Publication | Open Access
An integrated pharmacokinetics ontology and corpus for text mining
54
Citations
17
References
2013
Year
Drug pharmacokinetics data are unevenly collected across databases and literature, making text mining and integration difficult without a dedicated ontology. We built a comprehensive pharmacokinetics ontology covering metabolism and transport enzymes, annotated in vitro and in vivo studies, and used it to create a PK‑corpus with four abstract classes and a novel three‑level annotation scheme for key terms and drug‑interaction pairs. The ontology and corpus proved useful by annotating three studies and enabling drug‑interaction extraction, demonstrating their value for mining pharmacokinetics parameters and interactions.
Abstract Background Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases. Description A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK-corpus was demonstrated by a drug interaction extraction text mining analysis. Conclusions The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK-corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.
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