An accurate and precise representation of drug ingredients. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Hanna, Josh; Bian, Jiang; Hogan, William
• Is Part Of: Journal of biomedical semantics. Volume 7:Issue 1(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-12
• Subjects: Semantics -- Periodicals; Medicine -- Research -- Periodicals; Biology -- Research -- Periodicals; Computer systems -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1186/s13326-016-0048-2
• Languages: English
• ISSNs: 2041-1480

Abstract

Abstract Background In previous work, we built the Drug Ontology (DrOn) to support comparative effectiveness research use cases. Here, we have updated our representation of ingredients to include both active ingredients (and their strengths) and excipients. Our update had three primary lines of work: 1) analysing and extracting excipients, 2) analysing and extracting strength information for active ingredients, and 3) representing the binding of active ingredients to cytochrome P450 isoenzymes as substrates and inhibitors of those enzymes. Methods To properly differentiate between excipients and active ingredients, we conducted an ontological analysis of the roles that various ingredients, including excipients, have in drug products. We used the value specification model of the Ontology for Biomedical Investigations to represent strengths of active ingredients and then analyzed RxNorm to extract excipient and strength information and modeled them according to the results of our analysis. We also analyzed and defined dispositions of molecules used in aggregate as active ingredients to bind cytochrome P450 isoenzymes. Results Our analysis of excipients led to 17 new classes representing the various roles that excipients can bear. We then extracted excipients from RxNorm and added them to DrOn for branded drugs. We found excipients for 5, 743 branded drugs, covering ~27 % of the 21, 191 branded drugs in DrOn. Our analysis of active ingredients resulted in another new class, active ingredient role. We also extracted strengths for all types of tablets, capsules, and caplets, resulting in strengths for 5, 782 drug forms, covering ~41 % of the 14, 035 total drug forms and accounting for ~97 % of the 5, 970 tablets, capsules, and caplets in DrOn. We represented binding-as-substrate and binding-as-inhibitor dispositions to two cytochrome P450 (CYP) isoenzymes (CYP2C19 and CYP2D6) and linked these dispositions to 65 compounds. It is now possible to query DrOn automatically for all drug products that contain active ingredients whose molecular grains inhibit or are metabolized by a particular CYP isoenzyme. DrOn is open source and is available athttp://purl.obolibrary.org/obo/dron.owl .