Fewer than half of all medical interventions in use today are supported by clinical evidence. Despite allocating more than $11 billion each year to support clinical research, the federal government's funding of medical research lacks a coordinated, quantitative system for allocating resources to efficiently address these important knowledge gaps. This research will directly address whether or not promising advances in value-of-information analyses and risk prediction can be used to improve decision-making within a publicly funded cancer clinical trials co-operative group. This project will develop, test, and validate processes for rapidly estimating the expected risk and return for clinical trials proposals, and using these estimates explore how a portfolio optimization framework could improve allocations of limited public resources.
In terms of broader impacts, this research will provide new insights into factors associated with risk and return of publicly funded clinical trials' information that can directly contribute to the improved design of clinical research and policies that advance the efficient and systematic allocation of limited research funds. Furthermore, the findings from this work will advance efforts to develop a coordinated system to prioritize clinical research, a critical step to direct limited public funds in ways that are likely to have the greatest impact on public health.
