Your browser doesn't support javascript.
loading
Translational Knowledge Discovery Between Drug Interactions and Pharmacogenetics.
Wu, Heng-Yi; Shendre, Aditi; Zhang, Shijun; Zhang, Pengyue; Wang, Lei; Zeruesenay, Desta; Rocha, Luis M; Shatkay, Hagit; Quinney, Sara K; Ning, Xia; Li, Lang.
Affiliation
  • Wu HY; Genentech Inc., San Francisco, California, USA.
  • Shendre A; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
  • Zhang S; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
  • Zhang P; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
  • Wang L; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
  • Zeruesenay D; Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Rocha LM; School of Informatics, Computing & Engineering, Indiana University, Bloomington, Indiana, USA.
  • Shatkay H; Instituto Gulbenkian de Ciência, Oeiras, Portugal.
  • Quinney SK; Department of Computer and Information Sciences, University of Delaware, Newark, Delaware, USA.
  • Ning X; Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Li L; Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Clin Pharmacol Ther ; 107(4): 886-902, 2020 04.
Article in En | MEDLINE | ID: mdl-31863452
Clinical translation of drug-drug interaction (DDI) studies is limited, and knowledge gaps across different types of DDI evidence make it difficult to consolidate and link them to clinical consequences. Consequently, we developed information retrieval (IR) models to retrieve DDI and drug-gene interaction (DGI) evidence from 25 million PubMed abstracts and distinguish DDI evidence into in vitro pharmacokinetic (PK), clinical PK, and clinical pharmacodynamic (PD) studies for US Food and Drug Administration (FDA) approved and withdrawn drugs. Additionally, information extraction models were developed to extract DDI-pairs and DGI-pairs from the IR-retrieved abstracts. An overlapping analysis identified 986 unique DDI-pairs between all 3 types of evidence. Another 2,157 and 13,012 DDI-pairs and 3,173 DGI-pairs were identified from known clinical PK/PD DDI, clinical PD DDI, and DGI evidence, respectively. By integrating DDI and DGI evidence, we discovered 119 and 18 new pharmacogenetic hypotheses associated with CYP3A and CYP2D6, respectively. Some of these DGI evidence can also aid us in understanding DDI mechanisms.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pharmacogenetics / United States Food and Drug Administration / Drug Interactions / Translational Research, Biomedical / Data Mining / Knowledge Discovery Limits: Humans Country/Region as subject: America do norte Language: En Journal: Clin Pharmacol Ther Year: 2020 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pharmacogenetics / United States Food and Drug Administration / Drug Interactions / Translational Research, Biomedical / Data Mining / Knowledge Discovery Limits: Humans Country/Region as subject: America do norte Language: En Journal: Clin Pharmacol Ther Year: 2020 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos