New FDA draft guidance encourages use of adaptive designs for clinical trials and biologics

The FDA has issued their draft guidance on “Adaptive Design Clinical Trials for Drugs and Biologics”. This has been a long awaited draft guidance and a valuable resource. The last couple years some sponsors have been leery of doing adaptive designs for fear that the FDA was not receptive to the idea of adaptive trials. This guidance demonstrates what we have known for a while — that the FDA is not only accepting they are encouraging. Adaptive trials are a big step forward for all parties involved: better for subjects in and out of the trial, more efficient with time and costs, and are scientifically more powerful, which is better for the FDA and science in general.

In particular the guidance refers to “Complex Adaptive Designs,” which we have been involved with for 10 plus years. We were particularly excited with the following reference to Bayesian statistics and the utilization of predictive probabilities…

Some modeling and simulation strategies lend themselves to a Bayesian approach that might be
useful. The Bayesian framework provides a way to posit models (i.e., priors) for the study
design and the adaptive choices as they might probabilistically occur, and may aid in evaluating
the impact of different assumed distributions for the parameters of the model and modeled
sources of uncertainty. The Bayesian approach can be a useful planning tool at the study design
stage to accommodate a range of plausible scenarios. Using Bayesian predictive probability,
which depends upon probabilities of outcomes conditional on what has been observed up to an
interim point in the adaptive study, may aid in deciding which adaptation should be selected,
while the study design is still able to maintain statistical control of the Type I error rate in the
frequentist design.” (Lines 1313-1322)

In addition the draft guidance refers to the need and benefits of clinical trial simulations (lines 1291-1299)

Many of the less well-understood and complex adaptive designs involve several adaptation
decision points and many potential adaptations. For study designs that have multiple factors to
be simultaneously considered in the adaptive process, it is difficult to assess design performance
characteristics and guide sample size planning or optimal design choices because these
characteristics might depend upon the adaptations that actually occur. In these cases, trial
simulations performed before conducting the study can help evaluate the multiple-trial design
options and the clinical scenarios that might occur when the study is actually conducted, and can
be an important planning tool in assessing the statistical properties of a trial design and the
inferential statistics used in the data analysis.

You can find the original document in pdf format here: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM201790.pdf