Hypothetical and experimental models of unbound fraction have been proposed to facilitate predicting the hepatic clearance (CLH) of drugs from values of intrinsic clearance for the unbound drug (CLint-in vitro-unbound) and the well-stirred model (WSM). The hypothetical model (fu-adjusted) is adjusting the unbound fractions determined in plasma in vitro to estimate the maximum unbound fractions at the hepatocytes if each drug-protein complex in plasma becomes fully dissociated at the membrane by any albumin (ALB)-facilitated hepatic uptake mechanism. The model of fu-adjusted is also adjusting the unbound fraction for a pH gradient effect across the membrane. Alternatively, the new experimental model (fu-dynamic) measures the unbound fractions resulting to the dynamic dissociation kinetics from proteins in the presence of plasma and a liver enzyme in an in vitro assay. The objective of this study was to conduct an in-depth analysis of previous CLH predictions made with these unbound fractions in a companion manuscript. Furthermore, a new dataset on transporter substrates was also included in this study. Finally, the physiological basis of fu-adjusted has been redefined to extend its applicability with more drugs. In this case, there are lower concentrations of binding proteins in liver versus plasma that could also explain the higher unbound fractions for that organ. The outcomes associated to additional analyses pointed out that fu-adjusted, again, generally provided the most accurate predictions of CLH because fu-dynamic has generated superior biases of underpredictions or overpredictions. For slowly metabolized drugs bound to ALB, fu-dynamic was definitively less accurate than fu-adjusted. For other drug properties, fu-dynamic fared better but it was still not generally more accurate than fu-adjusted. Furthermore, experimental values of fu-dynamic were sometimes incoherent. For example, drugs bound to alpha-acid glycoprotein (AGP) did not follow the principle of fu-dynamic (i.e., values of fu-dynamic did not correlate with values of CLint-in vitro-unbound) by contrast to those drugs bound to ALB. Therefore, the current experimental setting for fu-dynamic might be unsuitable in some circumstances. Overall, this study confirmed that calculated values of fu-adjusted were as accurate as experimental values of fu-dynamic and can even be more accurate. A guidance on which unbound fraction to use in the WSM is also provided.

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu-dynamic) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

Post-hepatectomy liver failure (PHLF) is the most common postoperative complication and the leading cause of death after hepatectomy. The albumin-bilirubin (ALBI) score and nutritional risk index (NRI) have been shown to assess end-stage liver disease and predict PHLF and patient survival. We hypothesized that the ALBI score and NRI interact in the prediction of PHLF.

To analyze the interaction between the ALBI score and NRI in PHLF in patients with hepatocellular carcinoma.

This retrospective study included 186 patients who underwent hepatectomy for hepatocellular carcinoma at the Affiliated Hospital of Youjiang Medical University for Nationalities between January 2020 and July 2023. Data on patient characteristics and laboratory indices were collected from their medical records. Univariate and multivariate logistic regression were performed to determine the interaction effect between the ALBI score and NRI in PHLF.

Of the 186 patients included in the study, PHLF occurred in 44 (23.66%). After adjusting for confounders, multivariate logistic regression identified ALBI grade 2/3 [odds ratio (OR) = 73.713, 95% confidence interval (CI): 9.175-592.199] and NRI > 97.5 (OR = 58.990, 95%CI: 7.337-474.297) as risk factors for PHLF. No multiplicative interaction was observed between the ALBI score and NRI (OR = 0.357, 95%CI: 0.022-5.889). However, the risk of PHLF in patients with ALBI grade 2/3 and NRI < 97.5 was 101 times greater than that in patients with ALBI grade 1 and NRI ≥ 97.5 (95%CI: 56.445-523.839), indicating a significant additive interaction between the ALBI score and NRI in PHLF.

Both the ALBI score and NRI were risk factors for PHLF, and there was an additive interaction between the ALBI score and NRI in PHLF.

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

The Extended Clearance Classification System (ECCS) was established to facilitate the timely anticipation of clearance rate determination according to the physicochemical characteristics of a given compound and in vitro passive membrane permeability. Unfortunately, distinguishing between renal and hepatic uptake clearance mechanisms using ECCS class 3B is not possible. We determined the effects of plasma protein binding (PPB) on major hepatic organic anion transporting polypeptide (OATP) and renal organic anion transporter (OAT) substrates. A modified ECCS could predict when renal or hepatic uptake mechanisms were the main clearance rate determinants (accounting for ≥ 70% of total clearance).

