In this episode of "In the Interim…", Dr. Scott Berry explores the origins of REMAP-CAP with Prof. Steve Webb, former chair of the REMAP-CAP International Trial Steering Committee.

Longitudinal modeling and predictive modeling are the foundation of learning efficiently in adaptive clinical trials, allowing real-time learning from early data. Bayesian models enable faster, more informed decisions even when primary endpoints are distant.

In this episode of "In the Interim…", Dr. Scott Berry explores the challenge of protracted endpoint timelines in adaptive clinical trials and the statistical strategies used to increase the rate of actionable information gain.

In this episode of "In the Interim…", Dr. Scott Berry is joined by Dr. Will Meurer, professor of Emergency Medicine and Neurology at the University of Michigan, for an in-depth analysis of the ICECAP trial’s adaptive Bayesian design.

REMAP-CAP, ATTACC, and ACTIV-4a unified under a multi-platform randomized clinical trial with a joint Bayesian adaptive design, rapidly determining that therapeutic anticoagulation benefits moderate, but not severe, COVID-19 patients.

In this episode of "In the Interim…", Dr. Scott Berry details the design, execution, and results of the multi-platform Randomized Clinical Trial (mpRCT) pioneered during the COVID-19 pandemic.