All Studies Meta Analysis Recent:

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

Post
Facebook

Source PDF All Studies Meta AnalysisMeta

Download Image

Metformin for COVID-19

3rd treatment shown to reduce risk in July 2020

^*, now with p < 0.00000000001 from 93 studies.

Lower risk for mortality, ventilation, ICU admission, hospitalization, progression, and recovery.

No treatment is 100% effective. Protocols combine treatments. ^* >10% efficacy, ≥3 studies.

4,500+ studies for 81 treatments. c19early.org

In Silico study followed by PSM analysis of the National COVID Cohort Collaborative data in the USA, showing 27% lower mortality with metformin use.

Important missing comments or errors? Let us know.

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: joy@ariscience.com, ruhul_abid@brown.edu.

This Paper Metformin All

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

doi:10.1101/2021.03.22.21254110

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

References

Bramante, Outpatient Metformin Use for Covid-19

Charlson, Szatrowski, Peterson, Gold, Validation of a combined comorbidity index, J Clin Epidemiol, doi:10.1016/0895-4356(94)90129-5

Fitzpatrick, Szefler, Mauger, Development and initial validation of the Asthma Severity Scoring System (ASSESS), J Allergy Clin Immunol, doi:10.1016/j.jaci.2019.09.018

Fontes, Ribeiro, Sillero, Inhibition and activation of enzymes. The effect of a modifier on the reaction rate and on kinetic parameters, Acta Biochim Pol

Funk, Tyson, Intent to get a COVID-19 Vaccine Rises to 60% as Confidence in Research and Development Process Increases

Goodrich, Gabry, Ali, Brilleman, rstanarm: Bayesian applied regression modeling via Stan

Haendel, Christopher G Chute, Bennett, The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment, JAMIA, doi:10.1093/jamia/ocaa196

Ho, Imai, King, Stuart, MatchIt: Nonparametric Preprocessing for Parametric Causal Inference, J. Stat. Softw

Hou, Okuda, Edwards, SARS-CoV-2 Reverse Genetics Reveals a Variable Infection Gradient in the Respiratory Tract, Cell, doi:10.1016/j.cell.2020.05.042

Huang, Yang, Xu, Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19, Acta Pharmacol Sin, doi:10.1038/s41401-020-0485-4

Hundal, Krssak, Dufour, Mechanism by which metformin reduces glucose production in type 2 diabetes, Diabetes Dec, doi:10.2337/diabetes.49.12.2063

Huttner, Bielicki, Clements, Frimodt-Møller, Muller et al., Oral amoxicillin and amoxicillin-clavulanic acid: properties, indications and usage, Clin Microbiol Infect, doi:10.1016/j.cmi.2019.11.028

Island, None

Johnson, Speedie, Simon, Kumar, Westra, Quantifying the Effect of Data Quality on the Validity of an eMeasure, Appl Clin Inform, doi:10.4338/ACI-2017-03-RA-0042

Kwok, Lai, Wei, Herd immunity -estimating the level required to halt the COVID-19 epidemics in affected countries, J Infect, doi:10.1016/j.jinf.2020.03.027

Magrina, Marata, Mario, Daya, Vignatelli, Review of the available evidence on Thiazides Diuretics in the management of Heart Failure

Mcginley, Abutaleb, Johnson, Pfizer tells US officials it cannot supply substantial additional vaccines until late June or July

O'driscoll, Ribeiro Dos Santos, Wang, Age-specific mortality and immunity patterns of SARS-CoV-2, Nature, doi:10.1038/s41586-020-2918-0

Paltiel, Schwartz, Zheng, Walensky, Clinical Outcomes Of A COVID-19 Vaccine: Implementation Over Efficacy, Health Affairs, doi:10.1377/hlthaff.2020.02054

Parks, Smith, How to discover antiviral drugs quickly, NEJM, doi:10.1056/NEJMcibr2007042

