Emi Kimoto

Classification of inhibitors of hepatic organic anion transporting polypeptides (OATPs): influence of protein expression on drug-drug interactions.

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.

Mechanistic pharmacokinetic modeling for the prediction of transporter-mediated disposition in humans from sandwich culture human hepatocyte data

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 anion-transporting 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.

Mechanistic Modeling to Predict the Transporter- and Enzyme-Mediated Drug-Drug Interactions of Repaglinide

ABSTRACTPurposeQuantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide.MethodsIn vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-β-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data.ResultsIn vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-β-glucuronide.ConclusionsThis study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

Characterization of organic anion transporting polypeptide (OATP) expression and its functional contribution to the uptake of substrates in human hepatocytes.

Since the substrate specificities of OATP1B1, 1B3, and 2B1 are broad and overlapping, the contribution of each isoform to the overall hepatic uptake is of concern when assessing transporter-mediated drug-drug interactions (DDIs) or genetic polymorphism impact in the clinic. Herein, we quantitatively measured OATP proteins in cryopreserved hepatocytes, sandwich-cultured human hepatocytes (SCHH), and the liver, and examined the relationship with functional uptake of OATP substrates in an effort to identify the OATP isoform(s) contributing to the hepatic uptake of pitavastatin. The modulation of OATP expression in SCHH was found to be lot-dependent. However, OATP protein measurements averaged from 5 lots of SCHH were comparable to that of suspended hepatocytes. All three OATP transporters in suspended hepatocytes and SCHH were significantly lower than those in the liver. In SCHH, the uptake of CCK-8 and pravastatin was found to be associated with the expression of OATP1B3 and OATP1B1, respectively. In suspended hepatocytes, OATP1B1 appeared to show a positive trend with respect to the uptake of pitavastatin, which suggests a selective contribution of OATP1B1 to pitavastatin transport and thus an OATP quantitative protein expression-activity relationship. While the passive diffusion of rosuvastatin in SCHH was consistent across hepatocyte lots, the passive diffusion of pitavastatin varied over a broad range (>4-fold) in suspended hepatocytes and was inversely correlated with transporter-mediated uptake, presumably due to cell membrane alterations imparted by cryopreservation. Collectively, SCHH maintains OATP protein expression and membrane integrity and, if feasible when considering research goals, would be considered a superior tool for the characterization of in vitro transport parameters without the complication of membrane leakage.

In Vitro Evaluation of Hepatic Transporter-Mediated Clinical Drug-Drug Interactions: Hepatocyte Model Optimization and Retrospective Investigation

To assess the feasibility of using sandwich-cultured human hepatocytes (SCHHs) as a model to characterize transport kinetics for in vivo pharmacokinetic prediction, the expression of organic anion-transporting polypeptide (OATP) proteins in SCHHs, along with biliary efflux transporters, was confirmed quantitatively by liquid chromatography-tandem mass spectrometry. Rifamycin SV (Rif SV), which was shown to completely block the function of OATP transporters, was selected as an inhibitor to assess the initial rates of active uptake. The optimized SCHH model was applied in a retrospective investigation of compounds with known clinically significant OATP-mediated uptake and was applied further to explore drug-drug interactions (DDIs). Greater than 50% inhibition of active uptake by Rif SV was found to be associated with clinically significant OATP-mediated DDIs. We propose that the in vitro active uptake value therefore could serve as a cutoff for class 3 and 4 compounds of the Biopharmaceutics Drug Disposition Classification System, which could be integrated into the International Transporter Consortium decision tree recommendations to trigger clinical evaluations for potential DDI risks. Furthermore, the kinetics of in vitro hepatobiliary transport obtained from SCHHs, along with protein expression scaling factors, offer an opportunity to predict complex in vivo processes using mathematical models, such as physiologically based pharmacokinetics models.

Quantitative assessment of the contribution of sodium-dependent taurocholate co-transporting polypeptide (NTCP) to the hepatic uptake of rosuvastatin, pitavastatin and fluvastatin

Hepatic uptake transport is often the rate‐determining step in the systemic clearance of drugs. The ability to predict uptake clearance and to determine the contribution of individual transporters to overall hepatic uptake is therefore critical in assessing the potential pharmacokinetic and pharmacodynamic variability associated with drug–drug interactions and pharmacogenetics. The present study revisited the interaction of statin drugs, including pitavastatin, fluvastatin and rosuvastatin, with the sodium‐dependent taurocholate co‐transporting polypeptide (NTCP) using gene transfected cell models. In addition, the uptake clearance and the contribution of NTCP to the overall hepatic uptake were assessed using in vitro hepatocyte models. Then NTCP protein expression was measured by a targeted proteomics transporter quantification method to confirm the presence and stability of NTCP expression in suspended and cultured hepatocyte models. It was concluded that NTCP‐mediated uptake contributed significantly to active hepatic uptake in hepatocyte models for all three statins. However, the contribution of NTCP‐mediated uptake to the overall active hepatic uptake was compound‐dependent and varied from about 24% to 45%. Understanding the contribution of individual transporter proteins to the overall hepatic uptake and its functional variability when other active hepatic uptake pathways are interrupted could improve the current prediction practice used to assess the pharmacokinetic variability due to drug–drug interactions, pharmacogenetics and physiopathological conditions in humans. Copyright

