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

Clicks: 329
ID: 109590
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #151 of 296 articles by views in Journal of medical Internet research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 296 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Driven by the desperate time and the dire need racing to discover an antiviral drug to save our fellow humans, we explored the landscape of the SARS-CoV-2 Biomedical publications to satisfy the following objectives.(1) identify off-label drugs that may bring benefit for the COVID-19 pandemic, (2) present a novel ranking algorithm called CovidX, to recommend existing drugs for potential repurposing, and (3) validate the literature-based outcome with drug knowledge available in clinical trials.To achieve such objectives, we applied Natural Language Processing (NLP) techniques to identify drugs and linked entities (e.g., disease, gene, protein, chemical compounds, etc.). When such entities are linked, they form a map that can be further explored using Network Science tools. The CovidX algorithm is based upon a notion which we called "diversity". A diversity score for a given drug can is 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 an up to date evidence of the fast development of this disease.From 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 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 be needed to be taken at the same time.Not applicable.
Reference Key
gates2020thejournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gates, Lyndsey Elaine;Hamed, Ahmed Abdeen;
Journal Journal of medical Internet research
Year 2020
DOI
10.2196/21169
URL
Keywords
natural language processing colonoscopy pathology report

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.