A summarized version of this DRAFT GUIDANCE- by Teresa Gallagher
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 trial.
The primary focus of this guidance is on adaptive designs for clinical trials intended to support the effectiveness and safety of drugs. This guidance will replace the 2010 draft guidance for industry, Adaptive Design Clinical Trials for Drugs and Biologics.
For the purposes of this guidance, an adaptive design is defined as a clinical trial design that allows for prospectively planned modifications to one or more aspects of the design based on accumulating data from subjects in the trial. An interim analysis is any examinations of the data obtained from subjects in a trial while that trial is ongoing, and is not restricted to cases in which there are formal between-group comparisons.
The term prospective, for the purposes of this guidance, means that the adaptation is planned and details specified before any comparative analyses of accumulating trial data are conducted. In nearly all situations, potential adaptive design modifications should be planned and described in the clinical trial protocol (and a separate statistical analysis plan, if used) prior to initiation of the trial.
A non-adaptive trial is a clinical trial without any prospectively planned opportunities for modifications to the design.
Adaptive designs can provide a variety of advantages over non-adaptive designs. These advantages arise from the fundamental property of clinical trials with an adaptive design: they allow the trial to adjust to information that was not available when the trial began. The potential advantages fall into the following categories: statistical efficiency, and ethical considerations.