Physiologically Based Pharmacokinetic Models for Prediction of Complex CYP2C8 and OATP1B1 (SLCO1B1) Drug-Drug-Gene Interactions: A Modeling Network of Gemfibrozil, Repaglinide, Pioglitazone, Rifampicin, Clarithromycin and Itraconazole.
Area Under Curve
Carbamates
/ administration & dosage
Clarithromycin
/ administration & dosage
Cytochrome P-450 CYP2C8
/ drug effects
Drug Interactions
Gemfibrozil
/ administration & dosage
Humans
Itraconazole
/ administration & dosage
Liver-Specific Organic Anion Transporter 1
/ drug effects
Models, Biological
Pioglitazone
/ administration & dosage
Piperidines
/ administration & dosage
Rifampin
/ administration & dosage
Journal
Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849
Informations de publication
Date de publication:
12 2019
12 2019
Historique:
pubmed:
28
5
2019
medline:
12
9
2020
entrez:
27
5
2019
Statut:
ppublish
Résumé
Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) pose a serious health risk that can be avoided by dose adaptation. These interactions are investigated in strictly controlled setups, quantifying the effect of one perpetrator drug or polymorphism at a time, but in real life patients frequently take more than two medications and are very heterogenous regarding their genetic background. The first objective of this study was to provide whole-body physiologically based pharmacokinetic (PBPK) models of important cytochrome P450 (CYP) 2C8 perpetrator and victim drugs, built and evaluated for DDI and DGI studies. The second objective was to apply these models to describe complex interactions with more than two interacting partners. PBPK models of the CYP2C8 and organic-anion-transporting polypeptide (OATP) 1B1 perpetrator drug gemfibrozil (parent-metabolite model) and the CYP2C8 victim drugs repaglinide (also an OATP1B1 substrate) and pioglitazone were developed using a total of 103 clinical studies. For evaluation, these models were applied to predict 34 different DDI studies, establishing a CYP2C8 and OATP1B1 PBPK DDI modeling network. The newly developed models show a good performance, accurately describing plasma concentration-time profiles, area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C Whole-body PBPK models of gemfibrozil, repaglinide, and pioglitazone have been built and qualified for DDI and DGI prediction. PBPK modeling is applicable to investigate complex interactions between multiple drugs and genetic polymorphisms.
Sections du résumé
BACKGROUND
Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) pose a serious health risk that can be avoided by dose adaptation. These interactions are investigated in strictly controlled setups, quantifying the effect of one perpetrator drug or polymorphism at a time, but in real life patients frequently take more than two medications and are very heterogenous regarding their genetic background.
OBJECTIVES
The first objective of this study was to provide whole-body physiologically based pharmacokinetic (PBPK) models of important cytochrome P450 (CYP) 2C8 perpetrator and victim drugs, built and evaluated for DDI and DGI studies. The second objective was to apply these models to describe complex interactions with more than two interacting partners.
METHODS
PBPK models of the CYP2C8 and organic-anion-transporting polypeptide (OATP) 1B1 perpetrator drug gemfibrozil (parent-metabolite model) and the CYP2C8 victim drugs repaglinide (also an OATP1B1 substrate) and pioglitazone were developed using a total of 103 clinical studies. For evaluation, these models were applied to predict 34 different DDI studies, establishing a CYP2C8 and OATP1B1 PBPK DDI modeling network.
RESULTS
The newly developed models show a good performance, accurately describing plasma concentration-time profiles, area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C
CONCLUSIONS
Whole-body PBPK models of gemfibrozil, repaglinide, and pioglitazone have been built and qualified for DDI and DGI prediction. PBPK modeling is applicable to investigate complex interactions between multiple drugs and genetic polymorphisms.
Identifiants
pubmed: 31129789
doi: 10.1007/s40262-019-00777-x
pii: 10.1007/s40262-019-00777-x
pmc: PMC6885506
doi:
Substances chimiques
Carbamates
0
Liver-Specific Organic Anion Transporter 1
0
Piperidines
0
SLCO1B1 protein, human
0
Itraconazole
304NUG5GF4
repaglinide
668Z8C33LU
CYP2C8 protein, human
EC 1.14.14.1
Cytochrome P-450 CYP2C8
EC 1.14.14.1
Clarithromycin
H1250JIK0A
Gemfibrozil
Q8X02027X3
Rifampin
VJT6J7R4TR
Pioglitazone
X4OV71U42S
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1595-1607Références
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