Objectives/Goals: To achieve the greatest impact, protocols must be rigorous and feasible. The University of Minnesota’s Clinical Research Support Center developed a feasibility review (FR) to identify barriers, offer solutions, and strengthen translation through multidisciplinary expertise. Improvements are tracked using an Impact Scoring System. Methods/Study Population: Established in 2018, the FR was designed to address operational barriers that delay study start-up and help researchers strengthen protocols before regulatory submission and implementation. Drafts are reviewed by a multidisciplinary panel with expertise in logistics, recruitment, biostatistics, monitoring, and regulation. Each protocol undergoes a 1-week review process culminating in a 90-minute structured discussion between the panel and study team. A written report summarizes strengths, concerns, available resources, and next steps. To assess impact, we developed a novel scoring system that assigns each protocol a pre- and post-review score, objectively measuring how protocols improve in response to feedback. Results/Anticipated Results: Since its launch, 186 clinical studies from nine schools and colleges have completed FR. Study teams report high satisfaction (average rating 4.8/5), noting clearer recruitment plans, improved logistics, and valuable resource connections. The Impact Scoring System provides measurable evidence of change: on average, protocols increased their score by 28% from pre- to post-review, reflecting greater operational readiness and likelihood of success. Tracking also shows that FR participation is associated with fewer protocol-related IRB stipulations, offering an additional objective indicator of improved quality. Together, these results demonstrate both the perceived value and the measurable operational impact of the FR process. Discussion/Significance of Impact: The FR addresses operational barriers early, ensuring protocols are both rigorous and feasible before launch. Its Impact Scoring System provides objective evidence of improvement and a scalable model other institutions can adopt to advance rigor, efficiency, and trustworthy translation.
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Tosun et al. (2026) studied this question.
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