Novel Study Designs in Precision Medicine - Basket, Umbrella and Platform Trials

Curr Rev Clin Exp Pharmacol. 2022;17(2):114-121. doi: 10.2174/1574884716666210316114157.

Abstract

The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypotheses within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration, while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.

Keywords: Precision medicine initiative; biomarker enrichment designs; drug development; master protocols; oncology trials; pharmacogenomic models.

Publication types

  • Review

MeSH terms

  • Clinical Trials as Topic* / methods
  • Drug Development
  • Humans
  • Precision Medicine* / methods
  • Records
  • Research Design*
  • Risk Factors