Physiologically Based Modeling of Pravastatin Transporter-Mediated Hepatobiliary Disposition and Drug-Drug Interactions

Purpose

To develop physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and drug-drug interactions (DDI) of pravastatin, using the in vitro transport parameters.

Methods

In vitro hepatic sinusoidal active uptake, passive diffusion and canalicular efflux intrinsic clearance values were determined using sandwich-culture human hepatocytes (SCHH) model. PBPK modeling and simulations were implemented in Simcyp (Sheffield, UK). DDI with OATP1B1 inhibitors, cyclosporine, gemfibrozil and rifampin, was also simulated using inhibition constant (Ki) values.

Results

SCHH studies suggested active uptake, passive diffusion and efflux intrinsic clearance values of 1.9, 0.5 and 1.2?μL/min/10⁶cells, respectively, for pravastatin. PBPK model developed, using transport kinetics and scaling factors, adequately described pravastatin oral plasma concentration-time profiles at different doses (within 20% error). Model based prediction of DDIs with gemfibrozil and rifampin was similar to that observed. However, pravastatin-cyclosporine DDI was underpredicted (AUC ratio 4.4 Vs ~10). Static (R-value) model predicted higher magnitude of DDI compared to the AUC ratio predicted by the PBPK modeling.

Conclusions

PBPK model of pravastatin, based on in vitro transport parameters and scaling factors, was developed. The approach described can be used to predict the pharmacokinetics and DDIs associated with hepatic uptake transporters.     

Prediction of pharmacokinetic profile of valsartan in human based on in vitro uptake transport data

The aim of this study was to evaluate a strategy based on a physiologically based pharmacokinetic (PBPK) model for the prediction of PK profiles in human using in vitro data when elimination of compounds relies on active transport processes. The strategy was first applied to rat in vivo and in vitro data in order to refine the PBPK model. The model could then be applied to human in vitro uptake transport data using valsartan as a probe substrate. Plated rat and human hepatocytes, and cell lines overexpressing human OATP1B1 and OATP1B3 were used for in vitro uptake experiments. The uptake rate of valsartan was higher for rat hepatocytes (K _m,u = 28.4 ± 3.7 μM, V _max = 1318 ± 176 pmol/mg/min and P _dif = 1.21 ± 0.42 μl/mg/min) compared to human hepatocytes (K _m,u = 44.4 ± 14.6 μM, V _max = 304 ± 85 pmol/mg/min and P _dif = 0.724 ± 0.271 μl/mg/min). OATP1B1 and 1B3 parameters were correlated to human hepatocyte data using experimentally established relative activity factors (RAF). Resulting PBPK simulations using those in vitro data were compared for plasma (human and rat) and bile (rat) concentration–time profiles following i.v. bolus administration of valsartan. An uncertainty analysis indicated that the scaled in vitro uptake clearance had to be adjusted with an additional empirical scaling factor of 5 to match the plasma concentrations and biliary excretion profiles. Applying this model, plasma clearances (CL_P) for rat and human were predicted within two-fold relative to predictions based on respective in vitro data. The corrected hepatic uptake transport kinetic parameters enabled the prediction of valsartan in vivo PK profiles and plasma clearances, using PBPK modeling. Moreover, the interspecies difference in elimination rate observed in vivo was correctly reflected in the transport parameters determined in vitro. More data are needed to support more general applications of the proposed approach including its use for metabolized compounds.     

Physiologically based pharmacokinetic (PBPK) modeling of disposition of epiroprim in humans

