Cytel Blog on Applying Bayesian Methods to COVID-19 Clinical Trials

A Cytel blog post discusses how Bayesian methods have impacted COVID-19 vaccine clinical trials. Using Bayesian statistics can improve study efficiency while still providing robust evidence regarding outcomes. In addition, the increasing use of these methods in clinical trials is expected to accelerate in future studies.

According to Dr. Senchaudhuri, “For a number of people, the results of the Pfizer study will be emblazoned into memory for the foreseeable future; as for the rest of us: Pfizer completed early phase studies of its mRNA vaccine candidate in the US and Germany, before launching a multinational Phase 2/3 study. A total of 43,448 participants were randomized. Despite the large-scale trial, the clinical trial design is a study in seamless adaptive methods. The early results from the BioNTech study, were combined into a broader Phase I-II seamless study, which then led directly in a Phase III study, all within 9 months of each other. A number of precautionary stopping rules proved unnecessary, and ultimately the vaccine candidate was found to be 95% effective.” Read more here.

(Source: Esha Senchaudhuri, Cytel, 4/23/21)