FDA Compliancy for Adaptive Trial Implementation

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Tuesday, November 09, 2010
12:00 PM - 01:00 PM EST
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A major concern among many drug companies is that precious patient resources on therapies and doses are potentially wasted and are unlikely to be successful. Adaptive designs are created to prevent waste, speed up drug development and increase accuracy in identifying the appropriate dose, regimen and indication.

The adaptive approach also allows for addressing questions that could never be addressed in a balanced randomised trial. Individual questions such as discriminating the effect of one dose from that of another dose may not have high power, but some power may be better than none.

As a leader in the adaptive revolution, the FDA recently issued a draft guidance for industries regarding the use of adaptive designs in the regulatory setting, focusing principally on “adequate and well controlled” phase III trials.1

Furthermore, the FDA’s Critical Path Initiative encourages the use of (i) innovative clinical trial design and (ii) biomarkers in the early phases of drug development. 2

Adaptive design differs from a traditional design in that it uses accumulating results in the trial to modify the trial’s course. All adaptations should be completely specified in advance of the trial, at the design stage, so that operating characteristics can be calculated.

In this webinar, participants will learn:

  • Using a Bayesian approach for developing adaptive designs
  • Practical examples of designing and conducting clinical trials using adaptive designs for regulatory approval.
  • The benefits and challenges of adaptive designs
  • The limitations and disadvantages of adaptive designs
  • The implications of the FDA Guidance on late phase adaptive trials
  • Adaptive designs in early phase trials
  • Adaptive designs in pivotal Phase 3 studies


1. http://www.fda.gov/downloads/DrugsGuidanceComplianceRegulatoryInformation/Guidances/UCM201790.pdf
2. http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/default.htm 


Donald Berry, Ph.D
Head of the Division of Quantitative Sciences, Chair, Department of Biostatistics
M.D. Anderson Cancer Center

Donald Berry holds the Frank T. McGraw Memorial Chair for Cancer Research at The University of Texas M. D. Anderson Cancer Center, where he is Head of the Division of Quantitative Sciences and Chairman of the Department of Biostatistics. He serves as a faculty statistician on the Breast Cancer Committee of the Cancer and Leukemia Group B (CALGB), a national oncology group. In this role he has designed and supervised the conduct of many large U.S. intergroup trials.

Through Berry Consultants, LLC he has consulted with many pharmaceutical and medical device companies on clinical trial design and analysis issues. He is well known as a developer of Bayesian adaptive designs that minimize sample size while increasing the likelihood of detecting drug activity, efficiently using information that accrues over the course of the trial.

Since moving to M.D. Anderson Cancer Center in 1999 his department has designed over 300 clinical trials that take a Bayesian approach. He is co-developer (with Giovanni Parmigiani) of BRCAPRO, a widely used program that provides individuals’ probabilities of carrying mutations of breast/ovarian cancer susceptibility genes BRCA1 and BRCA2.

Dr. Berry received his Ph.D. in statistics from Yale University, and previously served on the faculty at the University of Minnesota and at Duke University, where he held the Edger Thompson Professorship in the College of Arts and Sciences.

Dr. Berry is the author of several books on biostatistics and over 300 published articles, including first-authored articles in the New England Journal of Medicine, the Journal of the American Medical Association, and Nature. Dr. Berry has been the principal investigator for numerous research grants from the National Institutes of Health and the National Science Foundation. He is a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics.

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