Optimizing the Trade-off Between Learning and Doing in a Pandemic

The world is united regarding the goal of ending the coronavirus disease 2019 (COVID-19) pandemic but not the strategy to achieve that goal. One stark example is the debate over whether to prescribe available therapies, such as quinine-based antimalarial drugs (eg, chloroquine or hydroxychloroquine), or test these drugs in randomized clinical trials (RCTs). At the heart of the problem is one of the oldest dilemmas in human organizations: the “exploitation-exploration” trade-off.¹ Exploitation refers to acting on current knowledge, habits, or beliefs despite uncertainty. This is the “just do it” option: give various therapies (eg, chloroquine) to affected patients based on current knowledge or a hunch. Exploration refers to actions taken to generate new knowledge and reduce uncertainty, eg, testing therapies in an RCT. This is the “must learn” option.

Currently, these approaches are framed as a choice: do something (treat the patient) or learn something (test the drug). This dilemma is now playing out across the world, with many clinicians recommending treatments (eg, antiviral agents or immunomodulating drugs), even while researchers and regulators emphasize that evidence is limited and the need for RCTs is paramount. The problem is that exploitation/exploration trade-offs are almost always best solved by a strategy that blends both: simultaneously learning while doing. The joint goal of this integrated effort is to maximize short-term outcomes (eg, the best possible recovery of patients who must be treated now) and long-term outcomes (eg, the fastest path to discovery and dissemination of new treatments). This balance is elusive, and potentially impossible without an integrated approach—a single system that “learns while doing,” with alacrity.