The COVID-19 Therapeutic Information Browser

As the pace of COVID-19 research rapidly escalated during the pandemic, we built a platform to help biomedical experts easily discover published research about potential COVID-19 therapeutics and vaccines. The platform, COVID-TIB for short, uses rule-based natural language processing to identify documents about viruses, drugs, and vaccine types at scale. COVID-TIB displays numbers of journal papers, preprints, and clinical trials about particular drugs and SARS-CoV-2 and other viruses, binned by research stage. Users can apply multiple filters (e.g., recency, publication type, virus) to winnow results, select a set to see document metadata with links, and download search results. Users can also search for terms in the full text of papers and filter papers based on these search terms. In addition, users can link out to xDD’s COSMOS system (https://xdd.wisc.edu/set_visualizer/sets/xdd-covid-19) to browse figures and tables related to a virus and therapeutic. COVID-TIB currently presents information on 13 viruses and nearly 3,000 therapeutics found in 26K paper abstracts and clinical trial summaries. COVID-TIB can be used to browse recent drug research, identify promising drug candidates, gather information for reviews and meta-analyses, and track research over time. COVID-TIB is available at https://covidtib.c19hcc.org/. Keywords—COVID-19, therapeutics, drugs, natural language processing, text mining