Comparison of In Vitro-In Vivo Extrapolation of Biliary Clearance Using an Empirical Scaling Factor Versus Transport-Based Scaling Factors in Sandwich-Cultured Rat Hepatocytes

Quantitative Prediction of OATP-Mediated Disposition and Biliary Clearance Using Human Liver Chimeric Mice

Drug biliary clearance (CLbile) in vivo is among the most difficult pharmacokinetic parameters to predict accurately and quantitatively because biliary excretion is influenced by metabolic enzymes, transporters, and passive diffusion across hepatocyte membranes. The purpose of this study is to demonstrate the use of Hu-FRG mice [Fah-/-/Rag2-/-/Il2rg-/- (FRG) mice transplanted with human-derived hepatocytes] to quantitatively predict human organic anion transporting polypeptide (OATP)-mediated drug disposition and CLbile To predict OATP-mediated disposition, six OATP substrates (atorvastatin, fexofenadine, glibenclamide, pitavastatin, pravastatin, and rosuvastatin) were administered intravenously to Hu-FRG and Mu-FRG mice (FRG mice transplanted with mouse hepatocytes) with or without rifampicin as an OATP inhibitor. We calculated the hepatic intrinsic clearance (CLh,int) and the change of hepatic clearance (CLh) caused by rifampicin (CLh ratio). We compared the CLh,int of humans with that of Hu-FRG mice and the CLh ratio of humans with that of Hu-FRG and Mu-FRG mice. For predicting CLbile, 20 compounds (two cassette doses of 10 compounds) were administered intravenously to gallbladder-cannulated Hu-FRG and Mu-FRG mice. We evaluated the CLbile and investigated the correlation of human CLbile with that of Hu-FRG and Mu-FRG mice. We found good correlations between humans and Hu-FRG mice in CLh,int (100% within threefold) and CLh ratio (R2 = 0.94). Moreover, we observed a much better relationship between humans and Hu-FRG mice in CLbile (75% within threefold). Our results suggest that OATP-mediated disposition and CLbile can be predicted using Hu-FRG mice, making them a useful in vivo drug discovery tool for quantitatively predicting human liver disposition. SIGNIFICANCE STATEMENT: OATP-mediated disposition and biliary clearance of drugs are likely quantitatively predictable using Hu-FRG mice. The findings can enable the selection of better drug candidates and the development of more effective strategies for managing OATP-mediated DDIs in clinical studies.

Developing an In Vitro to In Vivo Extrapolation (IVIVE) Model to Predict Human Milk-to-Plasma Drug Concentration Ratios

Determining the amount of drug transferred into human milk is critical for benefit-risk analysis of taking medication while breastfeeding. In this study, we developed an in vitro and in vivo extrapolation (IVIVE) model to predict human milk/plasma (M/P) drug concentration ratios. Drug unionized fractions at pH 7.0 (F_ni,7.0) and 7.4 (F_ni,7.4), drug fractions unbound in human plasma (f_up) and milk (f_um), and in vitro cell permeability in both directions (efflux ratio, ER) were incorporated into the IVIVE model. A multiple regression E_max model was chosen to predict f_um from f_up and polar surface area (PSA). A total of 97 drugs with experimental ER from Caco-2 cells were used to test the IVIVE model. The M/P ratios predicted by the IVIVE model had a 1.93-fold geometric mean fold error (GMFE) and 72% of predictions were within two-fold error (Pw2FE), which were superior to the performance of previously reported five models. The IVIVE model showed a reasonable prediction accuracy for passive diffusion drugs (GMFE = 1.71-fold, Pw2FE = 82%, N = 50), BCRP substrates (BCRP: GMFE = 1.91-fold, Pw2FE = 60%, N = 5), and substrates of P-gp and BCRP (GMFE = 1.74-fold, Pw2FE = 75%, N = 8) and a lower prediction performance for P-gp substrates (GMFE = 2.51-fold, Pw2FE = 55%, N = 22). By fitting the observed M/P ratios of 39 P-gp substrates, an optimized ER (1.61) was generated to predict the M/P ratio of P-gp substrates using the developed IVIVE model. Compared with currently available in vitro models, the developed IVIVE model provides a more accurate prediction of the drug M/P ratio, especially for passive diffusion drugs. The model performance is expected to be further improved when more experimental f_um and ER data are available.