C-Aryl glycoside inhibitors of SGLT2: Exploration of sugar modifications including C-5 spirocyclization

Modifications to the sugar portion of C-aryl glycoside sodium glucose transporter 2 (SGLT2) inhibitors were explored, including systematic deletion and modification of each of the glycoside hydroxyl groups. Based on results showing activity to be quite tolerant of structural change at the C-5 position, a series of novel C-5 spiro analogues was prepared. Some of these analogues exhibit low nanomolar potency versus SGLT2 and promote urinary glucose excretion (UGE) in rats. However, due to sub-optimal pharmacokinetic parameters (in particular half-life), predicted human doses did not meet criteria for further advancement.

Impact of drug transporter pharmacogenomics on pharmacokinetic and pharmacodynamic variability – considerations for drug development

Introduction: Drug transporter proteins are expressed on the cell membrane, regulating substrate exposure in systemic circulation and/or peripheral tissues. Genetic polymorphism of drug transporter genes encoding these proteins could alter the functional activity and/or protein expression, having effects on absorption, distribution, metabolism and excretion (ADME), efficacy and adverse effects. Areas covered: The authors provide the reader with an overview of the pharmacogenetics (PGx) of 12 membrane transporters. The clinical literature is summarized as to the quantitative significance on pharmacokinetics (PK) and implications on pharmacodynamics (PD) and adverse effects, due to transporter influence on intracellular drug concentrations. Expert opinion: Unlike polymorphisms for cytochrome P450s (CYPs) resulting in large magnitude of PK variation, genetic mutations for membrane transporters are typically less than threefold alteration in systemic PK for drugs with a few exceptions. However, substantially greater changes in intracellular drug levels may result. We are aware of 1880 exome variants in 12 of the best-studied transporters to date, and nearly 40% of these change the amino acid. However, the functional consequences of most of these variants remain to be determined, and have only been empirically evaluated for a handful. To the extent that genetic polymorphisms impact ADME, it is a variable that will contribute to ethnic differences due to substantial frequency differences for the known variants.

Quantitative Rationalization of Gemfibrozil Drug Interactions: Consideration of Transporters-Enzyme Interplay and the Role of Circulating Metabolite Gemfibrozil 1-O-β-Glucuronide

Gemfibrozil has been suggested as a sensitive cytochrome P450 2C8 (CYP2C8) inhibitor for clinical investigation by the U.S. Food and Drug Administration and the European Medicines Agency. However, gemfibrozil drug-drug interactions (DDIs) are complex; its major circulating metabolite, gemfibrozil 1-O-β-glucuronide (Gem-Glu), exhibits time-dependent inhibition of CYP2C8, and both parent and metabolite also behave as moderate inhibitors of organic anion transporting polypeptide 1B1 (OATP1B1) in vitro. Additionally, parent and metabolite also inhibit renal transport mediated by OAT3. Here, in vitro inhibition data for gemfibrozil and Gem-Glu were used to assess their impact on the pharmacokinetics of several victim drugs (including rosiglitazone, pioglitazone, cerivastatin, and repaglinide) by employing both static mechanistic and dynamic physiologically based pharmacokinetic (PBPK) models. Of the 48 cases evaluated using the static models, about 75% and 98% of the DDIs were predicted within 1.5- and 2-fold of the observed values, respectively, when incorporating the interaction potential of both gemfibrozil and its 1-O-β-glucuronide. Moreover, the PBPK model was able to recover the plasma profiles of rosiglitazone, pioglitazone, cerivastatin, and repaglinide under control and gemfibrozil treatment conditions. Analyses suggest that Gem-Glu is the major contributor to the DDIs, and its exposure needed to bring about complete inactivation of CYP2C8 is only a fraction of that achieved in the clinic after a therapeutic gemfibrozil dose. Overall, the complex interactions of gemfibrozil can be quantitatively rationalized, and the learnings from this analysis can be applied in support of future predictions of gemfibrozil DDIs.

Quantitative prediction of transporter- and enzyme-mediated clinical drug-drug interactions of organic anion-transporting polypeptide 1B1 substrates using a mechanistic net-effect model.

Quantitative prediction of complex drug-drug interactions (DDIs) involving hepatic transporters and cytochromes P450 (P450s) is challenging. We evaluated the extent of DDIs of nine victim drugs—which are substrates to organic anion-transporting polypeptide 1B1 and undergo P450 metabolism or biliary elimination—caused by five perpetrator drugs, using in vitro data and the proposed extended net-effect model. Hepatobiliary transport and metabolic clearance estimates were obtained from in vitro studies. Of the total of 62 clinical interaction combinations assessed using the net-effect model, 58 (94%) could be predicted within a 2-fold error, with few false-negative predictions. Model predictive performance improved significantly when in vitro active uptake clearance was corrected to recover in vivo clearance. The basic R-value model yielded only 63% predictions within 2-fold error. This study demonstrates that the interactions involving transporter-enzyme interplay need to be mechanistically assessed for quantitative rationalization and prospective prediction.