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

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® 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.

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE).

BACKGROUND AND OBJECTIVE: The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results. METHODS: Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors. RESULTS: The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC. CONCLUSIONS: The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Novel method of measurement of in vitro drug uptake in OATP1B3 overexpressing cells in the presence of dextran.

BACKGROUND: In predictions about hepatic clearance (CLH), a number of studies explored the role of albumin and transporters in drug uptake by liver cells, challenging the traditional free-drug theory. It was proposed that liver uptake can occur for transporter substrate compounds not only from the drug's unbound form but also directly from the drug-albumin complex, a phenomenon known as uptake facilitated by albumin. In contrast to albumin, dextran does not exhibit binding properties for compounds. However, as a result of its inherent capacity for stabilization, it is widely used to mimic conditions within cells. METHODS: The uptake of eight known substrates of the organic anion-transporting polypeptide 1B3 (OATP1B3) was assessed using a human embryonic kidney cell line (HEK293), which stably overexpresses this transporter. An inert polymer, dextran, was used to simulate cellular conditions, and the results were compared with experiments involving human plasma and human serum albumin (HSA). RESULTS: This study is the first to demonstrate that dextran increases compound uptake in cells with overexpression of the OATP1B3 transporter. Contrary to the common theory that highly protein-bound ligands interact with hepatocytes to increase drug uptake, the results indicate that dextran's interaction with test compounds does not significantly increase concentrations near the cell membrane surface. CONCLUSIONS: We evaluated the effect of dextran on the uptake of known substrates using OATP1B3 overexpressed in the HEK293 cell line, and we suggest that its impact on drug concentrations in liver cells may differ from the traditional role of plasma proteins and albumin.