berry Consultants specializing in the design of Bayesian and adaptive clinical trials. She serves as an elected officer of the Section on Biostatistics and Pharmaceutical Statistics for the International Society for Bayesian Analysis (ISBA). She earned her PhD in Statistical Science from Duke University. During the COVID-19 pandemic, Dr. Berry was heavily involved in the design of Bayesian adaptive platform trials, leading to publication of actionable findings in the Journal of the American Medical Association and the New England Journal of Medicine. Dr. Berry’s interests focus on innovative Bayesian methods for clinical trials including adaptive allocation procedures, historical borrowing, evaluation of heterogeneity of treatment effect, and disease progression modeling.