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- Publisher Website: 10.1093/bioinformatics/btx834
- Scopus: eid_2-s2.0-85047082882
- PMID: 29293946
- WOS: WOS:000432170400027
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Article: PolyPK: An R package for pharmacokinetic analysis of multi-component drugs using a metabolomics approach
Title | PolyPK: An R package for pharmacokinetic analysis of multi-component drugs using a metabolomics approach |
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Authors | |
Issue Date | 2018 |
Citation | Bioinformatics, 2018, v. 34, n. 10, p. 1792-1794 How to Cite? |
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). |
Persistent Identifier | http://hdl.handle.net/10722/342704 |
ISSN | 2023 Impact Factor: 4.4 2023 SCImago Journal Rankings: 2.574 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Mengci | - |
dc.contributor.author | Wang, Shouli | - |
dc.contributor.author | Xie, Guoxiang | - |
dc.contributor.author | Ma, Xiaohui | - |
dc.contributor.author | Chen, Tianlu | - |
dc.contributor.author | Jia, Wei | - |
dc.date.accessioned | 2024-04-17T07:05:39Z | - |
dc.date.available | 2024-04-17T07:05:39Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Bioinformatics, 2018, v. 34, n. 10, p. 1792-1794 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | http://hdl.handle.net/10722/342704 | - |
dc.description.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). | - |
dc.language | eng | - |
dc.relation.ispartof | Bioinformatics | - |
dc.title | PolyPK: An R package for pharmacokinetic analysis of multi-component drugs using a metabolomics approach | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1093/bioinformatics/btx834 | - |
dc.identifier.pmid | 29293946 | - |
dc.identifier.scopus | eid_2-s2.0-85047082882 | - |
dc.identifier.volume | 34 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 1792 | - |
dc.identifier.epage | 1794 | - |
dc.identifier.eissn | 1460-2059 | - |
dc.identifier.isi | WOS:000432170400027 | - |