Adaptivity in drug discovery and development

The development of novel drugs is becoming increasingly challenging, inefficient, and costly, as acknowledged by all major stakeholders of pharmaceutical products. Adaptive designs have attracted considerable attention in recent years, as they promise an increase in efficiency of the drug development process by making better use of the observed data. The key idea of adaptive designs is to use data accumulating from an ongoing experiment to decide on how to modify certain design aspects and better address the question(s) of interest and/or adjust for incorrect assumptions. When planned carefully and applied in appropriate situations, a number of adaptive designs allow for scientifically sound conclusions: early stopping either for futility or for success, sample size reassessment, treatment selection, etc. Most of the current discussions regarding adaptive designs, focus however, on clinical trial applications in the (late) development phase of a novel drug. The aim of this review is to broaden this perspective and to demonstrate that adaptivity is a fundamentally important concept that can be applied to many different stages of drug discovery and development. We review the major statistical methods available for planning and analyzing adaptive designs and then move through the drug discovery and development process and identify possible opportunities for adaptivity. To illustrate the ideas, we refer to examples and case studies from the literature, where available. A brief discussion about regulatory perspectives, operational aspects, and some potential hurdles is also given. Drug Dev Res 70, 2009. © 2009 Wiley‐Liss, Inc.

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