The objective of this study was to use in synergy physiologically based and empirical approaches to estimate the drug-specific input parameters of PBPK models of disposition to simulate the plasma concentration-time profile of epiroprim in human. The estimated input parameters were the tissue:plasma partition coefficients (Pt:p) for distribution and the blood clearance (CL) for the in vivo conditions. Epiroprim represents a challenge for such methods, because it shows large interspecies differences in its pharmacokinetic properties. Two approaches were used to predict the human Pt:p values: the tissue composition model (TCM) and the "Arundel approach" based on the volume of distribution at steady state (Vdss) determined in vivo in the rat. CL in human was predicted by (1) conventional allometric scaling of in vivo animal clearances (CAS), (2) physiologically based direct scaling up of in vitro hepatocyte data (DSU), and (3) allometric scaling of animal intrinsic in vivo blood CL normalized by the ratios of animal:human intrinsic clearances determined in vitro with hepatocytes (NAS). The performance of prediction was assessed by comparing separately the above pharmacokinetic parameters (Vdss estimated from the Pt:p values and blood CL) with the corresponding in vivo data obtained from the plasma kinetic profiles. These input parameters were used in PBPK models, and the resulting plasma concentration-time profiles of epiroprim were compared with those observed in rat and human. Previously to the construction of the human PBPK model, a model for the rat was also developed to gain more confidence on the model structure and assumptions. Overall, using the TCM and the NAS for the parameterization of the distribution and clearance, respectively, the PBPK model gave the more accurate predictions of epiroprim's disposition in human. This study represents therefore an attractive approach, which may potentially help the clinical candidate selection.     

A novel strategy for physiologically based predictions of human pharmacokinetics

BACKGROUND: The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics. METHODS: PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods. RESULTS: By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (V(z)/F), terminal elimination half-life (t(1/2)), peak plasma concentration (C(max)), area under the plasma concentration-time curve (AUC) and time to reach C(max) (t(max)), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach. CONCLUSIONS: Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.     

Application of physiologically based pharmacokinetic modeling and clearance concept to drugs showing transporter-mediated distribution and clearance in humans

This review illustrates the concept of a rate-determining process in the overall hepatic elimination of anionic drugs that involves transporters in the uptake process. A kinetic study in rats has demonstrated that uptake is the rate-determining process for most anionic drugs, and this is likely to hold true for the hepatic elimination of statins in humans. To simulate the effects of variations in the transporter activities on systemic and liver exposure, a physiologically based pharmacokinetic model was constructed for pravastatin, the overall elimination of which involves OATP1B1 and MRP2 in the hepatic uptake and canalicular efflux, respectively. The plasma concentrations of pravastatin in humans were successfully reproduced using the kinetic parameters extrapolated from in vitro data obtained using human hepatocytes and canalicular membrane vesicles and the scaling factors determined in rats. Sensitivity analyses showed that a variation in hepatic uptake altered the plasma concentration of pravastatin markedly, but had a small effect on the liver concentration, and vice versa for the canalicular efflux. Therefore, variation in the OATP1B1 activities will have small and large impacts on the therapeutic efficacy and adverse effect (myopathy) of pravastatin, respectively, whereas that affecting the MRP2 activities may have an opposite effect (i.e., large and small impacts on the therapeutic efficacy and side effect). This pharmacokinetic characteristics likely hold true for other anionic statins, i.e., variation of OATP1B1 is associated with the risk of adverse reactions, whereas that of sequestration mechanisms causes the variation of their pharmacological effect.     

Prediction of human plasma concentration-time profiles of monoclonal antibodies from monkey data by a species-invariant time method

We have previously reported that human total body clearance (CL) and steady-state volume of distribution (Vss) of monoclonal antibodies (mAbs) could be predicted reasonably well from monkey data alone using simple allometry with scaling exponents of 0.79 and 1.12 (for soluble targets), and 0.96 and 1.00 (for membrane-bound targets). In the present study, to predict the plasma concentration-time profiles of mAbs in humans, we employed simple dose-normalization and species-invariant time methods (elementary Dedrick plot and complex Dedrick plot), based on the monkey data and the scaling exponents we previously determined. The results demonstrated that the species-invariant time methods were able to provide higher accuracy of prediction than simple dose-normalization, regardless of the type of target antigens (soluble or membrane-bound). The accuracy between elementary Dedrick plot and complex Dedrick plot was nearly equivalent. The predicted human CL and Vss using species-invariant time methods were within mostly 2-fold differences from the observed values. The prediction not only of pharmacokinetic (PK) parameters but also of the plasma concentration-time profile in humans can serve as guidelines for better planning of clinical studies on mAbs.     

