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ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms

Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been responsible for a large portion of new drug development failure. Molecular understanding and in silico evaluation of drug (or candidate) safety in labora...

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Detalles Bibliográficos
Autores principales: Cai, Mei-Chun, Xu, Quan, Pan, Yan-Jing, Pan, Wen, Ji, Nan, Li, Yin-Bo, Jin, Hai-Jing, Liu, Ke, Ji, Zhi-Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383906/
https://www.ncbi.nlm.nih.gov/pubmed/25361966
http://dx.doi.org/10.1093/nar/gku1066
Descripción
Sumario:Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been responsible for a large portion of new drug development failure. Molecular understanding and in silico evaluation of drug (or candidate) safety in laboratory is thus so desired, and unfortunately has been largely hindered by misuse of ADR terms. The growing impact of bioinformatics and systems biology in toxicological research also requires a specialized ADR term system that works beyond a simple glossary. Adverse Drug Reaction Classification System (ADReCS; http://bioinf.xmu.edu.cn/ADReCS) is a comprehensive ADR ontology database that provides not only ADR standardization but also hierarchical classification of ADR terms. The ADR terms were pre-assigned with unique digital IDs and at the same time were well organized into a four-level ADR hierarchy tree for building an ADR–ADR relation. Currently, the database covers 6544 standard ADR terms and 34 796 synonyms. It also incorporates information of 1355 single active ingredient drugs and 134 022 drug–ADR pairs. In summary, ADReCS offers an opportunity for direct computation on ADR terms and also provides clues to mining common features underlying ADRs.