Does Addition of Protein to Hepatocyte or Microsomal In Vitro Incubations Provide a Useful Improvement in In Vitro-In Vivo Extrapolation Predictability?

Accurate prediction of in vivo hepatic clearance is an essential part of successful and efficient drug development; however, many investigators have recognized that there are significant limitations in the predictability of clearance with a tendency for underprediction for primarily metabolized drugs. Here, we examine the impact of adding serum or albumin into hepatocyte and microsomal incubations on the predictability of in vivo hepatic clearance. The addition of protein into hepatocyte incubations has been reported to improve the predictability for high clearance (extraction ratio) drugs and highly protein-bound drugs. Analyzing published data for 60 different drugs and 97 experimental comparisons (with 17 drugs being investigated from two to seven) we confirmed the marked underprediction of clearance. However, we could not validate any relevant improved predictability within twofold by the addition of serum to hepatocyte incubations or albumin to microsomal incubations. This was the case when investigating all measurements, or when subdividing analyses by extraction ratio, degree of protein binding, Biopharmaceutics Drug Disposition Classification System class, examining Extended Clearance Classification System class 1B drugs only, or drug charge. Manipulating characteristics of small data sets of like compounds and adding scaling factors can appear to yield good predictability, but the carryover of these methods to alternate drug classes and different laboratories is not evident. Improvement in predictability of poorly soluble compounds is greater than that for soluble compounds, but not to a meaningful extent. Overall, we cannot confirm that protein addition improves in vitro-in vivo extrapolation predictability to any clinically meaningful degree when considering all drugs and different subsets. SIGNIFICANCE STATEMENT: The addition of protein into microsomal or hepatocyte incubations has been widely proposed to improve hepatic clearance predictions. To date, studies examining this phenomenon have not included appropriate negative controls where predictability is achieved without protein addition and have been conducted with small data sets of similar compounds that don't apply to alternate drug classes. Here, an extensive analysis of published data for 60 drugs and 97 experimental comparisons couldn't validate any relevant clinically improved clearance predictability with protein addition.

Prediction of Drug Clearance from Enzyme and Transporter Kinetics

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.

Prediction of Transporter-Mediated Rosuvastatin Hepatic Uptake Clearance and Drug Interaction in Humans Using Proteomics-Informed REF Approach

Suspended, plated, or sandwich-cultured human hepatocytes are routinely used for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated hepatic clearance (CL) of drugs. However, these hepatocyte models have been reported to underpredict transporter-mediated in vivo hepatic uptake CL (CL _{uptake,in vivo} ) of some drugs. Therefore, we determined whether transporter-expressing cells (TECs) can accurately predict the CL _{uptake,in vivo} of drugs. To do so, we determined the uptake CL (CL _{int,uptake,cells} ) of rosuvastatin (RSV) by TECs (organic anion transporting polypeptides/Na⁺-taurocholate cotransporting polypeptide) and then scaled it to that in vivo by relative expression factor (REF) (the ratio of transporter abundance in human livers and TEC) determined by liquid chromatography tandem mass spectrometry-based quantitative proteomics. Both the TEC and hepatocyte models did not meet our predefined success criteria of predicting within 2-fold the RSV CL _{uptake,in vivo} value obtained from our positron emission tomography (PET) imaging. However, the TEC performed better than the hepatocyte models. Interestingly, using REF, TECs successfully predicted RSV CL _{int,uptake,hep} obtained by the hepatocyte models, suggesting that the underprediction of RSV CL _{uptake,in vivo} by TECs and hepatocytes is due to endogenous factor(s) not present in these in vitro models. Therefore, we determined whether inclusion of plasma (or albumin) in TEC uptake studies improved IVIVE of RSV CL _{uptake,in vivo} It did, and our predictions were close to or just fell above our lower 2-fold acceptance boundary. Despite this success, additional studies are needed to improve transporter-mediated IVIVE of hepatic uptake CL of drugs. However, using REF and TEC, we successfully predicted the magnitude of PET-imaged inhibition of RSV CL _{uptake,in vivo} by cyclosporine A. SIGNIFICANCE STATEMENT: We showed that the in vivo transporter-mediated hepatic uptake CL of rosuvastatin, determined by PET imaging, can be predicted (within 2-fold) from in vitro studies in transporter-expressing cells (TECs) (scaled using REF), but only when plasma proteins were included in the in vitro studies. This conclusion did not hold when plasma proteins were absent in the TEC or human hepatocyte studies. Thus, additional studies are needed to improve in vitro to in vivo extrapolation of transporter-mediated drug CL.

