Model-based approaches to predict drug–drug interactions associated with hepatic uptake transporters: preclinical, clinical and beyond

Abstract

Static and dynamic models can be convincingly applied to quantitatively predict drug interactions, early in drug discovery, to mitigate clinical risks as well as to avoid unnecessary clinical studies. Compared to basic models, which focus on individual processes, mechanistic models provide the ability to assess DDI potential for compounds with systemic disposition determined by both transporters and metabolic enzymes. However, complexities in the experimental tools and an apparent disconnect in the IVIVE of transport kinetics have limited the physiologically based pharmacokinetic modeling strategies. Emerging data on the expression of transporter proteins and tissue drug concentrations are expected to help bridge these gaps. In addition, detailed characterization of substrate kinetics can facilitate building comprehensive mechanistic models.

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

“…ATP binding-cassette (ABC) efflux transporters localized on the canalicular membrane of hepatocytes, such as P-glycoprotein (P-gp) (ABCB1), multidrug resistance-associated protein (MRP) 2 (ABCC2), breast cancer resistance protein (BCRP) (ABCG2), and BSEP (ABCB11), are mainly responsible for canalicular secretion (Ishikawa et al, 1995;Muller and Jansen, 1997;Suzuki and Sugiyama, 1999;Chandra and Brouwer, 2004). Based on the analysis of physicochemical property space, ionization state, size, and polarity were noted to be important determinants in the biliary elimination, and these properties are also closely associated with molecular interaction with the hepatic uptake transporters Varma et al, 2012a) The extended clearance equations (Equations 6 and 7) can be applied to get an estimate of the effect of transporter involvement in the hepatic disposition and further to predict the overall hepatic clearance (Liu and Pang, 2005;Barton et al, 2013).…”

“…6 and 7 using hepatocellularity and liver weight factors (Umehara and Camenisch, 2012;Varma et al, 2013c). Success of mechanistic-based prediction of transportermediated disposition and drug-drug interactions (DDIs) depends upon: 1) the adaptation of experimental tools and study design to obtain in vitro parameters that are relevant in vivo, 2) bridging the functional and protein expression difference between in vitro and in vivo systems, and 3) understanding the uncertainty associated with the parameters obtained from in vitro tools (Barton et al, 2013).…”

“…By regulatory standards, a significant contribution of a particular elimination pathway is generally considered when $25% of the NCE's elimination is subject to metabolic clearance, renal clearance, biliary elimination, or transporter-mediated disposition (albeit it needs to be appreciated that even complete inhibition of a pathway contributing 25% to clearance would only yield an increase in exposure of ;30%). During drug discovery, these estimates are obtained from a combination of in vitro studies utilizing human tissue preparations, evaluation of renal clearance in animals, and biliary elimination estimates obtained from studies with bile-duct-cannulated rats and/or dogs, or in vitro studies with sandwich-cultured human hepatocytes (see above) Barton et al, 2013). In certain cases, transporter-mediated disposition at the level of the intestine, liver, kidney, or biliary excretion could also impact NCE disposition, particularly for compounds classified as BDDCS class III and IV (Wu and Benet, 2005).…”

“…Therefore, a predicted R value .2 would generally require further assessment using mechanistic static or dynamic models for quantitative DDI evaluation. Drugs targeting the liver generally carry the implication that these agents could be victims of transporter-mediated DDIs, since liver uptake transporters (e.g., OATP1B1, OATP1B3) could be inhibited by coadministered drugs (Barton et al, 2013). NCE disposition is studied in systems with increased complexity: transporter gene overexpressing cells and primary isolated hepatocytes and/or sandwich-cultured human hepatocytes (see above).…”

Effect of Ondansetron on Metformin Pharmacokinetics and Response in Healthy Subjects

“…For a long time the study of pharmacokinetics has been largely focused on drug metabolizing enzymes (van Schaik, 2008;Hirota et al, 2013;Samer et al, 2013;Zanger and Schwab, 2013), but increasing evidence has clearly suggested the importance of membrane transporters in pharmacokinetics (Lu et al, 2010;Hua et al, 2012;Barton et al, 2013). For example, disposition of certain cationic drugs may be determined by their uptake via organic cation transporters (OCTs) from circulation to hepatocytes and/or renal tubular cells.…”