Literature DB >> 20238427

Characterization and classification of adverse drug interactions.

Masataka Takarabe1, Daichi Shigemizu, Masaaki Kotera, Susumu Goto, Minoru Kanehisa.   

Abstract

Drug interactions which may cause harmful events are important for our health and new drag development. In the previous work, we extracted the drug interaction data from Japanese drug package inserts and generated the drug interaction network. The network contains a large number of drugs densely connected to each other, where drug targets and drug-metabolizing enzymes were shared in the drug interactions. In this study, we further analyzed the obtained drug interaction network by merging drugs into drug categories based on the Anatomical Therapeutic Chemical (ATC) classification. The merged data of drug interactions indicated drug properties that are related to drug interaction mechanisms or symptoms. We investigated the relationships between the drug groups and drug interaction mechanisms or symptoms.

Mesh:

Substances:

Year:  2010        PMID: 20238427

Source DB:  PubMed          Journal:  Genome Inform        ISSN: 0919-9454


  3 in total

1.  Text Mining Driven Drug-Drug Interaction Detection.

Authors:  Su Yan; Xiaoqian Jiang; Ying Chen
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2013

2.  Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs.

Authors:  Francisco J Azuaje; Lu Zhang; Yvan Devaux; Daniel R Wagner
Journal:  Sci Rep       Date:  2011-08-02       Impact factor: 4.379

3.  A Pharmacovigilance Approach for Post-Marketing in Japan Using the Japanese Adverse Drug Event Report (JADER) Database and Association Analysis.

Authors:  Masakazu Fujiwara; Yohei Kawasaki; Hiroshi Yamada
Journal:  PLoS One       Date:  2016-04-27       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.