ArticleBritish journal of clinical pharmacology2018
Physiologically-based pharmacokinetic modelling of a CYP2C19 substrate, BMS-823778, utilizing pharmacogenetic data.
Article in British journal of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Physiologically based pharmacokinetic (PBPK) modeling for prediction of celecoxib pharmacokinetics according to CYP2C9 genetic polymorphism.Archives of pharmacal research · 2021Trial
- Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods.Computational and structural biotechnology journal · 2023Review
- A physiologically based pharmacokinetic model of clopidogrel in populations of European and Japanese ancestry: An evaluation of CYP2C19 activity.Pharmacology research & perspectives · 2022Article
- Physiologically based pharmacokinetic (PBPK) modeling of meloxicam in different CYP2C9 genotypes.Archives of pharmacal research · 2021Article
- Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends.Frontiers in pharmacology · 2021Review
- A Scoping Review of the Evidence Behind Cytochrome P450 2D6 Isoenzyme Inhibitor Classifications.Clinical pharmacology and therapeutics · 2020Article
- Physiologically-based pharmacokinetic modelling of a CYP2C19 substrate, BMS-823778, utilizing pharmacogenetic data.British journal of clinical pharmacology · 2018Article
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Authors and funding
5 authors at 1 institution in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsPrevious studies demonstrated direct correlation between CYP2C19 genotype and BMS-823778 clearance in healthy volunteers. The objective of the present study was to develop a physiologically-based pharmacokinetic (PBPK) model for BMS-823778 and use the model to predict PK and drug-drug interaction (DDI) in virtual populations with multiple polymorphic genes.
methodsThe PBPK model was built and verified using existing clinical data. The verified model was simulated to predict PK of BMS-823778 and significance of DDI with a strong CYP3A4 inhibitor in subjects with various CYP2C19 and UGT1A4 genotypes.
resultsThe verified PBPK model of BMS-823778 accurately recovered observed PK in different populations. In addition, the model was able to capture the exposure differences between subjects with different CYP2C19 genotypes. PK simulation indicated higher exposures of BMS-823778 in CYP2C19 poor metabolizers who were also devoid of UGT1A4 activity, compared to those with normal UGT1A4 functionality. Moderate DDI with itraconazole was predicted in subjects with wild-type CYP2C19 or UGT1A4. However, in subjects without CYP2C19 or UGT1A4 functionality, significant DDI was predicted when BMS-823778 was coadministered with itraconazole.
conclusionsA PBPK model was developed using clinical data that accurately predicted human PK in different population with various CYP2C19 phenotypes. Simulations with the verified PBPK model indicated that UGT1A4 was probably an important clearance pathway in CYP2C19 poor metabolizers. DDI with itraconazole is likely to be dependent on the genotypes of CYP2C19 and UGT1A4.
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