No abstract

The hepatic organic anion transporting polypeptides (OATPs) influence the pharmacokinetics of several drug classes and are involved in many clinical drug–drug interactions. Predicting potential interactions with OATPs is, therefore, of value. Here, we developed in vitro and in silico models for identification and prediction of specific and general inhibitors of OATP1B1, OATP1B3, and OATP2B1. The maximal transport activity (MTA) of each OATP in human liver was predicted from transport kinetics and protein quantification. We then used MTA to predict the effects of a subset of inhibitors on atorvastatin uptake in vivo. Using a data set of 225 drug-like compounds, 91 OATP inhibitors were identified. In silico models indicated that lipophilicity and polar surface area are key molecular features of OATP inhibition. MTA predictions identified OATP1B1 and OATP1B3 as major determinants of atorvastatin uptake in vivo. The relative contributions to overall hepatic uptake varied with isoform specificities of the inhibitors.

Intestinal transporters are crucial determinants in the oral absorption of many drugs. We therefore studied the mRNA expression (N = 33) and absolute protein content (N = 10) of clinically relevant transporters in healthy epithelium of the duodenum, the proximal and distal jejunum and ileum, and the ascending, transversal, descending, and sigmoidal colon of six organ donors (24-54 years). In the small intestine, the abundance of nearly all studied proteins ranged between 0.2 and 1.6 pmol/mg with the exception of those of OCT3 (<0.1 pmol/mg) and PEPT1 (2.6-4.9 pmol/mg) that accounted for ∼50% of all measured transporters. OATP1A2 was not detected in any intestinal segment. ABCB1, ABCG2, PEPT1, and ASBT were significantly more abundant in jejunum and ileum than in colon. In contrast to this, the level of expression of ABCC2, ABCC3, and OCT3 was found to be highest in colon. Site-dependent differences in the levels of gene and protein expression were observed for ABCB1 and ASBT. Significant correlations between mRNA and protein levels have been found for ABCG2, ASBT, OCT3, and PEPT1 in the small intestine. Our data provide further physiological pieces of the puzzle required to predict intestinal drug absorption in humans.

ABSTRACT:With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic aniontransporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under-and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.

Intracellular concentrations of drugs and metabolites are often important determinants of efficacy, toxicity, and drug interactions. Hepatic drug distribution can be affected by many factors, including physicochemical properties, uptake/efflux transporters, protein binding, organelle sequestration, and metabolism. This white paper highlights determinants of hepatocyte drug/metabolite concentrations and provides an update on model systems, methods, and modeling/simulation approaches used to quantitatively assess hepatocellular concentrations of molecules. The critical scientific gaps and future research directions in this field are discussed.