  In the search for effective treatments for COVID-19, initial emphasis has
been on re-purposed treatments. To maximise the chances of finding successful
treatments, novel treatments that have been developed for this disease in
particular, are needed. In this manuscript we describe and evaluate the
statistical design of the AGILE platform, an adaptive randomized seamless Phase
I/II trial platform that seeks to quickly establish a safe range of doses and
investigates treatments for potential efficacy using a Bayesian sequential
trial design. Both single agent and combination treatments are considered. We
find that the design can identify potential treatments that are safe and
efficacious reliably with small to moderate sample sizes.
