PS11: Perspective of Using Bayesian Statistics in Confirmatory Clinical Trials

Bayesian statistics is gaining traction in the field of clinical trials, offering a more flexible, adaptive, and informative approach compared to traditional frequentist methods. Its ability to integrate prior knowledge and provide probabilistic reasoning makes it particularly well-suited for complex drug development scenarios. The session will focus on the application of Bayesian methods in the context of regulatory submissions, particularly in the interaction with regulatory bodies such as the FDA and EMA. The discussion will cover how Bayesian techniques are used in clinical trial design, analysis, and interpretation to support more robust and efficient regulatory decision-making. This session will highlight both the opportunities and challenges in using Bayesian methods for regulatory submissions, as well as the growing acceptance and guidance from regulatory agencies in utilizing Bayesian statistics in clinical trials. The session will start with an overview of Bayesian statistics and its unique advantages in clinical trials, particularly when dealing with limited data or the need for adaptive trial designs. Next, we'll discuss the evolving perspectives of regulatory agencies such as the FDA, EMA, and other global regulators on the use of Bayesian methods in clinical trial submissions. It'll be followed by real-world studies where Bayesian methods were discussed in the regulatory submissions, highlighting key aspects such as prior selection, adaptive trial designs, simulation studies and probabilistic inference. The discussion will also highlight the need for transparency, rigor, and clear communication with regulatory bodies. Finally, the session will also reflect the key challenges and lessons learnt. The session will include experts from industry and FDA, followed by a moderated Q&A and open discussion.