Advancing Bayesian Methods in Clinical Trials

In a recent video interview with Applied Clinical Trials, David Morton, PhD, director of biostatistics, Certara, discussed how the FDA’s increased support for Bayesian methods is expected to drive a shift from traditional frequentist approaches toward more flexible, probability-based trial designs. He emphasized the growing role of external data borrowing, adaptive decision-making, and simulation-driven planning in improving efficiency, particularly in rare disease and small population studies. Morton also highlighted the need for stronger upfront design, including justification of prior data and robust analytical frameworks, as well as greater cross-functional alignment and early regulatory engagement to support transparency, reduce uncertainty, and accelerate more data-driven development models.

Editor's note: This transcript is a lightly edited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

ACT: What is most operationally significant about the FDA’s increased support for Bayesian methods in clinical trials?

Morton: I think we’re moving a little bit beyond being purely frequentist. So I think it’s going to be a shift from that frequentist mindset over to a Bayesian mindset. There’s going to be a lot of innovative approaches becoming more regulatory acceptable from the FDA.

The greater openness to alternative evidence frameworks is really important, because we see this in the industry all the time. We get a lot of questions about whether we can borrow external controls. Leveraging existing data and borrowing information from previous trials or external controls can reduce the necessary sample size of a current trial.

So it’s very flexible and efficient. These methods have been around for a while, and there’s a lot of research on them. Operationally, I think this will reduce regulatory uncertainty and encourage sponsors to consider Bayesian designs earlier, on the front end of the study instead of trying to use them as a rescue strategy.