ArticleBioinformatics (Oxford, England)2018
polyPK: an R package for pharmacokinetic analysis of multi-component drugs using a metabolomics approach.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- National Center for Complementary and Integrative Health Perspectives on Clinical Research Involving Natural Products.Drug metabolism and disposition: the biological fate of chemicals · 2020Article
- Data Mining and Systematic Pharmacology to Reveal the Mechanisms of Traditional Chinese Medicine in Recurrent Respiratory Tract Infections' Treatment.Evidence-based complementary and alternative medicine : eCAM · 2020Article
- The metaRbolomics Toolbox in Bioconductor and beyond.Metabolites · 2019Review
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Authors and funding
6 authors.
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Abstract
Summary: Pharmacokinetics (PK) is a long-standing bottleneck for botanical drug and traditional medicine research. By using an integrated phytochemical and metabolomics approach coupled with multivariate statistical analysis, we propose a new strategy, Poly-PK, to simultaneously monitor the performance of drug constituents and endogenous metabolites, taking into account both the diversity of the drug's chemical composition and its complex effects on the mammalian metabolic pathways. Poly-PK is independent of specific measurement platforms and has been successfully applied in the PK studies of Puerh tea, a traditional Chinese medicine Huangqi decoction and many other multi-component drugs. Here, we introduce an R package, polyPK, the first and only automation of the data analysis pipeline of Poly-PK strategy. polyPK provides 10 functions for data pre-processing, differential compound identification and grouping, traditional PK parameters calculation, multivariate statistical analysis, correlations, cluster analyses and resulting visualization. It may serve a wide range of users, including pharmacologists, biologists and doctors, in understanding the metabolic fate of multi-component drugs. Availability and implementation: polyPK package is freely available from the R archive CRAN (https://CRAN.R-project.org/package=polyPK). Contact: wjia@cc.hawaii.edu or chentianlu@sjtu.edu.cn. Supplementary information: Supplementary data are available at Bioinformatics online.
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