A dataset of 66 human OATP and 41 OAT substrates was analyzed to determine the effect of PPB. A total of 63 acidic and zwitterionic, and high-molecular-weight (MW > 400 Da) compounds, including 50 drugs in ECCS classes 1B and 3B, were reanalyzed considering their PPB.

Statistical analyses revealed that hepatic uptake transporter (OATP1B1 and OATP1B3) substrates possess a high PPB rate of ≥ 90%, whereas OAT1 and/or OAT3 substrates possess low PPB rates of < 90%. By analyzing the 63 drugs on the basis of their PPB, the active hepatic uptakes of acids and zwitterions were determined to be the main clearance mechanisms, with PPB ≥ 90%, whereas renally eliminated drugs exhibited limited PPB (< 90%).

Therefore, PPB is an effective parameter for defining clearance rate determination for acidic and zwitterionic drugs with high MWs. Using PPB as an additional parameter in ECCS, clearance mechanisms for class 1B and 3B compounds can be predicted, and OATP and OAT substrates may be readily distinguished.

Plasma proteins or human serum albumin (HSA) have been reported to increase the in vitro intrinsic uptake clearance (CLint,uptake) of drugs by hepatocytes or organic anion transporting polypeptide (OATP)-transfected cell lines. This so-called protein-mediated uptake effect (PMUE) is thought to be due to an interaction between the drug-protein complex and the cell membrane causing an increase in the unbound drug concentration at the cell surface, resulting in an increase in the apparent CLint,uptake of the drug. To determine if the PMUE on OATP-mediated drug uptake is an artifact or a real phenomenon, we determined the effect of 1%, 2%, and 5% HSA on OATP1B1-mediated [human embryonic kidney (HEK)293 transfected cells] and passive CLint,uptake (mock HEK293 cells) on a cocktail of five statins. In addition, we determined the non-specific binding (NSB) of the statin-HSA complex to the cells/labware. The increase in uptake of atorvastatin, fluvastatin, and rosuvastatin in the presence of HSA was completely explained by the extent of NSB of the statin-HSA complex, indicating that the PMUE for these statins is an artifact. In contrast, this was not the case for OATP1B1-mediated uptake of pitavastatin and passive uptake of cerivastatin, suggesting that the PMUE is a real phenomenon for these drugs. Additionally, the PMUE on OATP1B1-mediated uptake of pitavastatin was confirmed by a decrease in its unbound IC50 in the presence of 5% HSA versus Hank's balanced salt solution buffer (HBSS). These data question the utility of routinely including plasma proteins or HSA in uptake experiments and the previous findings on PMUE on OATP-mediated drug uptake. SIGNIFICANCE STATEMENT: Here we report, for the first time, that the protein-mediated uptake effect (PMUE) on organic anion transporting polypeptide (OATP)-transported drugs could be an artifact of the non-specific binding (NSB) of the drug-albumin complex to cells/labware. Future experiments on PMUE must take into consideration such NSB. In addition, mechanisms other than PMUE need to be explored to explain the underprediction of in vivo OATP-mediated hepatic drug clearance from in vitro uptake studies.

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.

Accurately predicting the pharmacokinetics of compounds that are transporter substrates has been notoriously challenging using traditional in vitro systems and physiologically based pharmacokinetic (PBPK) modeling. The objective of this study was to use PBPK modeling to understand the translational accuracy of data generated with human embryonic kidney 293 (HEK293) cells overexpressing the hepatic uptake transporters organic anion transporting polypeptide (OATP) 1B1/3 with and without plasma while accounting for transporter expression. Models of four OATP substrates, two with low protein binding (pravastatin and rosuvastatin) and two with high protein binding (repaglinide and pitavastatin) were explored, and the OATP in vitro data generated in plasma incubations were used for a plasma model, and in buffer incubations for a buffer model. The pharmacokinetic parameters and concentration-time profiles of pravastatin and rosuvastatin were similar and well predicted (within 2-fold of observed values) using the plasma and buffer models without needing an empirical scaling factor, whereas the dispositions of the highly protein bound repaglinide and pitavastatin were more accurately simulated with the plasma models than the buffer models. This work suggests that data from HEK293 overexpressing transporter cells corrected for transporter expression represent a valid approach to improve bottom-up PBPK modeling for highly protein bound OATP substrates with plasma incubations and low protein binding OATP substrates with or without plasma incubations. SIGNIFICANCE STATEMENT: This work demonstrates the bottom-up approach of using in vitro data directly without employing empirical scaling factors to predict the intravenous pharmacokinetic (PK) profiles reasonably well for four organic anion transporting polypeptide (OATP) substrates. Based on these results, using HEK293 overexpressing cells, examining the impact of plasma for highly bound compounds, and incorporating transporter quantitation for the lot in which the in vitro data were generated represents a valid approach to achieve more accurate prospective PK predictions for OATP substrates.

