Statistical Opportunities to Accelerate Development for COVID-19 Therapeutics

The COVID-19 pandemic presents unprecedented challenges for drug developers seeking to evaluate the safety and efficacy of potential treatments for COVID-19. Clinical researchers must work quickly and adapt to emerging data. Building upon the FDA guidance document and Duke-Margolis' critical path to rapid development and access to safe and effective COVID-19 therapeutics, this article focuses on statistical opportunities for nimble and accelerated development for COVID-19 therapeutics. We focus on acceleration opportunities by way of increasing clinical trial efficiency, facilitating robust collection of key clinical outcomes, and enabling quantitative decision making to bring safe and effective therapeutics to the market. We present adaptive elements of trial designs which allow trials to evolve as new information emerges and discuss participation in master protocols to optimize use of resources, ensure scientific rigor and enhance interpretation of study results. Key clinical outcomes of importance to public health and core data elements are proposed to facilitate broader data sharing and robust decision making. Available statistical methods and efficient approaches to rapidly generate and synthesize meaningful evidence are presented contributing to quantitative decision making on the effectiveness and safety of COVID-19 therapeutics. In this article, we share innovative trial designs, clinical outcome and data standards, and existing statistical methods to accelerate the development of COVID-19 therapeutics and recommend that they should be applied immediately in a harmonized fashion.