Quantification of Hepatic Organic Anion Transport Proteins OAT2 and OAT7 in Human Liver Tissue and Primary Hepatocytes

Organic anion transporter (OAT) 2 and OAT7 were recently shown to be involved in the hepatic uptake of drugs; however, there is limited understanding of the population variability in the expression of these transporters in liver. There is also a need to derive relative expression-based scaling factors (REFs) that can be used to bridge in vitro functional data to the in vivo drug disposition. To this end, we quantified OAT2 and OAT7 surrogate peptide abundance in a large number of human liver tissue samples (<i>n</i> = 52), as well as several single-donor cryopreserved human hepatocyte lots (<i>n</i> = 30) by a novel, validated liquid chromatography tandem mass spectrometry (LC–MS/MS) method. The average surrogate peptide expression of OAT2 and OAT7 in the liver samples was 1.52 ± 0.57 and 4.63 ± 1.58 fmol/μg membrane protein, respectively. While we noted statistically significant differences (<i>p</i> < 0.05) in hepatocyte and liver tissue abundances for both OAT2 and OAT7, the differences were relatively small (1.8- and 1.5-fold difference in median values, respectively). Large interindividual variability was noted in the hepatic expression of OAT2 (16-fold in liver tissue and 23-fold in hepatocytes). OAT7, on the other hand, showed less interindividual variability (4-fold) in the livers, but high variability for the hepatocyte lots (27-fold). A significant positive correlation in OAT2 and OAT7 expression was observed, but expression levels were neither associated with age nor sex. In conclusion, our data suggest marked interindividual variability in the hepatic expression of OAT2/7, which may contribute to the pharmacokinetic variability of their substrates. Because both transporters were less abundant in hepatocytes than livers, a REF-based approach is recommended when scaling in vitro hepatocyte transport data to predict hepatic drug clearance and liver exposure of OAT2/7 substrates

Clearance Mechanism Assignment and Total Clearance Prediction in Human Based upon in Silico Models

We introduce a two-tier model based on an exhaustive data set, where discriminant models based on principal component analysis (PCA) and partial least squares (PLS) are used separately and in conjunction, and we show that PCA is highly discriminant approaching 95% accuracy in the assignment of the primary clearance mechanism. Furthermore, the PLS model achieved a quantitative predictive performance comparable to methods based on scaling of animal data while not requiring the use of either in vivo or in vitro data, thus sparing the use of animal. This is likely the highest performance that can be expected from a computational approach, and further improvements may be difficult to reach. We further offer the medicinal scientist a PCA model to guide in vitro and/or in vivo studies to help limit the use of resources via very rapid computations

Special Section on Prediction of Human Pharmacokinetic Parameters from In Vitro Systems-Perspective A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

ABSTRACT Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drugdisposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, halflife, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data

Hepatic Disposition of Gemfibrozil and Its Major Metabolite Gemfibrozil 1‑<i>O</i>‑β-Glucuronide

Gemfibrozil (GEM), which decreases serum triglycerides and low density lipoprotein, perpetrates drug–drug interactions (DDIs) with several drugs. These DDIs are primarily attributed to the inhibition of drug transporters and metabolic enzymes, particularly cytochrome P450 (CYP) 2C8 by the major circulating metabolite gemfibrozil 1-<i>O</i>-β-glucuronide (GG). Here, we characterized the transporter-mediated hepatic disposition of GEM and GG using sandwich-cultured human hepatocytes (SCHH) and transporter-transfect systems. Significant active uptake was noted in SCHH for the metabolite. GG, but not GEM, showed substrate affinity to organic anion transporting polypeptide (OATP) 1B1, 1B3, and 2B1. In SCHH, glucuronidation was characterized affinity constants (<i>K</i>_m) of 7.9 and 61.4 μM, and biliary excretion of GG was observed. Furthermore, GG showed active basolateral efflux from preloaded SCHH and ATP-dependent uptake into membrane vesicles overexpressing multidrug resistance-associated protein (MRP) 2, MRP3, and MRP4. A mathematical model was developed to estimate hepatic uptake and efflux kinetics of GEM and GG based on SCHH studies. Collectively, the hepatic transporters play a key role in the disposition and thus determine the local concentrations of GEM and more so for GG, which is the predominant inhibitory species against CYP2C8 and OATP1B1