University of pittsburgh clinical and translational science institute

The National Center for Advancing Translational Sciences at the National Institutes of Health awarded the University of Pittsburgh a cooperative agreement totaling $10,192,245 on July 15, 2026, under the National Center for Advancing Translational Sciences program (CFDA 93.350).

The University of Pittsburgh Clinical and Translational Science Institute will operate as a learning research system to systematically identify and disseminate generalizable methods that accelerate translational research and overcome barriers to research planning, conduct, dissemination, and implementation. The Institute will apply translational science principles to improve translational research tools, resources, and efficiency; connect investigators with communities, patients, clinicians, and policymakers to build skilled, well-resourced research teams; and systematically study the impact of rapid advances in data science and artificial intelligence on translational research. The Institute will gather quantitative and qualitative data on research gaps and opportunities, then create and test novel methods to enhance research efficiency, quality, innovation, rigor, and reproducibility. Work will include creating and refining an ontology to characterize research barriers, developing scalable measures of research output and impact, and disseminating effective solutions to investigators within and beyond the University of Pittsburgh.

The award funds performance at Pittsburgh, Pennsylvania 15213, with a period of performance extending from the award date through May 31, 2033.

Abstract

The university of pittsburgh (pitt) clinical translational science institute (ctsi) will build on the success since its founding in 2006 of supporting translational research to now conduct rigorous and impactful translational science, identifying generalizable methods and strategies that accelerate translational research. Our strategy is for ctsi to operate as a learning research system that uses translational science principles and frameworks to overcome barriers to the planning, conduct, dissemination, or implementation of translational research. Our learning research system will leverage the >700 service, consultation, and resource requests we receive each year from pitt investigators to identify common research obstacles toward the development, testing, and dissemination of generalizable solutions. Specifically, we will: 1) apply translational science through our learning research system to systematically improve translational research tools, resources, and efficiency; 2) connect investigators with communities, patients, clinicians, and policymakers to create well-resourced and skilled teams who deliver impactful translational research; and 3) systematically study the impact of rapid advances in data science and artificial intelligence on translational research and translational science. We will gather quantitative and qualitative data on gaps and opportunities in translational research and then create and test novel methods to enhance research efficiency, quality, innovation, rigor, and reproducibility. Our methods will include creating and refining an ontology to characterize research barriers and developing scalable measures of research output and impact. Within this framework, we will ideate and iteratively refine solutions that, if effective, we will disseminate back to our investigators and beyond. We will work to seamlessly integrate research in the context of clinical care through research training for clinicians, support practice-based research networks, and earn the trust of patients and the broader community by listening, engaging, and elevating their role as members of the research team. We will also promote strong and sustainable bidirectional relationships with a wide range of stakeholder groups and examine new ways to gather, train, and sustain multidisciplinary teams. We will identify how and when new data science innovations are adopted, how they influence the efficiency and rigor of translational research, and how they alter the interactions between investigators, individuals, patients and clinicians. We will develop, demonstrate, and disseminate methods for using real-world data to advance research and generate new knowledge. We will develop and test analytic approaches to detect and mitigate data- or AI-generated threats to rigor or generalizability and offer timely learning modules that optimize the ability of our investigators to leverage the latest AI tools and resources. Building on two decades of impact, ctsi activities moving forward will help integrate translational research into the culture of clinical operations, increase trustworthiness and participation in all studies, and pursue translational science with goal-driven intentionality to enable these outcomes.