Prioritizing research: evaluation of a portfolio management approach in clinical

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DESCRIPTION (provided by applicant): 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, federal funding for medical research lacks a coordinated system for prioritizing and allocating resources to efficiency address these important knowledge gaps. Thus a coordinated system to prioritize the most promising clinical research is critical if limited publc funds are to be used in ways that are likely to have the greatest impact on public health. Portfolio management is a systematic approach to decision-making that is widely used in the private sector to inform and manage research investments. The overall objective of this proposal is to determine whether a portfolio management framework can improve the efficiency of selecting and prioritizing publicly funded research studies within the setting of a large cancer clinical trials cooperative group. The key challenge to implementing such a framework in the public research setting is the difficultly in defining and efficiently estimating two key measures f performance the expected risk of failure and the expected societal return from the proposed research study. The aims of this proposal are therefore to develop and evaluate quantitative metrics of risk and return that are appropriate for the publicly funded clinical trial setting and relevant to and accepted by stakeholders. We will develop a statistical model to predict the risk of a clinical trial failure, defined as a trial that does not enroll a sufficient number of patient and consequently is unable to inform clinical practice patterns, based on trial-level variables available before the trial is launched. We will quantify the societal return of the proposed studie using Value of Information (VOI) analyses and will develop a process for rapidly and efficiently generating these estimates using a relatively new technique, minimal modeling VOI. Lastly, we will estimate measures of risk and return for a sample of recently reviewed clinical trial proposals to illustrate how a portfolio management framework can improve the efficiency of funding decisions within a cancer clinical trials cooperative group setting. Developing measures of risk and return will provide decision makers with valuable information on the study proposals they review and help them make more systematic and efficient funding decisions. If successful, this project could provide a novel prioritization paradigm for medical research organizations and funding agencies, and ultimately help maximize the public health impact of limited research funds.