Most of us are familiar with the concept of platform clinical trials as they have gained popularity in the recent years. It is an experimental infrastructure to evaluate multiple treatments and/or combinations of treatments. They have garnered substantial support and have provided an efficient way of testing multiple compounds in a single and consistent framework.
Dr. Kyle Wathen, Vice President of Scientific Strategy & Innovation at Cytel, presented a webinar this week in our Innovations in Bayesian Clinical Trials Virtual Symposium. He reviews platform clinical trials, protocol structure, the potential benefits and risks, and introduces the concept of a platform clinical trial that utilizes Bayesian modeling to make Go/No-Go decision.
Benefits Vs. Risk of Platform Trials
Platform trials can offer unique advantages over the more commonly used traditional designs. They can possibly reduce the number of patients on the placebo/control arm, and all treatments leverage the common control group. There is also a possibility to have a greater number of sites allowing for quicker enrollment, thus the recruitment can go faster. Moreover, often times it will be able to give you the ability to look at performance of novel endpoints across multiple compounds.
Platform trials generally incur higher costs and need more resources. As these designs are novel, the health authorities you may be working with or the IRBs (institutional review board) may impede transition to compound 2, 3 and so on. And lastly, Platform trials often see an explosion in the number of designs to compare and thereby heavy computation is needed which is not a trivial task. However, with an expert statistician, all of these risks can be mitigated.
Bayesian modeling to make Go/No-Go decision in Platform Trials
Traditionally, statisticians have used p-values and confidence intervals to construct Go/No-Go (GNG) decision rules. However, moving to the Bayesian paradigm opens up exciting new possibilities for clinical development strategy. GNG decision-making is most effective when combined with powerful simulations. The Bayesian paradigm seems to provide several benefits for conducting such simulations with accurate results. Dr. Kyle Wathen uses an example where a platform clinical trial utilizes Bayesian modeling to make Go/No-Go decision.
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About the Author:
Mansha Sachdev specializes in content creation and knowledge management. She holds an MBA degree and has 11 years of experience in handling various facets of marketing, across industries. At Cytel, Mansha is a Content Marketing Manager and is responsible for producing informative content that is related to the pharmaceutical and medical devices industries.
