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Blog
Regulatory Guidance, Adaptive Trials, and the Misconception of Efficiency
ICH-E20’s regulatory caution towards adaptive designs is often misapplied, resulting in inefficient or unrealistic alternatives for sponsors and patients. Operational casework demonstrates that so-called “complexity” in adaptive design is frequently misunderstood and that regulatory “false choices” undermine trial effectiveness.
Blog
Enhancing Phase 3 Trials Through Bayesian Borrowing
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.
Blog
Technical Realities of Ordinal Endpoint Analysis in Clinical Trials
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.
Blog
Guide to the Draft FDA Bayesian Guidance 2026
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.
Blog
The Rumored Shift to a One-Trial Standard for FDA Substantial Evidence
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.
Blog
Administrative Analyses for Funding Decisions in Adaptive Clinical Trials
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.
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