Chair: Rakhi  Kilaru  (PPD)

Instructor: John Scott (FDA)

In this short course, I  will describe the new FDA final guidance on adaptive designs.  The 2019 document, which replaced the 2010 draft, provides guidance on the appropriate use of adaptive designs for clinical trials to provide evidence of the effectiveness and safety of a drug or biologic.  I will describe the key principles for designing, conducting, analyzing, and reporting the results from a clinical trial with an adaptive design.  I will also address a number of special topics, such as the use of simulations in adaptive design planning and the use of Bayesian adaptive design features.  At the conclusion of this short course, participants should be able to:

  • Define an adaptive design and discuss important advantages and limitations of adaptive designs.
  • Describe four important principles for clinical trials with an adaptive design.
  • Provide examples of the types of design modifications that can be incorporated into an adaptive design.
  • Outline the types of information FDA needs to evaluate an adaptive design and to evaluate results from a trial with an adaptive design.
  • Discuss special considerations in adaptive design, including the use of simulations, the use of Bayesian features, adaptations in time-to-event settings, and adaptations based on a potential surrogate or intermediate endpoint.

John Scott, PhD
Food and Drug Administration
John Scott is Director of the Division of Biostatistics in the FDA’s Center for Biologics Evaluation and Research, where he has also served as Deputy Director and as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School.  He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment.  He has been a lead, co-lead or CBER lead for a number of FDA policy documents, including the Guidance on Adaptive Design Clinical Trials for Drugs and Biologics, the draft Guidance on Interacting with FDA on Complex Innovative Trial Designs, ICH E9(R1) Addendum on Estimands and Sensitivity Analyses, and ICH E20 Adaptive Clinical Trials.  He holds a Ph.D. in Biostatistics from the University of Pittsburgh, an M.A. in Mathematics from Washington University in St. Louis, and a B.A. in Liberal Arts from Sarah Lawrence College and is Editor of the journal, Pharmaceutical Statistics.