The accuracy in predicting in vivo hepatic clearance of drugs from in vitro data (often termed as in vitro-to-in vivo extrapolation, IVIVE) has improved in part by applying the extended-clearance concept that considers the interplay between hepatic metabolism and uptake/efflux processes. However, the IVIVE-based prediction performs poorly in predicting the hepatic uptake clearance of highly albumin-bound anionic drugs. Their hepatic uptake clearances tend to be much higher than expected based on the free-drug theory. Such observation can be attributable to a phenomenon called albumin-mediated hepatic uptake, for which various models have been thus far proposed. Our group has been applying a facilitated-dissociation model, which assumes the enhanced dissociation of the drug-albumin complex upon interaction with the cell surface. By considering the albumin-mediated hepatic uptake (using the facilitated-dissociation model or alternative kinetic models), a number of investigations demonstrated the improvement in the prediction accuracy for the hepatic clearance of highly protein-bound anionic drugs that are substrates for hepatic uptake transporters. This review summarizes the reported kinetic analyses of the albumin-mediated hepatic uptake of highly albumin-bound drugs concerning the IVIVE and the clinical and physiological relevance.

Characterizing the pharmacokinetic properties of drug candidates represents an essential task during drug development. In the past, liver microsomes and primary suspended hepatocytes have been extensively used for this purpose, but their relatively short stability limits the applicability of such in vitro systems for drug compounds with low metabolic turnover. In the present study, we used 3D primary human hepatocyte spheroids to predict the hepatic clearance of seven drugs with low to intermediate clearance in humans. Our results indicate that hepatocyte spheroids maintain their in vivo like phenotype during prolonged incubations allowing to monitor the depletion of parent drug for seven days. In contrast, attempts to increase the relative metabolic capacity by pooling hepatocyte spheroids resulted in an immediate fusion of the spheroids followed by hepatocellular de-differentiation processes, demonstrating limited applicability of the pooling approach for quantitative pharmacokinetic studies. The hepatic clearance values obtained from incubations with individual spheroids were in close correlation with the clinical reference data with six out of seven drug compounds being predicted within a three-fold deviation and average fold and absolute average fold errors of 0.57 and 1.74, respectively. In conclusion, the hepatocyte spheroid model enables accurate hepatic clearance predictions for slowly metabolized drug compounds and represents a valuable tool for determining the pharmacokinetic properties of new drug candidates as well as for mechanistic pharmacokinetic studies. Significance Statement Traditional in vitro systems often fail to predict the hepatic clearance of slowly metabolized drug compounds. The current study demonstrates the ability of primary human hepatocyte spheroids to provide accurate projections on the hepatic clearance of drug compounds with low and intermediate clearance.

The impact of desorption kinetics and permeation kinetics on in vitro-based predictions of in vivo hepatic blood clearances is investigated in the present study. Most commonly, possible limitations due to slow desorption of chemicals from albumin or slow permeation of chemicals through cellular membranes are not considered when in vivo clearances are predicted from in vitro biotransformation rate constants. To evaluate whether the most commonly used extrapolation models might thus overlook important kinetic limitations, we compare predictions of in vivo clearance that explicitly consider desorption and permeation kinetics with predictions of in vivo clearance that neglect these aspects. Our results show that strong limitations due to slow permeation kinetics are possible depending on the assumed permeability value. While permeability values estimated with a mechanistic approach are fast enough to avoid significant limitations, other experimentally derived permeability values lead to dramatically decreased in vivo clearance predictions. These latter values lead to unrealistically low in vivo biotransformation estimates. Furthermore, we also evaluated the implications of desorption kinetics using experimentally determined desorption rate constants. These evaluations show that slow desorption kinetics are unlikely to limit in vivo clearance.

