Another Published Preprint from the National COVID Cohort Collaborative (N3C)

National COVID Cohort Collaborative (N3C)

For the past year, researchers have been pursuing possibilities for the repurposing of existing drugs that can effectively disrupt COVID-19 disease processes. Electronic health record (EHR) data from the N3C Data Enclave were used to produce a recent preprint published in medRxiv on April 6, 2021 titled Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation demonstrate reduced COVID-19 mortality in 1.5M patient records authored by Joy Alamgir, Masanao Yajima, Rosa Ergas, Xinci Chen, Nicholas Hill, Naved Munir, Mohsan Saeed, Ken Gersing, Melissa Haendel, Christopher G. Chute, and M. Ruhul Abid. 

The study used a novel molecular simulation platform that analyzed energies and electron densities of target proteins and compounds to elucidate FDA-approved drugs that had the potential to interrupt specific SARS-CoV-2 proteins. From a shortlist of 18 in-silico (produced by using computer software or simulation) identified candidates, the authors found four drugs—metformin, triamcinolone, amoxicillin and hydrochlorothiazide—that were associated with reduced mortality odds by 27%, 26%, 26%, and 23%, respectively, in COVID-19 patients. The statistical analysis used multi-predictor propensity score based cohorts to determine effect. The findings from this research support the hypothesis that simulation of active compounds against SARS-CoV-2 proteins followed by statistical analysis of electronic health data results in effective therapeutics identification. 

This is yet another example of how the collaborative efforts of the N3C—the largest national data repository in the United States—can help answer questions for the treatment of COVID-19. For more information on N3C, visit

Publishing CTSA Program Hub’s Name
CTSA Program In Action Goals
Goal 5: Advance the Use of Cutting-Edge Informatics