Pushpakom, Iorio, Eyers, Drug repurposing: progress, challenges and recommendations, Nat Rev Drug Discov, doi:10.1038/nrd.2018.168

Ritsinger, Lagerqvist, Lundman, Diabetes, metformin and glucose lowering therapies after myocardial infarction: Insights from the SWEDEHEART registry, Diab Vasc Dis Res, doi:10.1177/1479164120973676

Roush, Sica, Diuretics for Hypertension: A Review and Update, Am J Hypertens, doi:10.1093/ajh/hpw030

Salpeter, Greyber, Pasternak, Salpeter, Risk of fatal and nonfatal lactic acidosis with metformin use in type 2 diabetes mellitus, Cochrane Database Syst Rev, doi:10.1002/14651858.CD002967.pub4

Schubert, Karousis, Jomaa, SARS-CoV-2 Nsp1 binds the ribosomal mRNA channel to inhibit translation, Nat Struct Mol Biol, doi:10.1038/s41594-020-0511-8

Sidhu, Preuss, None, Triamcinolone

Somogyi, Stockley, Keal, Rolan, Bochner, Reduction of metformin renal tubular secretion by cimetidine in man, Br J Clin Pharmacol, doi:10.1111/j.1365-2125.1987.tb03090.x

Stuart, Matching methods for causal inference: A review and a look forward, Stat Sci, doi:10.1214/09-STS313

Theoharides, Conti, Dexamethasone for COVID-19? Not so fast, J Biol Regul Homeost Agents, doi:10.23812/20-EDITORIAL_1-5

Thigpen, Funk, Most Americans expect a COVID-19 vaccine within a year; 72% say they would get vaccinated

Tyson, Johnson, Funk, US public now divided over whether to get COVID-19 vaccine

Zeng, Liu, Ma, Biochemical characterization of SARS-CoV-2 nucleocapsid protein, Biochem Biophys Res Commun, doi:10.1016/j.bbrc.2020.04.136