Gemfibrozil and its glucuronide inhibit the hepatic uptake of pravastatin mediated by OATP1B1

When pravastatin (40 mg/day) was co-administered with gemfibrozil (600 mg, b.i.d., 3 days) to man, the AUC of pravastatin increased approximately 2-fold. We have clarified that OATP1B1 is a key determinant of the hepatic uptake of pravastatin in humans. Thus, we hypothesized that gemfibrozil and the main plasma metabolites, a glucuronide (gem-glu) and a carboxylic acid metabolite (gem-M3), might inhibit the hepatic uptake of pravastatin and lead to the elevation of the plasma concentration of pravastatin. Gemfibrozil and gem-glu inhibited the uptake of (14)C-pravastatin by human hepatocytes with K(i) values of 31.7 microM and 15.7 microM, respectively and also inhibited pravastatin uptake by OATP1B1-expressing Xenopus laevis oocytes with K(i) values of 15.1 microM and 7.6 microM. Additionally, we examined the biliary transport of pravastatin and demonstrated that pravastatin was transported by MRP2 using both human canalicular membrane vesicles (hCMVs) and human MRP2-expressing vesicles. However, gemfibrozil, gem-glu and gem-M3 did not affect the biliary transport of pravastatin by MRP2. Considering the plasma concentrations of gemfibrozil and gem-glu in humans, the inhibition of OATP1B1-mediated hepatic uptake of pravastatin by gem-glu would contribute, at least in part, to the elevation of plasma concentration of pravastatin by the concomitant use of gemfibrozil.     

Modelling and PBPK Simulation in Drug Discovery

Physiologically based pharmacokinetic (PBPK) models are composed of a series of differential equations and have been implemented in a number of commercial software packages. These models require species-specific and compound-specific input parameters and allow for the prediction of plasma and tissue concentration time profiles after intravenous and oral administration of compounds to animals and humans. PBPK models allow the early integration of a wide variety of preclinical data into a mechanistic quantitative framework. Use of PBPK models allows the experimenter to gain insights into the properties of a compound, helps to guide experimental efforts at the early stages of drug discovery, and enables the prediction of human plasma concentration time profiles with minimal (and in some cases no) animal data. In this review, the application and limitations of PBPK techniques in drug discovery are discussed. Specific reference is made to its utility (1) at the lead development stage for the prioritization of compounds for animal PK studies and (2) at the clinical candidate selection and “first in human” stages for the prediction of human PK.     

A Novel Experimental and Theoretical Method for Estimating Albumin-Mediated Hepatic Uptake Based on the Albumin Binding Fraction in Plasma and Human PK Prediction Using a Physiologically-Based Pharmacokinetic Approach

Recently, protein-facilitated uptake has been suggested to be an important factor in the precise prediction of the pharmacokinetic (PK) profiles of drugs. In our previous study, a physiologically-based pharmacokinetic (PBPK) approach considering the mechanism of albumin-mediated hepatic uptake was developed for predicting human PK profiles. It was assumed that drugs affected by albumin-mediated hepatic uptake would bind only to albumin, which means that there would be over-estimation of the contribution of protein-facilitated uptake for a drug that could bind to multiple proteins. In this study, we developed a method that can evaluate the albumin binding fraction in plasma considering the affinity for other proteins. Based on the albumin binding fraction, the contribution of albumin-mediated hepatic uptake was theoretically estimated, and then the human PK profiles were predicted by our proposed PBPK approach incorporating this mechanism. As a result, the predicted human PK profiles agreed well with the observed ones, and the absolute average fold error of PK parameters was almost within a 1.5-fold error on average. These findings show the importance of considering protein-facilitated uptake and also suggest that our proposed PBPK approach can be useful in scientific discussions with regulatory authorities.     

