Bayesian borrowing in Phase 3 trials formally combines prior evidence with the new trial data to enhance development efficiency and regulatory decision making. This approach requires rigorous statistical modeling, careful selection of historical information, and detailed regulatory dialogue.

A rigorous review of ordinal endpoint analyses, showing every approach—utility weighting, proportional odds, dichotomization, or non-parametric—inevitably assigns relative weights to outcome states. Berry Consultants’ mathematical demonstration reveals how proportional odds analysis embeds prevalence-based weights, underscoring the need for transparency and clinical input in trial design.

The FDA Draft Bayesian guidance is a dramatic leap forward for Bayesian clinical trials and regulatory science. In this blog, Dr. Kert Viele outlines the key concepts and motivations for the guidance recommendations.

In recent public discussion, FDA leaders have indicated a possible shift from the longstanding two-trial requirement for substantial evidence of drug efficacy to acceptance of a single, highly stringent trial. Dr. Scott Berry and Dr. Kert Viele, on the "In the Interim..." podcast, analyze the statistical, regulatory, and scientific implications and highlight those in this blog.

Seamless adaptive trials can deliver higher statistical power with fewer patients and shorter timelines, yet practical funding hurdles persist. Objective administrative (financial) analyses—often Bayesian-driven—can define funding triggers without compromising trial integrity.

Digital twins in clinical research generate discussion and controversy, but current use is limited by lack of rich data sets. The potential is great for modeling counterfactual outcomes in clinical research, and we will get there.