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Science of Science Approach to Analyzing and Innovating the Biomedical Research Enterprise (SoS:BIO)

Award Number: R01GM170992
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/20/2026
PERIOD OF PERFORMANCE END DATE: 03/31/2030

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Science of Science Approach to Analyzing and Innovating the Biomedical Research Enterprise (SoS:BIO) - PROJECT SUMMARY (See instructions): The United States federal government invests more than $45 billion annually in biomedical research with the ultimate goal of improving human health. However, the pathway from funded projects to a novel therapy is long and indirect, shaped by a sequence of consequential decisions made by many stakeholders. Funders and policymakers lack systematic, data-driven tools to trace research investments through this pathway, identify where progress stalls, and forecast which research is most likely to improve health. This project addresses that gap by reframing research impact assessment as a decision science problem, and building the data infrastructure, analytic methods, and forecasting models needed to measure and accelerate the translation of federally funded research into improved health. Aim 1 will construct an enriched NIH knowledge graph linking grants to downstream outputs such as FDA-approvals, clinical practice guidelines, and real-world health data. This graph will quantify semantic relatedness across document types, revealing more meaningful connections than citation-based methods. Aim 2 will use this knowledge graph for econometric and network analysis to identify which features explain the success or failure of translation at three pivotal decision points: (1) targeted funding initiatives at shifting the direction of science; (2) patent portfolios at subsequent FDA approval; and (3), clinical guideline's evidence base contributing to real-world prescribing. Each decision point offers observable counterfactuals, enabling rigorous retrospective comparison. Aim 3 turns to predictive analytics. We will develop machine learning models to forecast successive stages of therapeutic development, from FDA approval through guideline recommendation to real-world prescription uptake. Together these aims will yield a publicly accessible knowledge infrastructure and analytic framework enabling funders, researchers, and policymakers to evaluate research portfolios, identify leverage points, and make evidence-based investment decisions while those decisions can still shape outcomes. All schemas, methods, and data products will be designed for reuse and interoperability with existing federal data assets, advancing the science of science and strengthening the nation's capacity to convert biomedical research dollars into measurable improvements in public health.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $259,270 )
2026	2026	UNIVERSITY OF WISCONSIN SYSTEM	21 N PARK ST STE 6301	MADISON	WI	53715	DANE	USA	Biomedical Research and Research Training	000	1	8/19/2026	NEW	$259,270
														Subtotal = $259,270

Grand Total All Awards = $259,270

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Science of Science Approach to Analyzing and Innovating the Biomedical Research Enterprise (SoS:BIO)

Award Number: R01GM170992

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/20/2026

PERIOD OF PERFORMANCE END DATE: 03/31/2030

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