PropertyValue
?:abstract
  • With the novel COVID-19 pandemic disrupting and threatening the lives of millions, researchers and clinicians have been recently conducting clinical trials at an unprecedented rate to learn more about the virus and potential drugs/treatments/vaccines to treat its infection. As a result of the influx of clinical trials, researchers, clinicians, and the lay public, now more than ever, face a significant challenge in keeping up-to-date with the rapid rate of discoveries and advances. To remedy this problem, this research mined the ClinicalTrials.gov corpus to extract COVID-19 related clinical trials, produce unique reports to summarize findings and make the meta-data available via Application Programming Interfaces (APIs). Unique reports were created for each drug/intervention, Medical Subject Heading (MeSH) term, and Human Phenotype Ontology (HPO) term. These reports, which have been run over multiple time points, along with APIs to access meta-data, are freely available at http://covidresearchtrials.com. The pipeline, reports, association of COVID-19 clinical trials with MeSH and HPO terms, insights, public repository, APIs, and correlations produced are all novel in this work. The freely available, novel resources present up-to-date relevant biological information and insights in a robust, accessible manner, illustrating their invaluable potential to aid researchers overcome COVID-19 and save hundreds of thousands of lives.
?:creator
?:doi
?:doi
  • 10.1371/journal.pone.0239694
?:journal
  • PLoS_One
?:license
  • cc-by
?:pdf_json_files
  • document_parses/pdf_json/58b3f272c2f7c08723298e0b73d8d90b3d14d678.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7526926.xml.json
?:pmcid
?:pmid
?:pmid
  • 32997699.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • Medline; PMC
?:title
  • Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach
?:type
?:year
  • 2020-09-30

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