Early identification of drug-induced impairment of gastric emptying through physiologically based pharmacokinetic (PBPK) simulation of plasma concentration-time profiles in rat

Inhibition of gastric emptying rate can have adverse effects on the absorption of food and nutrients. The absorption phase of the plasma concentration-time profile of a compound administered orally to pre-clinical species reflects among others, the gastric and intestinal transit kinetics, and can thus assist in the early identification of delayed gastric emptying. The purpose of this article is to demonstrate the value of Physiologically Based Pharmacokinetic (PBPK) modelling in the early identification of drug induced impairment of gastric emptying from pharmacokinetic profiles. To our knowledge, this is first time that the value of a generic PBPK model for hypothesis testing has been demonstrated with examples. A PBPK model built in-house using MATLAB package and incorporating absorption, metabolism, distribution, biliary and renal elimination models has been employed for the simulation of concentration-time profiles. PBPK simulations of a few compounds that are currently in drug discovery projects show that the observed initial absorption phase of their concentration-time profiles in rat were consistent with reduced gastric emptying rates. The slow uptake of these compounds into the systemic circulation is reflected in their pharmacokinetic profiles but it is not obvious until PBPK simulations are done. Delayed gastric emptying rates of these compounds in rats were also independently observed in x-ray imaging. PBPK simulations can provide early alerts to drug discovery projects, besides aiding the understanding of complex mechanisms that determine the lineshapes of pharmacokinetic profiles. The application of PBPK simulations in the early detection of gastric emptying problems with existing data and without the need to resort to additional animal studies, is appealing both from an economic and ethical standpoint.     

Gemfibrozil and its glucuronide inhibit the hepatic uptake of pravastatin mediated by OATP1B1

When pravastatin (40?mg/day) was co-administered with gemfibrozil (600?mg, b.i.d., 3 days) to man, the AUC of pravastatin increased approximately 2-fold. We have clarified that OATP1B1 is a key determinant of the hepatic uptake of pravastatin in humans. Thus, we hypothesized that gemfibrozil and the main plasma metabolites, a glucuronide (gem-glu) and a carboxylic acid metabolite (gem-M3), might inhibit the hepatic uptake of pravastatin and lead to the elevation of the plasma concentration of pravastatin. Gemfibrozil and gem-glu inhibited the uptake of ¹⁴C-pravastatin by human hepatocytes with K_i values of 31.7?µM and 15.7?µM, respectively and also inhibited pravastatin uptake by OATP1B1-expressing Xenopus laevis oocytes with K_i values of 15.1?µM and 7.6?µM. Additionally, we examined the biliary transport of pravastatin and demonstrated that pravastatin was transported by MRP2 using both human canalicular membrane vesicles (hCMVs) and human MRP2-expressing vesicles. However, gemfibrozil, gem-glu and gem-M3 did not affect the biliary transport of pravastatin by MRP2. Considering the plasma concentrations of gemfibrozil and gem-glu in humans, the inhibition of OATP1B1-mediated hepatic uptake of pravastatin by gem-glu would contribute, at least in part, to the elevation of plasma concentration of pravastatin by the concomitant use of gemfibrozil.     

Application of PBPK modelling in drug discovery and development at Pfizer

Early prediction of human pharmacokinetics (PK) and drug-drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need to be addressed to realize its application and utility more broadly.     

Development of a Translational Physiologically Based Pharmacokinetic Model for Antibody-Drug Conjugates: a Case Study with T-DM1

Systems pharmacokinetic (PK) models that can characterize and predict whole body disposition of antibody-drug conjugates (ADCs) are needed to support (i) development of reliable exposure-response relationships for ADCs and (ii) selection of ADC targets with optimal tumor and tissue expression profiles. Towards this goal, we have developed a translational physiologically based PK (PBPK) model for ADCs, using T-DM1 as a tool compound. The preclinical PBPK model was developed using rat data. Biodistribution of DM1 in rats was used to develop the small molecule PBPK model, and the PK of conjugated trastuzumab (i.e., T-DM1) in rats was characterized using platform PBPK model for antibody. Both the PBPK models were combined via degradation and deconjugation processes. The degradation of conjugated antibody was assumed to be similar to a normal antibody, and the deconjugation of DM1 from T-DM1 in rats was estimated using plasma PK data. The rat PBPK model was translated to humans to predict clinical PK of T-DM1. The translation involved the use of human antibody PBPK model to characterize the PK of conjugated trastuzumab, use of allometric scaling to predict human clearance of DM1 catabolites, and use of monkey PK data to predict deconjugation of DM1 in the clinic. PBPK model-predicted clinical PK profiles were compared with clinically observed data. The PK of total trastuzumab and T-DM1 were predicted reasonably well, and slight systemic deviations were observed for the PK of DM1-containing catabolites. The ADC PBPK model presented here can serve as a platform to develop models for other ADCs.     

