FDA Support Drives Shift Toward Bayesian Trial Design

The FDA’s growing support for Bayesian statistical methods is driving a shift in how drug developers design and analyze clinical trials. Unlike traditional frequentist approaches, Bayesian frameworks allow researchers to combine new trial data with prior information — such as previous study results or external evidence — enabling more flexible and efficient trial designs. This is especially useful in rare diseases or small population studies where traditional designs often struggle with sample size limitations.

In part 2 of recent Applied Clinical Trials video interview series, David Morton, PhD, Director of Biostatistics at Certara, explains that Bayesian designs can improve decision-making during trials by governing when to stop for success or futility, guiding dose selection, and supporting adaptive interim analyses.