Evidence map›Paper›PMID 34358753›Full record

ArticleBiomedicine & pharmacotherapy = Biomedecine & pharmacotherapie2021

In silico drug repurposing in COVID-19: A network-based analysis.

Pasquale Sibilio, Simone Bini, Giulia Fiscon, Marialuisa Sponziello, Federica Conte, Valeria Pecce, Cosimo Durante, Paola Paci, Rosa Falcone, Giuseppe Danilo Norata and 2 more

Abstract read
In one paragraph

Article in Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, 2021. 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.

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  12. Alveolar Regeneration in COVID-19 Patients: A Network Perspective.International journal of molecular sciences · 2021
    Review
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

12 authors.

Pasquale SibilioDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy; Institute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, Rome, Italy.
Simone BiniDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
Giulia FisconInstitute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, Rome, Italy; Fondazione per la Medicina Personalizzata, Via Goffredo Mameli, 3/1, Genova, Italy.
Marialuisa SponzielloDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
Federica ConteInstitute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, Rome, Italy.
Valeria PecceDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
Cosimo DuranteDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.
Paola PaciInstitute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, Rome, Italy; Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy. Electronic address: paci@diag.uniroma1.it.
Rosa FalconePhase 1 Unit-Clinical Trial Center Gemelli University Hospital, Rome, Italy.
Giuseppe Danilo NorataDepartment of Excellence in Pharmacological and Biomolecular Sciences, University of Milan and Center for the Study of Atherosclerosis, SISA Bassini Hospital, Milan, Italy.
Lorenzo FarinaDepartment of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy.
Antonella VerrientiDepartment of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 pandemic is a worldwide public health emergency. Despite the beginning of a vaccination campaign, the search for new drugs to appropriately treat COVID-19 patients remains a priority. Drug repurposing represents a faster and cheaper method than de novo drug discovery. In this study, we examined three different network-based approaches to identify potentially repurposable drugs to treat COVID-19. We analyzed transcriptomic data from whole blood cells of patients with COVID-19 and 21 other related conditions, as compared with those of healthy subjects. In addition to conventionally used drugs (e.g., anticoagulants, antihistaminics, anti-TNFα antibodies, corticosteroids), unconventional candidate compounds, such as SCN5A inhibitors and drugs active in the central nervous system, were identified. Clinical judgment and validation through clinical trials are always mandatory before use of the identified drugs in a clinical setting.

Indexed as

Computer SimulationCOVID-19COVID-19 Drug TreatmentDrug RepositioningAnti-Inflammatory AgentsCentral Nervous System AgentsEnzyme InhibitorsGene Expression ProfilingHumansImmunologic FactorsTreatment OutcomeVoltage-Gated Sodium Channel BlockersAnti-Inflammatory AgentsCentral Nervous System AgentsEnzyme InhibitorsImmunologic FactorsVoltage-Gated Sodium Channel BlockersCorticosteroidCOVID-19Drug repurposingHeparinInflammatory bowel diseaseSeptic shock

Identifiers

PMID34358753
PMCPMC8316014

What OpenQuestion holds

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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.