Evidence map›Paper›PMID 32735546›Full record

ArticleJournal of medical Internet research2020

The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation.

Lyndsey Elaine Gates, Ahmed Abdeen Hamed

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Trial
  2. Article
  3. Predictive modelling and ranking:Frontiers in chemistry · 2025
    Article
  4. Review
  5. Article
  6. Diabetes and COVID-19: The potential role of mTOR.Diabetes research and clinical practice · 2022
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Rapamycin: Drug Repurposing in SARS-CoV-2 Infection.Pharmaceuticals (Basel, Switzerland) · 2021
    Review
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lyndsey Elaine Gates *School of Nursing, Norwich University, Northfield, VT, United States.ORCID 0000-0003-1402-2270
Ahmed Abdeen Hamed *School of Cybersecurity, Data Science, and Computing, Norwich University, Northfield, VT, United States.ORCID 0000-0003-4411-8433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDriven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments.

objectiveThe aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials.

methodsTo achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called "diversity." A diversity score for a given drug was calculated by measuring how "diverse" a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease.

resultsFrom the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride.

conclusionsThe ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time.

Indexed as

Antiviral AgentsBetacoronavirusCoronavirus InfectionsCOVID-19COVID-19 Drug TreatmentDrug RepositioningHumansHydroxychloroquinePandemicsPneumonia, ViralSARS-CoV-2Antiviral AgentsHydroxychloroquineantiviralbiomedicalCOVID-19COVID-19 treatmentdrugdrug repurposinghealthinformaticsnetwork algorithmranking

Identifiers

PMID32735546
PMCPMC7474417

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.