Does the Systemic Plasma Profile Inform the Liver Profile? Analysis Using a Physiologically Based Pharmacokinetic Model and Individual Compounds

The physiologically based pharmacokinetic (PBPK) model for liver transporter substrates has been established previously and used for predicting drug–drug interactions (DDI) and for clinical practice guidance. So far, nearly all the published PBPK models for liver transporter substrates have one or more hepatic clearance processes (i.e., active uptake, passive diffusion, metabolism, and biliary excretion) estimated by fitting observed systemic data. The estimated hepatic clearance processes are then used to predict liver concentrations and DDI involving either systemic or liver concentration. However, the accuracy and precision of such predictions are unclear. In this study, we try to address this question by using the PBPK model to generate simulated compounds for which we know both systemic and liver profiles. We then developed an approach to assess the accuracy and precision of predicted liver concentration. With hepatic clearance processes estimated using plasma data, model predictions of liver are typically accurate (i.e., true value is bounded by predicted maximum and minimum); however, only for a few compounds are predictions also precise. The results of the current study indicate that extra attention is required when using the current PBPK approach to predict liver concentration and DDI for transporter substrates dependent upon liver concentrations.     

PBPK modeling of irbesartan: incorporation of hepatic uptake

Physiological based pharmacokinetic (PBPK) modeling is now commonly used in drug development to integrate human or animal physiological data in order to predict pharmacokinetic profiles. The aim of this work was to construct and refine a PBPK model of irbesartan taking into account its active uptake via OATP1B1/B3 in order to predict more accurately its pharmacokinetic profile using Simcyp^®. The activity and expression of the human hepatocyte transporters OATP1B1 and OATP1B3 were studied. The relative activity factors (RAFs) for OATP1B1 and OATP1B3 transporters were calculated from intrinsic clearances obtained by concentration dependent uptake experiments in human hepatocytes and HEK overexpressing cells: RAF_1B1 using estrone‐3‐sulfate and pitavastatine clearances, and RAF_1B3 using cholecystokinine octapeptide (CCK‐8) clearances. The relative expression factor (REF) was calculated by comparing immunoblotting of hepatocytes (REF_HH) or tissues (REF_tissue) with those of overexpressing HEK cells for each transporter. These scaling factors were applied in a PBPK model of irbesartan using the Simcyp® simulator. Pharmacokinetic simulation using REF_HH (1.82 for OATP1B1, 8.03 for OATP1B3) as an extrapolation factor was the closest to the human clinical pharmacokinetic profile of irbesartan. These investigations show the importance of integrating the contribution of the active uptake of a drug in the liver to improve PBPK modeling. Copyright © 2015 John Wiley & Sons, Ltd.     

Differential interaction of 3-hydroxy-3-methylglutaryl-coa reductase inhibitors with ABCB1, ABCC2, and OATP1B1.

