Adaptive Designs for Clinical Trials of Drugs and Biologics Guidance for Industry
I. INTRODUCTION AND SCOPE 2
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.2 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.
The primary focus of this guidance is on adaptive designs for clinical trials intended to support the effectiveness and safety of drugs. The concepts contained in this guidance are also useful for early-phase or exploratory clinical trials as well as trials conducted to satisfy post-marketing commitments or requirements.
In general, FDA’s guidance documents do not establish legally enforceable responsibilities. Instead, guidances describe the Agency’s current thinking on a topic and should be viewed only as recommendations, unless specific regulatory or statutory requirements are cited. The use of the word should in Agency guidances means that something is suggested or recommended, but not required.
II. DESCRIPTION OF AND MOTIVATION FOR ADAPTIVE DESIGNS
A. Definition
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.
B. Important Concepts
The following are descriptions of important concepts used in this guidance:
An interim analysis is any examination of 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 observed data used in the interim analysis can include one or more types, such as baseline data, safety outcome data, pharmacokinetic, pharmacodynamic or other biomarker data, or efficacy outcome data.
A non-comparative analysis is an examination of accumulating trial data in which the treatment group assignments of subjects are not used in any manner in the analysis. A comparative analysis is an examination of accumulating trial data in which treatment groups are identified, either with the actual assigned treatments or with codes (e.g., labeled as A and B, without divulging which treatment is investigational).4 The terms unblinded analysis and blinded analysis are also sometimes used to make the distinction between analyses in which treatment assignments are and are not identified, respectively. We avoid the terms unblinded analysis and blinded analysis in this guidance because these terms can misleadingly conflate knowledge of treatment assignment with the use of treatment assignment in adaptation algorithms. An interim analysis can be comparative or non-comparative regardless of whether trial subjects, investigators, and other personnel such as the sponsor and data monitoring committee (DMC) have knowledge of individual treatment assignments or access to comparative results by treatment arm. For example, it is possible to include adaptations based on a non-comparative analysis even in open-label trials, but ensuring that the adaptations are completely unaffected by knowledge of comparative data presents additional challenges. The importance of limiting access to comparative interim results is discussed in detail in section VII. of this guidance.