In the 2010 draft FDA ‘Guidance for Industry on Adaptive Design Clinical Trials for Drugs and Biologics', the agency makes an important distinction between ‘well understood’ and ‘less well understood’ adaptive designs.
‘Well understood” adaptive designs may include such approaches as adaptation of eligibility criteria, adaptation for stopping early and adaptations to maintain study power based on blinded interim analyses of aggregate data. For these 'well-understood designs', there is little concern from the FDA about their potential to be implemented in adequate and well-controlled trials. On the other hand, at the time of the drafting of the guidance at least, ‘ less well understood designs' (which include such approaches as adaptations for dose selection studies, adaptation of patient population based on treatment-effect estimates, and adaptation for end-point selection based on interim estimates of treatment effect) gave greater concern. Interestingly, the FDA Adaptive Designs for Medical Device Clinical Studies : Guidance for Industry and Food and Drug Administration Staff does not adopt this distinction.
A recent article, Addressing Challenges and Opportunities of “Less Well-Understood” Adaptive Designs (He et al 2016) (1) takes a look at some of the perceived challenges of these designs and ways in which they may be overcome. The publication is the result of work by a best practice sub-team formed by the DIA Adaptive Design Scientific Working group in January 2014. Cytel's Yannis Jemiai is a member of this group, and one of the co-authors of the article.
In this blog, we take a look at a few of the challenges outlined and some of the suggested mitigations. One aspect covered in the publication is seamless designs- and given the scope we'll devote a separate blog to this area.