The possible implications of slow binding kinetics on respiratory uptake, bioconcentration and exposure of chemicals were evaluated in the present study. Most physiological and chemical information needed for such an evaluation is already known from the literature or can be estimated. However, data for binding kinetics of chemicals in fish plasma have not been reported in the literature yet. In the first part of this study, we therefore experimentally investigated the plasma binding kinetics for ten chemicals, including pollutants like polycyclic aromatic hydrocarbons and a pesticide. The determined desorption rate constants were in the range of 0.4 s-1 to 0.1 s-1. In the second part of this study, we present a comparative modeling analysis of generic predictions with binding kinetics of different velocities. For doing so, a model that explicitly represents binding kinetics in blood was developed and applied for different hypothetical scenarios. The evaluation showed that slow sorption kinetics only limits respiratory uptake and thus influences the levels of bioaccumulation for extreme and, by that, rather unlikely parameter combinations (i.e. for strongly sorbing chemicals with very slow binding kinetics). It can therefore be assumed that limitations on respiratory uptake due to slow binding kinetics in blood are rather unlikely for most chemicals.

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug's human steady-state unbound brain interstitial fluid-to-plasma concentration ratio (K_p,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P-glycoprotein, P-gp). Due to lack of good in vitro human blood-brain barrier models, we and others have advocated the use of a proteomics-informed relative expressive factor (REF) approach to predict K_p,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P-gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N-desmethyl loperamide, and metoclopramide was determined in human P-gp-transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, K_p,uu,brain of the drug was predicted using REF (ER approach). Alternatively, in vitro passive and P-gp-mediated intrinsic clearances (CLs) of these drugs, estimated using a five-compartmental model, were extrapolated to in vivo using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted K_p,uu,brain of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N-desmethyl loperamide. Using the in vitro-to-in vivo extrapolated clearance approach, K_p,uu,brain was reasonably well predicted but not the brain unbound interstitial fluid drug concentration-time profile. Therefore, we propose that the ER approach be used to predict K_p,uu,brain of CNS candidate drugs to enhance their success in development.

The in vitro-to-in vivo extrapolation (IVIVE) methods for predicting the hepatic clearance (CL) of drugs based on microsomal or hepatocyte data have certainly advanced; however, there is still place for improving the extrapolations from in vitro assays containing no plasma proteins. Accordingly, there is a discussion on whether the free drug hypothesis or an albumin (ALB)-mediated hepatic uptake phenomenon is the best scaling method. Therefore, the objectives of this study were to guide the prediction of CL and to diagnose which scaling method between the free drug hypothesis and ALB-mediated uptake could be more accurate; this, irrespective of the mechanism(s) governing CL if the drugs can get to the hepatocyte membrane. The analysis of several datasets demonstrated that almost all values of CL in vivo fall within the two calculated values of CL use as boundaries from: 1) the free drug hypothesis, and 2) ALB-mediated uptake. The average value from these two CL boundaries predicted the CL in vivo with an incredible accuracy. Validating these boundaries in preclinical species prior going to human as well as considering the fractional binding in plasma increased the accuracy. Overall, this study is another step towards guiding the CL prediction in drug discovery and development.

