Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development. Issue 5 (May 2016)

• Record Type: Journal Article
• Authors: McEntire, Robin; Szalkowski, Debbie; Butler, James; Kuo, Michelle S.; Chang, Meiping; Chang, Man; Freeman, Darren; McQuay, Sarah; Patel, Jagruti; McGlashen, Michael; Cornell, Wendy D.; Xu, Jinghai James
• Is Part Of: Drug discovery today. Volume 21:Issue 5(2016)
• Page Start: 826
• Page End: 835
• Publication Date: 2016-05
• Subjects: Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2016.03.006
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: Medline, ClinicalTrials.gov and other sites offer search portal access to the latest information. The limited synonyms on the portals hinder efficient and effective searches. An internal workflow automates search, extraction and integration of downloaded content. This capability complements manually curated commercial sources. Abstract : External content sources such as MEDLINE ®, National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources.