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0 0.5 1 1.5 2+ Mortality 27% Improvement Relative Risk Mortality (b) 34% Mortality (c) 30% Metformin for COVID-19  Alamgir et al.  Prophylaxis Is prophylaxis with metformin beneficial for COVID-19? Retrospective 22,124 patients in the USA Lower mortality with metformin (p=0.000022) Alamgir et al., medRxiv, April 2021 Favors metformin Favors control

Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation demonstrate reduced COVID-19 mortality in 1.5M patient records

Alamgir et al., medRxiv, doi:10.1101/2021.03.22.21254110
Apr 2021  
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Metformin for COVID-19
3rd treatment shown to reduce risk in July 2020
*, now known with p < 0.00000000001 from 88 studies.
No treatment is 100% effective. Protocols combine complementary and synergistic treatments. * >10% efficacy in meta analysis with ≥3 clinical studies.
4,100+ studies for 60+ treatments.
In Silico study followed by PSM analysis of the National COVID Cohort Collaborative data in the USA, showing 27% lower mortality with metformin use.
risk of death, 27.0% lower, OR 0.73, p < 0.001, treatment 11,062, control 11,062, all patients, RR approximated with OR.
risk of death, 34.0% lower, OR 0.66, p = 0.007, treatment 5,369, control 5,369, diabetic patients with CCI≤3, RR approximated with OR.
risk of death, 30.0% lower, OR 0.70, p = 0.02, treatment 2,525, control 2,525, non-diabetic patients with CCI≤3, RR approximated with OR.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Alamgir et al., 6 Apr 2021, retrospective, database analysis, USA, preprint, 11 authors. Contact:,
This PaperMetforminAll
Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation demonstrate reduced COVID-19 mortality in 1.5M patient records
Joy Alamgir, PhD Masanao Yajima, MPH Rosa Ergas, Xinci Chen, Nicholas Hill, MD, MSc Naved Munir, Mohsan Saeed, Ken Gersing, PhD Melissa Haendel, Christopher G Chute, M Ruhul Abid
Background: Drug repositioning is a key component of COVID-19 pandemic response, through identification of existing drugs that can effectively disrupt COVID-19 disease processes, contributing valuable insights into disease pathways. Traditional non in silico drug repositioning approaches take substantial time and cost to discover effect and, crucially, to validate repositioned effects. Methods: Using a novel in-silico quasi-quantum molecular simulation platform that analyzes energies and electron densities of both target proteins and candidate interruption compounds on High Performance Computing (HPC), we identified a list of FDA-approved compounds with potential to interrupt specific SARS-CoV-2 proteins. Subsequently we used 1.5M patient records from the National COVID Cohort Collaborative to create matched cohorts to refine our in-silico hits to those candidates that show statistically significant clinical effect. Results: We identified four drugs, Metformin, Triamcinolone, Amoxicillin and Hydrochlorothiazide, that were associated with reduced mortality by 27%, 26%, 26%, and 23%, respectively, in COVID-19 patients. Conclusions: Together, these findings provide support to our hypothesis that in-silico simulation of active compounds against SARS-CoV-2 proteins followed by statistical analysis of electronic health data results in effective therapeutics identification.
CONFLICTS OF INTEREST Joy Alamgir is founder of ARIScience. Melissa Haendel is a co-founder of Pryzm Health. Analyzed
Bramante, Outpatient Metformin Use for Covid-19
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