A large body of evidence suggests hepatic uptake transporters, organic anion-transporting polypeptides (OATPs), are of high clinical relevance in determining the pharmacokinetics of substrate drugs, based on which recent regulatory guidances to industry recommend appropriate assessment of investigational drugs for the potential drug interactions. We recently proposed an extended clearance classification system (ECCS) framework in which the systemic clearance of class 1B and 3B drugs is likely determined by hepatic uptake. The ECCS framework therefore predicts the possibility of drug-drug interactions (DDIs) involving OATPs and the effects of genetic variants of SLCO1B1 early in the discovery and facilitates decision making in the candidate selection and progression. Although OATP-mediated uptake is often the rate-determining process in the hepatic clearance of substrate drugs, metabolic and/or biliary components also contribute to the overall hepatic disposition and, more importantly, to liver exposure. Clinical evidence suggests that alteration in biliary efflux transport or metabolic enzymes associated with genetic polymorphism leads to change in the pharmacodynamic response of statins, for which the pharmacological target resides in the liver. Perpetrator drugs may show inhibitory and/or induction effects on transporters and enzymes simultaneously. It is therefore important to adopt models that frame these multiple processes in a mechanistic sense for quantitative DDI predictions and to deconvolute the effects of individual processes on the plasma and hepatic exposure. In vitro data-informed mechanistic static and physiologically based pharmacokinetic models are proven useful in rationalizing and predicting transporter-mediated DDIs and the complex DDIs involving transporter-enzyme interplay.
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http://dx.doi.org/10.1002/jcph.695 | DOI Listing |
Drug Metab Dispos
September 2024
Quantitative, Translational, and ADME Sciences, Abbvie Inc., North Chicago, Illinois
Hepatic clearance ( ) prediction is a critical parameter to estimate human dose. However, underpredictions are common, especially for slowly metabolized drugs, and may be attributable to drug properties that pose challenges for conventional in vitro absorption, distribution, metabolism, and elimination (ADME) assays, resulting in nonvalid data, which prevents in vitro to in vivo extrapolation and predictions. Other processes, including hepatocyte and biliary distribution via transporters, can also play significant roles in Recent advances in understanding the interplay of metabolism and drug transport for clearance processes have aided in developing the extended clearance model.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
April 2024
Genentech, Inc., South San Francisco, California, USA.
Pralsetinib, a potent and selective inhibitor of oncogenic RET fusion and RET mutant proteins, is a substrate of the drug metabolizing enzyme CYP3A4 and a substrate of the efflux transporter P-gp based on in vitro data. Therefore, its pharmacokinetics (PKs) may be affected by co-administration of potent CYP3A4 inhibitors and inducers, P-gp inhibitors, and combined CYP3A4 and P-gp inhibitors. With the frequent overlap between CYP3A4 and P-gp substrates/inhibitors, pralsetinib is a challenging and representative example of the need to more quantitatively characterize transporter-enzyme interplay.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
July 2022
Laboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, School of Pharmacy, Josai International University, Tokyo, Japan.
P-glycoprotein (P-gp) is an efflux transporter that plays an important role in the pharmacokinetics of its substrate, and P-gp activities can be altered by induction and inhibition effects of rifampicin. This study aimed to establish a physiologically based pharmacokinetic (PBPK) model of rifampicin to predict the P-gp-mediated drug-drug interactions (DDIs) and assess the DDI impact in the intestine, liver, and kidney. The induction and inhibition parameters of rifampicin for P-gp were estimated using two of seven DDI cases of rifampicin and digoxin and incorporated into our previously constructed PBPK model of rifampicin.
View Article and Find Full Text PDFDrug Metab Dispos
July 2022
Global Drug Metabolism and Pharmacokinetics, Takeda Development Center Americas, Inc. (TDCA), Lexington, Massachusetts
Quantitative assessment of hepatic clearance (CL) of drugs is critical to accurately predict human dose and drug-drug interaction (DDI) liabilities. This is challenging for drugs that involve complex transporter-enzyme interplay. In this study, we demonstrate this interplay in the CL and DDI effect in the presence of CYP3A4 perpetrator for pevonedistat using both the conventional clearance model (CCM) and the extended clearance model (ECM).
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