FDA Designates Empirically Based Bayesian Emax Models for Dose Finding as ‘Fit-For-Purpose’: On August 5, 2022, the U.S. Food and Drug Administration (FDA) designated ‘Empirically Based Bayesian Emax Models for Dose Response Design and Analysis’ as a statistical methodology for dose-finding studies as ‘fit-for-purpose’ (FFP) in the context described below.
The importance of adequately understanding the dose-response relationship is well recognized in drug development. Dose-finding studies, however, are often designed with a small number of doses and a narrow dose range using suboptimal analysis techniques. Inadequate dose exploration due to limited understanding of the dose-response relationship can lead to failed late-stage trials. To address this issue, the use of empirically based Bayesian Emax models with supporting software has been proposed to improve the design and analysis of clinical trials whose primary purpose is to characterize the relationship between efficacy and dose to guide dose selection for further development.
A multidisciplinary team, with representation from both the Office of Biostatistics and the Office of Clinical Pharmacology in the Office of Translational Sciences within the Center for Drug Evaluation and Research, has determined that an empirically based Bayesian Emax model, including the goodness-of-fit (GOF) statistic, can be designated as FFP under the following conditions:
Additional details on this FFP designation can be found in the Determination Letter and Multidisciplinary Review posted on the FDA’s Drug Development Tools: Fit-for-Purpose Initiative website. The FDA’s FFP Initiative provides a pathway for the regulatory acceptance of dynamic tools for use in drug development programs. For more information on the initiative as well as other drug development tools designated as FFP, please refer to the FDA’s FFP website.
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