The US Food and Drug Administration (FDA) last week finalized guidance on adaptive clinical trial designs for drugs and biologics. This document provides guidance to sponsors and applicants submitting investigational new drug applications (INDs), new drug applications (NDAs), biologics licensing applications (BLAs), or supplemental applications on the appropriate use of adaptive designs for clinical trials to provide evidence of the effectiveness and safety of a drug or biologic. The guidance describes important principles for designing, conducting, and reporting the results from an adaptive clinical trial. The guidance also advises sponsors on the types of information to submit to facilitate FDA evaluation of clinical trials with adaptive designs, including Bayesian adaptive and complex trials that rely on computer simulations for their design.
Finalized Guidance
According to the FDA, the design, conduct, and analysis of an adaptive clinical trial intended to provide substantial evidence of effectiveness should satisfy four key principles: the chance of erroneous conclusions should be adequately controlled, estimation of treatment effects should be sufficiently reliable, details of the design should be completely prespecified, and trial integrity should be appropriately maintained. While all clinical trials intended to provide substantial evidence of effectiveness should satisfy these four principles, the FDA’s guidance outlines further considerations specific to adaptive designs.
The FDA further addresses different types of clinical trial designs in which there are prespecified rules for stopping the trial or modifying the design based on interim analyses of comparative data. The agency notes there are a few important concepts that are generally applicable to the sections that follow. First, in contrast to adaptations based on non-comparative data, adaptations based on comparative data often directly increase error probability and induce bias in treatment effect estimates. Therefore, statistical methods should take into account the adaptive trial design. Second, when adaptations are based on comparative interim analyses, additional steps are critical to ensure appropriate trial conduct. Finally, stopping or adaptation rules can be specified on a variety of different scales, such as the estimate of treatment effect, fixed sample p-value, conditional probability of trial success, Bayesian posterior probability that the drug is effective, or Bayesian predictive probability of trial success.
Regarding trial integrity, FDA recommends that access to comparative interim results be limited to individuals with relevant expertise who are independent of the personnel involved in conducting or managing the trial and have a need to know. Ensuring that patients, investigators and their staff, and sponsor personnel do not have access to comparative interim results serves two important purposes, according to the agency. First, it provides the greatest confidence that potential unplanned design modifications are not motivated in any way by accumulating data. Second, limitation of access to comparative interim results provides the greatest assurance of quality trial conduct. Issues with trial conduct are difficult to predict and generally impossible to adjust for in statistical analyses. Therefore, a clinical trial with an adaptive design should, according to FDA, include rigorous planning, careful implementation, and comprehensive documentation of approaches taken to maintain confidentiality of comparative interim results and to preserve trial integrity.05