Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach

• Published in: PloS one Vol. 15; no. 9; p. e0239694
• Main Author: Alag, Shray
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 30.09.2020; Public Library of Science (PLoS)
• Subjects: API (Computer programming); Betacoronavirus; Biological Ontologies; Biology and Life Sciences; Clinical trials; Clinical Trials as Topic; Computational Biology; Coronavirus Infections - therapy; Coronaviruses; COVID-19; Disease transmission; Drugs; Epidemics; Extensible Markup Language; Genotype & phenotype; Humans; Interfaces; Internet; Intervention; Java; Medical research; Medical Subject Headings; Medical Subject Headings-MeSH; Medicine and Health Sciences; Methods; Mutation; Natural Language Processing; Ontology; Pandemics; People and Places; Phenotype; Phenotypes; Pneumonia, Viral - therapy; Proteins; Research and Analysis Methods; SARS-CoV-2; Secondary data analysis; Severe acute respiratory syndrome coronavirus 2; Software; Trends; Uniqueness; United States; Vaccines; Viral diseases; Viruses; United States; United States > US
• DOI: 10.1371/journal.pone.0239694
• ISSN: 1932-6203

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.