How can one optimally design a clinical trial program for a medical device for a FDA clearance/approval submission? Typically, a clinical trial program involves a pilot study that aims to establish basic safety information, and possibly a preliminary estimate of effectiveness, followed by a similar pivotal trial intended to comprehensively address safety and effectiveness of the device in the intended use population.
It is essential to examine some conditions under which a clinical trial program for a medical device would lend itself to an adaptive approach, including an analysis of:
• Which endpoints are suitable?
• Which adaptations are possibly useful in every clinical trial setting?
• Which adaptations are not likely to appear to be controversial to a regulator?
• When might Bayesian methods be applicable?
What are the new opportunities for Adaptive Designs in Medical Device Studies?
• Sample size re-estimation: because the pre-planned sample size is based on highly uncertain effectiveness of device or control
• Early stopping for effectiveness, futility, or safety: Bayesian interim monitoring has become an accepted practice for CDRH
• Changing the allocation during the study: as new technology becomes available during a trial, randomization to the control may become infeasible
• Covariate-Adjusted Response-Adaptive Randomization for Trials of a Drug with a Companion Diagnostic Biomarker
• Adaptive selection of a subgroup: promising subgroup for a therapeutic device or sensitive subgroup defined by a biomarker
What are the challenges for use of Adaptive Design in Medical Device Trials?
• Who will perform the interim analysis? What is the Sponsor involvement?
• How is a recommended adaptation implemented so that trial integrity is maintained?
• What are valid statistical analyses to perform at the end of the trial?
During OneMedForumNY 2012, Aptiv Solutions led a session discussing these and similar questions. This module explores the advantages of adaptive designs in light of growing difficulty in implementing successful clinical trials, both as a result of regulatory practices and demand for speed and efficiency. In this module OneMedPlace has produced case studies with industry insiders and editorial pieces exploring these changing times. Check the right column for more!
Faculty:
Michael L. Feldstein, PhD, Senior Vice President, Medical Devices, Aptiv Solutions
Michael brings over forty years of experience in the design and analysis of clinical trials. He provides high-level strategic guidance to emerging and established medical device clients in the areas of study design and biostatistics. Prior to joining Aptiv Solutions (previously Medical Device Consultants, Inc.) in 1996, he was a professor of Biostatistics at Harvard University School of Public Health, where he directed the department’s Consulting Laboratory. He has authored or co-authored over eighty publications in medical journals and has given numerous presentations to professional societies. He is a member of the American Statistical Association and holds a Ph.D. in statistics from the State University of New York at Buffalo.
Vlad Dragalin, PhD, Senior Vice President, Clinical Trial Innovation Strategies Aptiv Solutions
As a member of the Aptiv Solutions Innovation Center, Vlad and his team collaborate with drug and medical device clients, and regulatory authorities to provide consulting on best practices for the use of adaptive designs, including trial design, simulation and execution. Prior to joining Aptiv Solutions, Vlad held senior positions at Quintiles, Wyeth Research (now part of Pfizer), and GlaxoSmithKline. Vlad is an elected member of PhRMA Biostatistics and Data Management Technical Group. He is a Member of the American Statistical Association, the Institute of Mathematical Statistics, the Drug Information Association, and an Associate Editor of Journal of Biopharmaceutical Statistics. Vlad was actively involved in the PhRMA Working Group on Adaptive Designs and the PhRMA Working Group on Adaptive Dose Ranging Studies.