Evaluation of Drug Biliary Excretion Using Sandwich-Cultured Human Hepatocytes

Evaluation of hepatobiliary transport of drugs is an important challenge, notably during the development of new molecular identities. In this context, sandwich-cultured human hepatocytes (SCHH) have been proposed as an interesting and integrated tool for predicting in vitro biliary excretion of drugs. The present review was therefore designed to summarize key findings about SCHH, including their establishment, their main functional features and their use for the determination of canalicular transport and the prediction of in vivo biliary clearance and hepatobiliary excretion-related drug-drug interactions. Reviewed data highlight the fact that SCHH represent an original and probably unique holistic in vitro approach to predict biliary clearance in humans, through taking into account sinusoidal drug uptake, passive drug diffusion, drug metabolism and sinusoidal and canalicular drug efflux. Limits and proposed refinements for SCHH-based analysis of drug biliary excretion, as well as putative human alternative in vitro models to SCHH are also discussed.

Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling

Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the prediction of human PKs prior to the first-in-human clinical trials. In vitro-in vivo extrapolation and allometric scaling are the choice of method for projection to human situations. Although these methods are useful tools for the estimation of PK parameters, it is a challenge to apply these methods since underlying biochemical, mathematical, physiological, and background knowledge of PKs are required. In addition, it is difficult to select an appropriate methodology depending on the data available. Therefore, this review covers the principles of PK parameters pertaining to the clearance, volume of distribution, elimination half-life, absorption rate constant, and prediction method from the original idea to recently developed models in order to introduce optimal models for the prediction of PK parameters.

The Importance of Incorporating OCT2 Plasma Membrane Expression and Membrane Potential in IVIVE of Metformin Renal Secretory Clearance

Transporter expression, determined by quantitative proteomics, together with PBPK models is a promising approach for in vitro-to-in vivo extrapolation (IVIVE) of transporter-mediated drug clearance. OCT2-expressing HEK293 and MDCKII cells were used to predict in vivo renal secretory clearance (CL_r,sec) of metformin. [¹⁴C]-Metformin uptake clearance in OCT2-expressing cells was determined and scaled to in vivo CL_r,sec by using OCT2 expression in the cells versus the human kidney cortex. Through quantitative targeted proteomics, the total expression of OCT2 in HEK293, MDCKII cells, and human kidney cortex was 369.4 ± 26.8, 19 ± 1.1, and 7.6 ± 3.8 pmol/mg cellular protein, respectively. The expression of OCT2 in the plasma membrane of HEK293 and MDCKII cells, measured using an optimized biotinylation method followed by quantitative proteomics, was 30.2% and 51.6%, respectively. After correcting for percent of OCT2 expressed in the plasma membrane and the resting membrane potential (millivolts) difference between the OCT2-expressing cells and the renal epithelial cells, the predicted CL_r,sec of metformin was 250.7 ml/min, a value within the range of the observed CL_r,sec of metformin. These data demonstrate the promise of using quantitative proteomics for IVIVE of transporter-mediated drug clearance and highlight the importance of quantifying plasma membrane expression of transporters and utilizing cells that mimic the in vivo mechanism(s) of transport of drugs.

Sandwich-Cultured Hepatocytes for Mechanistic Understanding of Hepatic Disposition of Parent Drugs and Metabolites by Transporter-Enzyme Interplay

