Transporter‐Enzyme Interplay: Deconvoluting Effects of Hepatic Transporters and Enzymes on Drug Disposition Using Static and Dynamic Mechanistic Models. (July 2016)

• Record Type: Journal Article
• Authors: Varma, Manthena V.; El‐Kattan, Ayman F.
• Other Names: Arya Vikram guestEditor.; Kiser Jennifer J. guestEditor.
• Is Part Of: Journal of clinical pharmacology. Volume 56(2016)Supplement 7
• Page Start: S99
• Page End: S109
• Publication Date: 2016-07
• Subjects: cytochrome P‐450 -- drug transporters -- drug‐drug interactions -- extended clearance classification system -- organic anion‐transporting polypeptides -- physiologically based pharmacokinetic model -- transporter‐enzyme interplay; Pharmacology -- Periodicals; Pharmacology -- Periodicals; Pharmacology, Clinical -- Periodicals; 615.1
• DOI: 10.1002/jcph.695
• Languages: English
• ISSNs: 0091-2700

Abstract

Abstract: 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.