Network proximity-based drug repurposing in copd

The National Heart, Lung, and Blood Institute awarded Brigham & Women's Hospital Inc. $372,635 under NIH Project Grant R21HL188684 on August 15, 2026, to develop a network proximity-based drug repurposing pipeline for chronic obstructive pulmonary disease.

The award funds two integrated aims. In Aim 1, the recipient will build an updated COPD disease module by integrating genome-wide association studies and multi-omics data into the human protein interactome, using a proximity-based framework to identify drugs whose targets lie closest to COPD-related networks and prioritize those expressed in lung tissue and relevant immune cells. In Aim 2, the recipient will perform comparative effectiveness studies using the Merative MarketScan dataset (covering more than 100 million covered lives) to test whether candidate drugs are associated with reduced COPD exacerbations compared to matched referent therapies using state-of-the-art methods for confounding control and causal inference.

Expected outcomes include an updated COPD network module and publicly available web platform for continued repurposing efforts, identification of promising drug candidates with biological plausibility, and prioritization of agents for early-phase clinical trials. Performance occurs in Boston, Massachusetts, with a period of performance from August 15, 2026, through August 14, 2028.

The award is issued under Assistance Listing 93.837, Cardiovascular Diseases Research, a program that fosters heart and vascular research across basic, translational, clinical, and population sciences.

Abstract

Chronic obstructive pulmonary disease (copd) is a leading cause of death worldwide and a major driver of healthcare costs, yet few new therapies have emerged in recent decades. Repurposing existing drugs offers a faster, lower-cost path to treatment; repurposed agents succeed at three times the rate of DE novo drugs. Further, drug candidates are twice as likely to be approved when supported by genetic evidence. However, the path to repurposing is often serendipitous rather than systematic. Systematic approaches that utilize genetic and multiple omics data to identify and validate drug repurposing candidates for copd have not been applied. This project combines network-based computational methods with real-world clinical data to accelerate copd drug repurposing. In aim 1, we will build an updated copd "disease module" by integrating the latest genome- wide association studies and multi-omics data into the human protein interactome. Using a proximity-based framework and hypothesis testing, we will identify drugs whose targets LIE closest to copd-related networks and prioritize those expressed in lung tissue and relevant immune cells. In aim 2, we will perform comparative effectiveness studies in the merative marketscan dataset (>100 million covered lives) to test whether candidate drugs are associated with reduced copd exacerbations compared to matched referent therapies using state- of- the-art methods for confounding control and causal inference. The expected outcomes include: (1) an updated copd network module and publicly available web platform for continued repurposing efforts; (2) identification of promising drug candidates with biological plausibility; and (3) prioritization of agents for early-phase clinical trials. This project is innovative in systematically uniting genetics, omics, and network science with pharmacoepidemiology, and significant in contributing to a low-cost, scalable pipeline for drug repurposing in copd. The work will generate critical preliminary data for subsequent R01 and clinical trial proposals, with the goal of expanding effective treatment options for millions of patients with copd.