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

It is generally presumed that uptake transport mechanisms are of limited significance in hepatic clearance for lipophilic or high passive-permeability drugs. In this study, we evaluated the mechanistic role of the hepato-selective organic anion-transporting polypeptides (OATPs) 1B1/1B3 in the pharmacokinetics of compounds representing large lipophilic acid space. Intravenous pharmacokinetics of 16 compounds with molecular mass ∼400-730 Da, logP ∼3.5-8, and acid pKa <6 were obtained in cynomolgus monkey after dosing without and with a single-dose rifampicin-OATP1B1/1B3 probe inhibitor. Rifampicin (30 mg/kg oral) significantly (P < 0.05) reduced monkey clearance and/or steady-state volume of distribution (VDss) for 15 of 16 acids evaluated. Additionally, clearance of danoprevir was reduced by about 35%, although statistical significance was not reached. A significant linear relationship was noted between the clearance ratio (i.e., ratio of control to treatment groups) and VDss ratio, suggesting hepatic uptake contributes to the systemic clearance and distribution simultaneously. In vitro transport studies using primary monkey and human hepatocytes showed uptake inhibition by rifampicin (100 µM) for compounds with logP ≤6.5 but not for the very lipophilic acids (logP > 6.5), which generally showed high nonspecific binding in hepatocyte incubations. In vitro uptake clearance and fraction transported by OATP1B1/1B3 (ft,OATP1B) were found to be similar in monkey and human hepatocytes. Finally, for compounds with logP ≤6.5, good agreement was noted between in vitro ft,OATP1B and clearance ratio (as well as VDss ratio) in cynomolgus monkey. In conclusion, this study provides mechanistic evidence for the pivotal role of OATP1B-mediated hepatic uptake in the pharmacokinetics across a wide, large lipophilic acid space. SIGNIFICANCE STATEMENT: This study provides mechanistic insight into the pharmacokinetics of a broad range of large lipophilic acids. Organic anion-transporting polypeptides 1B1/1B3-mediated hepatic uptake is of key importance in the pharmacokinetics and drug-drug interactions of almost all drugs and new molecular entities in this space. Diligent in vitro and in vivo transport characterization is needed to avoid the false negatives often noted because of general limitations in the in vitro assays while handling compounds with such physicochemical attributes.

Current challenges with the in vitro-in vivo extrapolation (IVIVE) of hepatic uptake clearance involving organic anion-transporting polypeptide (OATP) 1B1/1B3 hinder drug design strategies. Here we evaluated the effect of 100% human plasma on the uptake clearance using transfected human embryonic kidney (HEK) 293 cells and primary human hepatocytes and assessed IVIVE. Apparent unbound uptake clearance (PSinf,u) increased significantly (P < 0.05) in the presence of plasma (vs. buffer incubations) for about 50% of compounds in both OATP1B1-transfected and wild-type HEK cells. Thus, plasma showed a minimal effect on the uptake ratios. With cultured human hepatocytes, plasma significantly (P < 0.05) increased PSinf,u for 11 of 19 OATP1B substrates (median change of 2.1-fold). Cell accumulation in HEK cells and hepatocytes was also increased for tolbutamide, which is not an OATP substrate. Plasma-to-buffer ratio of PSinf,u obtained in hepatocytes showed a good correlation with unbound fraction in plasma, and the relationship was best described by a "facilitated-dissociation" model. IVIVE was evaluated for the 19 OATP1B substrates using hepatocyte data in the presence of buffer and plasma. PSinf,u from buffer incubations markedly underpredicted hepatic intrinsic clearance (calculated via well stirred and parallel tube models) with an estimated bias of 0.10-0.13. Predictions improved when using PSinf,u from plasma incubations; however, considerable systemic underprediction was still apparent (0.19-0.26 bias). Plasma data with a global scaling factor of 3.8-5.3 showed good prediction accuracy (95% predictions within 3-fold; average fold error = 1.7, bias = 1). In summary, this study offers insight into the effect of plasma on the uptake clearance and its scope in improving IVIVE. SIGNIFICANCE STATEMENT: Our study using diverse anionic compounds shows that human plasma facilitates organic anion-transporting polypeptide 1B-mediated as well as passive uptake clearance, particularly for the highly bound compounds. Leveraging data from transfected human embryonic kidney 293 cells and primary human hepatocytes, we further evaluated mechanisms involved in the observed plasma-facilitated uptake transport. Enhanced hepatic uptake rate in the presence of plasma could be of relevance, as such mechanisms likely prevail in vivo and emphasize the need to maintain physiologically relevant assay conditions to achieve improved translation of transport data.

Bteich and coworkers recently demonstrated in a companion manuscript (J Pharm Sci 109: https://doi.org/10.1016/j.xphs.2020.07.003) that a protein-mediated hepatic uptake have occurred in an isolated perfused rat liver (IPRL) model for two drugs (Perampanel; PER and Fluoxetine; FLU) that bind extensively to the albumin (ALB) and alpha-1-acid glycoprotein (AGP). However, to our knowledge, there is no quantitative model available to predict the impact of a plasma protein-mediated hepatic uptake on the extent of hepatic clearance (CLh) for a drug binding extensively to these two proteins. Therefore, the main objective was to predict the corresponding CLh, which is an extension of the companion manuscript. The method consisted of extrapolating the intrinsic clearance from the unbound fraction measured in the perfusate or the unbound fraction extrapolated to the surface of the hepatocyte membrane by adapting an existing model of protein-mediated hepatic uptake (i.e., the fu_p-adjusted model) to include a binding ratio between the ALB and AGP. This new approach showed a relevant improvement compared to the free drug hypothesis particularly for FLU that showed the highest degree of ALB-mediated uptake. Overall, this study is a first step towards the development of predictive methods of CLh by considering the binding to ALB and AGP.

