By Dr. Esha Senchaudhuri
The urgent need to discover and assess the efficacy and safety of COVID-19 vaccine candidates will affect the future clinical development of all infectious disease vaccine candidates, including those for diseases like tuberculosis. An under-appreciated component of this change is the transformational role that Bayesian statistics has played in quality vaccines being quickly identified and assessed.
In a recent roundtable, a statistician who worked on the Pfizer vaccine joined my colleagues at Cytel who designed the BCG vaccine trial, as well as former CBER (FDA) expert and a member of the French Scientific Council to discuss these developments. Here I review the design features of these clinical trials, and why Bayesian methods reduced risk and generated scientific findings more quickly.