Principal-Agent Hypothesis Testing
This addresses the challenge of aligning regulatory approval with social utility in drug development, though it appears incremental as it builds on existing principal-agent frameworks.
The paper tackles the problem of designing statistical testing protocols for a regulator to approve drugs, considering that a strategic pharmaceutical company may adjust its trial behavior based on the evidence standard. It shows how to design robust protocols and derives the optimal one in the presence of such strategic agents.
Consider the relationship between a regulator (the principal) and an experimenter (the agent) such as a pharmaceutical company. The pharmaceutical company wishes to sell a drug for profit, whereas the regulator wishes to allow only efficacious drugs to be marketed. The efficacy of the drug is not known to the regulator, so the pharmaceutical company must run a costly trial to prove efficacy to the regulator. Critically, the statistical protocol used to establish efficacy affects the behavior of a strategic, self-interested agent; a lower standard of statistical evidence incentivizes the agent to run more trials that are less likely to be effective. The interaction between the statistical protocol and the incentives of the pharmaceutical company is crucial for understanding this system and designing protocols with high social utility. In this work, we discuss how the regulator can set up a protocol with payoffs based on statistical evidence. We show how to design protocols that are robust to an agent's strategic actions, and derive the optimal protocol in the presence of strategic entrants.