Functional interplay between transporters and drug-metabolizing enzymes is currently one of the hottest topics in the field of drug metabolism and pharmacokinetics. Uptake transporter-enzyme interplay is important to determine intrinsic hepatic clearance based on the extended clearance concept. Enzyme and efflux transporter interplay, which includes both sinusoidal (basolateral) and canalicular efflux transporters, determines the fate of metabolites formed in the liver. As sandwich-cultured hepatocytes (SCHs) maintain metabolic activities and form a canalicular network, the whole interplay between uptake and efflux transporters and drug-metabolizing enzymes can be investigated simultaneously. In this article, we review the utility and applicability of SCHs for mechanistic understanding of hepatic disposition of both parent drugs and metabolites. In addition, the utility of SCHs for mimicking species-specific disposition of parent drugs and metabolites in vivo is described. We also review application of SCHs for clinically relevant prediction of drug-drug interactions caused by drugs and metabolites. The usefulness of mathematical modeling of hepatic disposition of parent drugs and metabolites in SCHs is described to allow a quantitative understanding of an event in vitro and to develop a more advanced model to predict in vivo disposition.

Successful Prediction of In Vivo Hepatobiliary Clearances and Hepatic Concentrations of Rosuvastatin Using Sandwich-Cultured Rat Hepatocytes, Transporter-Expressing Cell Lines, and Quantitative Proteomics

We determined whether in vivo transporter-mediated hepatobiliary clearance (CL) and hepatic concentrations of rosuvastatin (RSV) in the rat could be predicted by transport activity in sandwich-cultured rat hepatocytes (SCRHs) and/or transporter-expressing cell lines scaled by differences in transporter protein expression between SCRHs, cell lines, and rat liver. The predicted hepatobiliary CLs and hepatic concentrations of RSV were compared with our previously published positron emission tomography imaging data. Sinusoidal uptake CL ([Formula: see text]) and efflux (canalicular and sinusoidal) CLs of [³H]-RSV in SCRHs were evaluated in the presence and absence of Ca²⁺ and in the absence and presence of 1 mM unlabeled RSV (to estimate passive diffusion CL). [Formula: see text] of RSV into cells expressing organic anion transporting polypeptide (Oatp) 1a1, 1a4, and 1b2 was also determined. Protein expression of Oatps in SCRHs and Oatp-expressing cells was quantified by liquid chromatography tandem mass spectrometry. SCRHs well predicted the in vivo RSV sinusoidal and canalicular efflux CLs but significantly underestimated in vivo [Formula: see text]. Oatp expression in SCRHs was significantly lower than that in the rat liver. [Formula: see text], based on RSV [Formula: see text] into Oatp-expressing cells (active transport) plus passive diffusion CL in SCRHs, scaled by the difference in protein expression in Oatp cells versus SCRH versus rat liver, was within 2-fold of that observed in SCRHs or in vivo. In vivo hepatic RSV concentrations were well predicted by Oatp-expressing cells after correcting [Formula: see text] for Oatp protein expression. This is the first demonstration of the successful prediction of in vivo hepatobiliary CLs and hepatic concentrations of RSV using transporter-expressing cells and SCRHs.

Recent Progress in Hepatocyte Culture Models and Their Application to the Assessment of Drug Metabolism, Transport, and Toxicity in Drug Discovery: The Value of Tissue Engineering for the Successful Development of a Microphysiological System

Tissue engineering technology has provided many useful culture models. This article reviews the merits of this technology in a hepatocyte culture system and describes the applications of the sandwich-cultured hepatocyte model in drug discovery. In addition, we also review recent investigations of the utility of the 3-dimensional bioprinted human liver tissue model and spheroid model. Finally, we present the future direction and developmental challenges of a hepatocyte culture model for the successful establishment of a microphysiological system, represented as an organ-on-a-chip and even as a human-on-a-chip. A merit of advanced culture models is their potential use for detecting hepatotoxicity through repeated exposure to chemicals as they allow long-term culture while maintaining hepatocyte functionality. As a future direction, such advanced hepatocyte culture systems can be connected to other tissue models for evaluating tissue-to-tissue interaction beyond cell-to-cell interaction. This combination of culture models could represent parts of the human body in a microphysiological system.