The present study examined the interaction of four 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors (atorvastatin, lovastatin, and simvastatin in acid and lactone forms, and pravastatin in acid form only) with multidrug resistance gene 1 (MDR1, ABCB1) P-glycoprotein, multidrug resistance-associated protein 2 (MRP2, ABCC2), and organic anion-transporting polypeptide 1B1 (OATP1B1, SLCO21A6). P-glycoprotein substrate assays were performed using Madin-Darby canine kidney (MDCK) cells expressing MDR1, and the efflux ratios [the ratio of the ratio of basolateral-to-apical apparent permeability and apical-to-basolateral permeability between MDR1 and MDCK] were 1.87, 2.32/4.46, 2.17/3.17, and 0.93/2.00 for pravastatin, atorvastatin (lactone/acid), lovastatin (lactone/acid), and simvastatin (lactone/acid), respectively, indicating that these compounds are weak or moderate substrates of P-glycoprotein. In the inhibition assays (MDR1, MRP2, Mrp2, and OATP1B1), the IC50 values for efflux transporters (MDR1, MRP2, and Mrp2) were >100 microM for all statins in acid form except lovastatin acid (>33 microM), and the IC50 values were up to 10-fold lower for the corresponding lactone forms. In contrast, the IC50 values for the uptake transporter OATP1B1 were 3- to 7-fold lower for statins in the acid form compared with the corresponding lactone form. These data demonstrate that lactone and acid forms of statins exhibit differential substrate and inhibitor activities toward efflux and uptake transporters. The interconversion between the lactone and acid forms of most statins exists in the body and will potentially influence drug-transporter interactions, and may ultimately contribute to the differences in pharmacokinetic profiles observed between statins.     

Cyclosporine Inhibition of Hepatic and Intestinal CYP3A4, Uptake and Efflux Transporters: Application of PBPK Modeling in the Assessment of Drug-Drug Interaction Potential

Purpose

To apply physiologically-based pharmacokinetic (PBPK) modeling to investigate the consequences of reduction in activity of hepatic and intestinal uptake and efflux transporters by cyclosporine and its metabolite AM1.

Methods

Inhibitory potencies of cyclosporine and AM1 against OATP1B1, OATP1B3 and OATP2B1 were investigated in HEK293 cells +/? pre-incubation. Cyclosporine PBPK model implemented in Matlab was used to assess interaction potential (+/? metabolite) against different processes (uptake, efflux and metabolism) in liver and intestine and to predict quantitatively drug-drug interaction with repaglinide.

Results

Cyclosporine and AM1 were potent inhibitors of OATP1B1 and OATP1B3, IC₅₀ ranging from 0.019–0.093 μM following pre-incubation. Cyclosporine PBPK model predicted the highest interaction potential against liver uptake transporters, with a maximal reduction of >70% in OATP1B1 activity; the effect on hepatic efflux and metabolism was minimal. In contrast, 80–97% of intestinal P-gp and CYP3A4 activity was reduced due to the 50-fold higher cyclosporine enterocytic concentrations relative to unbound hepatic inlet. The inclusion of AM1 resulted in a minor increase in the predicted maximal reduction of OATP1B1/1B3 activity. Good predictability of cyclosporine-repaglinide DDI and the impact of dose staggering are illustrated.

Conclusions

This study highlights the application of PBPK modeling for quantitative prediction of transporter-mediated DDIs with concomitant consideration of P450 inhibition.     

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.     

Development of a physiologically based pharmacokinetic model for the rat central nervous system and determination of an in vitro-in vivo scaling methodology for the blood-brain barrier permeability of two transporter substrates, morphine and oxycodone

A whole-body physiologically based pharmacokinetic (PBPK) model was developed for the prediction of unbound drug concentration-time profiles in the rat brain, in which drug transfer across the blood–brain barrier (BBB) was treated mechanistically by separating the parameters governing the rate (permeability) of BBB transfer from brain binding. An in vitro–in vivo scaling strategy based on Caco-2 cell permeability was proposed to extrapolate the active transporter-driven component of this permeability, in which a relative activity factor, RAF, was estimated by fitting the model to rat in vivo profiles. This scaling factor could be interpreted as the ratio of transporter activity between the in vitro system and the in vivo BBB, for a given drug in a given in vitro system. Morphine and oxycodone were selected to evaluate this strategy, as substrates of BBB-located efflux and influx transporters, respectively. After estimation of their respective RAFs using the rat model, the PBPK model was used to simulate human brain concentration profiles assuming the same RAF, and the implications of this were discussed. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:4277–4292, 2012