{ 'institution': [{'name': 'medRxiv'}], 'indexed': { 'date-parts': [[2021, 12, 18]], 'date-time': '2021-12-18T01:40:36Z', 'timestamp': 1639791636206}, 'posted': {'date-parts': [[2021, 4, 6]]}, 'group-title': 'Infectious Diseases (except HIV/AIDS)', 'reference-count': 39, 'publisher': 'Cold Spring Harbor Laboratory', 'content-domain': {'domain': [], 'crossmark-restriction': False}, 'short-container-title': [], 'accepted': {'date-parts': [[2021, 4, 6]]}, 'abstract': 'ABSTRACTBackgroundDrug ' '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.MethodsUsing 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.ResultsWe 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.ConclusionsTogether, ' '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.', 'DOI': '10.1101/2021.03.22.21254110', 'type': 'posted-content', 'created': {'date-parts': [[2021, 4, 7]], 'date-time': '2021-04-07T08:10:12Z', 'timestamp': 1617783012000}, 'source': 'Crossref', 'is-referenced-by-count': 0, 'title': [ 'Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation ' 'demonstrate reduced COVID-19 mortality in 1.5M patient records'], 'prefix': '10.1101', 'author': [ {'given': 'Joy', 'family': 'Alamgir', 'sequence': 'first', 'affiliation': []}, {'given': 'Masanao', 'family': 'Yajima', 'sequence': 'additional', 'affiliation': []}, {'given': 'Rosa', 'family': 'Ergas', 'sequence': 'additional', 'affiliation': []}, {'given': 'Xinci', 'family': 'Chen', 'sequence': 'additional', 'affiliation': []}, {'given': 'Nicholas', 'family': 'Hill', 'sequence': 'additional', 'affiliation': []}, {'given': 'Naved', 'family': 'Munir', 'sequence': 'additional', 'affiliation': []}, {'given': 'Mohsan', 'family': 'Saeed', 'sequence': 'additional', 'affiliation': []}, {'given': 'Ken', 'family': 'Gersing', 'sequence': 'additional', 'affiliation': []}, {'given': 'Melissa', 'family': 'Haendel', 'sequence': 'additional', 'affiliation': []}, {'given': 'Christopher G', 'family': 'Chute', 'sequence': 'additional', 'affiliation': []}, {'given': 'M. Ruhul', 'family': 'Abid', 'sequence': 'additional', 'affiliation': []}], 'member': '246', 'reference': [ { 'key': '2021040810301948000_2021.03.22.21254110v1.1', 'unstructured': 'CDC COVID Data Tracker. Centers for Disease Control and Prevention ' 'website. Updated March 12, 2021. Accessed March 13, 2021. ' 'https://covid.cdc.gov/covid-data-tracker/'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.2', 'unstructured': 'COVID-19 Vaccines. Food and Drug Administration. Updated March 12, 2021. ' 'Accessed March 13, 2021. ' 'https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/covid-19-vaccines'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.3', 'unstructured': 'Corona Virus Disease 2019. Centers of Disease Control and Prevention ' 'website. Updated December 3, 2020. Accessed December 4, 2020. ' 'https://www.cdc.gov/coronavirus/2019-ncov/vaccines/8-things.html'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.4', 'doi-asserted-by': 'publisher', 'DOI': '10.1377/hlthaff.2020.02054'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.5', 'unstructured': 'Thigpen CL , Funk C. Most Americans expect a COVID-19 vaccine within a ' 'year; 72% say they would get vaccinated. Updated May 21, 2020. Accessed ' 'December 9, 2020. ' 'https://www.pewresearch.org/fact-tank/2020/05/21/most-americans-expect-a-covid-19-vaccine-within-a-year-72-say-they-would-get-vaccinated/'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.6', 'unstructured': 'Tyson, A , Johnson, C , Funk, C. US public now divided over whether to ' 'get COVID-19 vaccine. Updated September 17 2020. Accessed December 9, ' '2020. ' 'https://www.pewresearch.org/science/2020/09/17/u-s-public-now-divided-over-whether-to-get-covid-19-vaccine/'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.7', 'unstructured': 'Funk C , Tyson, A. Intent to get a COVID-19 Vaccine Rises to 60% as ' 'Confidence in Research and Development Process Increases. Updated ' 'December 2, 2020. Accessed December 9, 2020. ' 'https://www.pewresearch.org/science/2020/12/03/intent-to-get-a-covid-19-vaccine-rises-to-60-as-confidence-in-research-and-development-process-increases/'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.8', 'unstructured': 'McGinley L , Abutaleb Y , Johnson C. Pfizer tells US officials it cannot ' 'supply substantial additional vaccines until late June or July. ' 'Washington Post. Dec 8, 2020. Accessed December 9, 2020. ' 'https://www.washingtonpost.com/health/2020/12/07/pfizer-vaccine-doses-trump/'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.9', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.jinf.2020.03.027'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.10', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/nrd.2018.168'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.11', 'unstructured': 'Jupyter. Project Jupyter. Updated December 10, 2020. Accessed December ' '11, 2020. https://jupyter.org'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.12', 'doi-asserted-by': 'publisher', 'DOI': '10.1093/jamia/ocaa196'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.13', 'unstructured': 'CommonDataModel. Github https://github.com/OHDSI/CommonDataModel. ' 'Updated December 10, 2020. Accessed December 11 2020.'