Physiologically based pharmacokinetic modeling of CYP2C8 substrate rosiglitazone and its metabolite to predict metabolic drug-drug interaction

被引:0
|
作者
Gaud, Nilesh [1 ,2 ]
Gogola, Dawid [2 ]
Kowal-Chwast, Anna [2 ]
Gabor-Worwa, Ewelina [2 ]
Littlewood, Peter [2 ]
Brzozka, Krzysztof [2 ]
Kus, Kamil [2 ]
Walczak, Maria [1 ]
机构
[1] Jagiellonian Univ Med Coll, Fac Pharm, Dept Toxicol, Med 9, PL-30688 Krakow, Poland
[2] Ryvu Therapeut SA, Drug Metab & Pharmacokinet, Krakow, Poland
关键词
PBPK modeling; Drug-drug interaction; In vitro metabolism; enzyme induction; enzyme inhibition; Rosiglitazone; SINGLE-DOSE PHARMACOKINETICS; INHIBITOR; DISCOVERY; IMPACT; TRIMETHOPRIM; ANTAGONIST; RIFAMPIN; ALTER;
D O I
10.1016/j.dmpk.2024.101023
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Rosiglitazone is an activator of nuclear peroxisome proliferator-activated (PPAR) receptor gamma used in the treatment of type 2 diabetes mellitus. The elimination of rosiglitazone occurs mainly via metabolism, with major contribution by enzyme cytochrome P450 (CYP) 2C8. Primary routes of rosiglitazone metabolism are N-demethylation and hydroxylation. Modulation of CYP2C8 activity by co-administered drugs lead to prominent changes in the exposure of rosiglitazone and its metabolites. Here, we attempt to develop mechanistic parent-metabolite physiologically based pharmacokinetic (PBPK) model for rosiglitazone. Our goal is to predict potential drug-drug interaction (DDI) and consequent changes in metabolite N-desmethyl rosiglitazone exposure. The PBPK modeling was performed in the PKSim (R) (R) software using clinical pharmacokinetics data from literature. The contribution to N-desmethyl rosiglitazone formation by CYP2C8 was delineated using vitro metabolite formation rates from recombinant enzyme system. Developed model was verified for prediction of rosiglitazone DDI potential and its metabolite exposure based on observed clinical DDI studies. Developed model exhibited good predictive performance both for rosiglitazone and N-desmethyl rosiglitazone respectively, evaluated based on commonly acceptable criteria. In conclusion, developed model helps with prediction of CYP2C8 DDI using rosiglitazone as a substrate, as well as changes in metabolite exposure. In vitro data for metabolite formation can be successfully utilized to translate to in vivo conditions.
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页数:11
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