Understanding the Interplay Between Uptake and Efflux Transporters Within In Vitro Systems in Defining Hepatocellular Drug Concentrations

One of the most holistic in vitro systems for prediction of intracellular drug concentrations is sandwich-cultured hepatocytes (SCH); however, a comprehensive evaluation of the utility of SCH to estimate uptake and biliary clearances and the need for additional kinetic parameters has yet to be carried out. Toward this end, we have selected 9 compounds (rosuvastatin, valsartan, fexofenadine, pravastatin, repaglinide, telmisartan, atorvastatin, saquinavir, and quinidine) to provide a range of physicochemical and hepatic disposition properties. Uptake clearances were determined in SCH and compared with conventional monolayer and suspension hepatocyte systems, previously reported by our laboratory. CL_uptake ranged from 1 to 41 μL/min/10⁶ cells in SCH which were significantly lower (1%-10%) compared with the other hepatocyte models. The hepatocyte-to-media unbound concentration ratio (Kp_u) has been assessed and ranged 0.7-59, lower compared with other hepatocyte systems (8-280). Estimates of in vitro biliary clearance (CL_bile) for 4 drugs were determined and were scaled to predict in vivo values using both intracellular concentration and media drug concentrations. These studies demonstrate that reduced uptake in rat SCH may limit drug access to canalicular efflux transport proteins and highlight the importance of elucidating the interplay between these proteins for accurate prediction of hepatic clearance.

Hepatobiliary Clearance Prediction: Species Scaling From Monkey, Dog, and Rat, and In Vitro-In Vivo Extrapolation of Sandwich-Cultured Human Hepatocytes Using 17 Drugs

Hepatobiliary elimination can be a major clearance pathway dictating the pharmacokinetics of drugs. Here, we first compared the dose eliminated in bile in preclinical species (monkey, dog, and rat) with that in human and further evaluated single-species scaling (SSS) to predict human hepatobiliary clearance. Six compounds dosed in bile duct-cannulated (BDC) monkeys showed biliary excretion comparable to human; and the SSS of hepatobiliary clearance with plasma fraction unbound correction yielded reasonable predictions (within 3-fold). Although dog SSS also showed reasonable predictions, rat overpredicted hepatobiliary clearance for 13 of 24 compounds. Second, we evaluated the translatability of in vitro sandwich-cultured human hepatocytes (SCHHs) to predict human hepatobiliary clearance for 17 drugs. For drugs with no significant active uptake in SCHH studies (i.e., with or without rifamycin SV), measured intrinsic biliary clearance was directly scalable with good predictability (absolute average fold error [AAFE] = 1.6). Drugs showing significant active uptake in SCHH, however, showed improved predictability when scaled based on extended clearance term (AAFE = 2.0), which incorporated sinusoidal uptake along with a global scaling factor for active uptake and the canalicular efflux clearance. In conclusion, SCHH is a useful tool to predict human hepatobiliary clearance, whereas BDC monkey model may provide further confidence in the prospective predictions.

Inhibition of P-Glycoprotein and Multidrug Resistance-Associated Protein 2 Regulates the Hepatobiliary Excretion and Plasma Exposure of Thienorphine and Its Glucuronide Conjugate

Thienorphine (TNP) is a novel partial opioid agonist that has completed phase II clinical evaluation as a promising drug candidate for the treatment of opioid dependence. Previous studies have shown that TNP and its glucuronide conjugate (TNP-G) undergo significant bile excretion. The purpose of this study was to investigate the roles of efflux transporters in regulating biliary excretion and plasma exposure of TNP and TNP-G. An ATPase assay suggested that TNP and TNP-G were substrates of P-gp and MRP2, respectively. The in vitro data from rat hepatocytes showed that bile excretion of TNP and TNP-G was regulated by the P-gp and MRP2 modulators. The accumulation of TNP and TNP-G in HepG2 cells significantly increased by the treatment of mdr1a or MRP2 siRNA for P-gp or MRP2 modulation. In intact rats, the bile excretion, and pharmacokinetic profiles of TNP and TNP-G were remarkably changed with tariquidar and probenecid pretreatment, respectively. Tariquidar increased the Cmax and AUC0-t and decreased MRT and T1/2 of TNP, whereas probenecid decreased the plasma exposure of TNP-G and increased its T1/2. Knockdown P-gp and MRP2 function using siRNA significantly increased the plasma exposure of TNP and TNP-G and reduced their mean retention time in mice. These results indicated the important roles of P-gp and MRP2 in hepatobiliary excretion and plasma exposure of TNP and TNP-G. Inhibition of the efflux transporters may affect the pharmacokinetics of TNP and result in a drug-drug interaction between TNP and the concomitant transporter inhibitor or inducer in clinic.