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.14', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMcibr2007042'}, { 'issue': '1', 'key': '2021040810301948000_2021.03.22.21254110v1.15', 'doi-asserted-by': 'crossref', 'first-page': '233', 'DOI': '10.18388/abp.2000_4082', 'article-title': 'Inhibition and activation of enzymes. The effect of a modifier on the ' 'reaction rate and on kinetic parameters', 'volume': '47', 'year': '2000', 'journal-title': 'Acta Biochim Pol'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.16', 'unstructured': 'OMOP/N3C Templates and Codes. ARIScience. Updated December 18, 2020. ' 'Accessed December 19, 2020. ' 'https://www.ariscience.org/y1_omop_n3c.html.'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.17', 'doi-asserted-by': 'publisher', 'DOI': '10.18637/jss.v042.i08'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.18', 'doi-asserted-by': 'publisher', 'DOI': '10.1214/09-STS313'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.19', 'unstructured': 'Goodrich B , Gabry J , Ali I , Brilleman S (2020). “rstanarm: Bayesian ' 'applied regression modeling via Stan.” R package version 2.21.1. ' 'https://mc-stan.org/rstanarm'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.20', 'doi-asserted-by': 'publisher', 'DOI': '10.4338/ACI-2017-03-RA-0042'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.21', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/s41401-020-0485-4'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.22', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.bbrc.2020.04.136'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.23', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.cell.2020.05.042'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.24', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/s41594-020-0511-8'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.25', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/s41586-020-2918-0'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.26', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/0895-4356(94)90129-5'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.27', 'doi-asserted-by': 'publisher', 'DOI': '10.2337/diabetes.49.12.2063'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.28', 'doi-asserted-by': 'publisher', 'DOI': '10.1177/1479164120973676'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.29', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.jaci.2019.09.018'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.30', 'journal-title': 'Triamcinolone. 2020 Sep 28. In: StatPearls [Internet]. Treasure Island ' '(FL): StatPearls'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.31', 'doi-asserted-by': 'publisher', 'DOI': '10.23812/20-EDITORIAL_1-5'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.32', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.cmi.2019.11.028'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.33', 'doi-asserted-by': 'publisher', 'DOI': '10.1093/ajh/hpw030'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.34', 'unstructured': 'Bramante C. Outpatient Metformin Use for Covid-19. Updated November 27, ' '2020. Accessed December 15 2020. ' 'https://clinicaltrials.gov/ct2/show/NCT04510194'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.35', 'doi-asserted-by': 'publisher', 'DOI': '10.1111/j.1365-2125.1987.tb03090.x'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.36', 'doi-asserted-by': 'publisher', 'DOI': '10.1002/14651858.CD002967.pub4'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.37', 'unstructured': 'Magrina N , Marata A , Mario S , Daya L , Vignatelli L. Review of the ' 'available evidence on Thiazides Diuretics in the management of Heart ' 'Failure. WHO. Mar 2009. ' 'https://www.who.int/selection_medicines/committees/expert/17/application/thiazides.pdf'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.38', 'unstructured': 'A Review of the SARS-CoV-2 (COVID-19) Genome and Proteome. Genetex. ' 'Updated April 21, 2020. Accessed December 3, 2020. ' 'https://www.genetex.com/MarketingMaterial/Index/SARS-CoV-2_Genome_and_Proteome'}, { 'key': '2021040810301948000_2021.03.22.21254110v1.39', 'unstructured': 'COVID-19 HPC Consortium. Updated December 14, 2020. Accessed December ' '14, 2020. https://covid19-hpc-consortium.org.'}], 'container-title': [], 'original-title': [], 'link': [ { 'URL': 'https://syndication.highwire.org/content/doi/10.1101/2021.03.22.21254110', 'content-type': 'unspecified', 'content-version': 'vor', 'intended-application': 'similarity-checking'}], 'deposited': { 'date-parts': [[2021, 4, 8]], 'date-time': '2021-04-08T17:44:40Z', 'timestamp': 1617903880000}, 'score': 1, 'subtitle': [], 'short-title': [], 'issued': {'date-parts': [[2021, 4, 6]]}, 'references-count': 39, 'URL': 'http://dx.doi.org/10.1101/2021.03.22.21254110', 'relation': {}, 'published': {'date-parts': [[2021, 4, 6]]}, 'subtype': 'preprint'}

Download Image

Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.

Submit

Post

@CovidAnalysis

FAQ

Public domain CC0 1.0