FDA Guidance on Statistical Methods for Clinical Trials

The U.S. Food and Drug Administration (FDA) published a draft guidance designed to facilitate statistical methods for clinical trials. This will help drug developers to make better use of available data, conduct more efficient clinical trials, and deliver safe and effective treatments to patients sooner.

Background

The guidance provides recommendations on the appropriate use of Bayesian methods, with an emphasis on the use of these methods to support primary inference. Bayesian methods may be especially valuable for sponsors targeting rare or pediatric indications, where patient populations are smaller. These approaches use a different framework from traditional statistical approaches: In a Bayesian analysis, data from a study are combined with relevant prior information to form a new distribution that can be used for inference and to draw conclusions about safety and efficacy.

Examples of Bayesian calculations used in various ways in clinical trials can include:

• Determining futility or success earlier in adaptive trials
• Informing design elements like dose selection in subsequent trials
• Incorporating information from other sources, such as previous clinical study data, real-world evidence (RWE), and external or nonconcurrent controls
• Facilitating subgroup analyses
• Supporting primary inference in a trial

For more information please see the publication of this guidance: Use of Bayesian Methodology in Clinical Trials of Drugs and Biological Products.