Predicting transporter-mediated in vivo hepatic drug clearance (CL) from in vitro data (IVIVE) is important in drug development to estimate first-in-human dose and the impact of drug interactions and pharmacogenetics on hepatic drug CL. For IVIVE, one can use human hepatocytes and the traditional milligrams of protein content per gram of liver tissue (MGPGL) approach. However, this approach has been found to consistently underpredict the observed in vivo hepatic drug CL. Therefore, we hypothesized that using transporter-expressing cells and the relative expression factor (REF), determined using targeted quantitative proteomics, will accurately predict in vivo hepatic CL of drugs. We have successfully tested this hypothesis in rats with rosuvastatin, which is transported by hepatic Organic anion transporting polypeptides (OATPs). Here, we tested this hypothesis for another drug and another transporter; namely, organic cation transporter (OCT)1-mediated hepatic distributional CL of metformin. First, we estimated the in vivo metformin hepatic sinusoidal uptake CL (CLh,s,in) of metformin by reanalysis of previously published human positron emission tomography imaging data. Next, using the REF approach, we predicted the in vivo metformin CLh,s,in using OCT1-transporter-expressing HEK293 cells or plated human hepatocytes. Finally, we compared this REF-based prediction with that using the MGPGL approach. The REF approach accurately predicted the in vivo metformin hepatic CLh,s,in, whereas the MGPGL approach considerably underpredicted the in vivo metformin CLh,s,in Based on these and previously published data, the REF approach appears to be superior to the MGPGL approach for a diverse set of drugs transported by different transporters. SIGNIFICANCE STATEMENT: This study is the first to use organic cation transporter 1-expressing cells and plated hepatocytes to compare proteomics-informed REF approach with the traditional MGPGL approach to predict hepatic uptake CL of metformin in humans. The proteomics-informed REF approach, which corrected for plasma membrane abundance, accurately predicted the positron emission tomography-imaged metformin hepatic uptake CL, whereas the MGPGL approach consistently underpredicted this CL.

Pemafibrate (PMF) is highly albumin-bound (>99.8%) and a substrate for hepatic uptake transporters (OATP1B) and CYP enzymes. Here, we developed a PBPK model of PMF to capture drug-drug interactions (DDI) incurred by cyclosporine (CsA) and rifampicin (RIF), the two OATP1B inhibitors. Initial PBPK modeling of PMF utilized in vitro hepatic uptake clearance (PS_inf) obtained in the absence of albumin, but failed in capturing the blood PMF pharmacokinetic (PK) profiles. Based on the results that in vitro PS_inf of unbound PMF was enhanced in the presence of albumin, we applied the albumin-facilitated dissociation model and the resulting PS_inf parameters improved the prediction of the blood PMF PK profiles. In refining our PBPK model toward improved prediction of the observed DDI data (PMF co-administered with single dosing of CsA or RIF; PMF following multiple RIF dosing), we adjusted the previously obtained in vivo OATP1B inhibition constants (K_i,OATP1B) of CsA or RIF for pitavastatin by correcting for substrate-dependency. We also incorporated the induction of OATP1B and CYP enzymes after multiple RIF dosing. Sensitivity analysis informed that the higher gastrointestinal absorption rate constant could further improve capturing the observed DDI data, suggesting the possible inhibition of intestinal ABC transporter(s) by CsA or RIF.

Uptake transporter organic anion transporting polypeptides (OATPs), efflux transporters (P-gp, BCRP and MRP2) and cytochrome P450 enzymes (CYP450s) are widely expressed in the liver, intestine or kidney. They coordinately work to control drug disposition, termed as "interplay of transporters and enzymes". Cyclosporine A (CsA) is an inhibitor of OATPs, P-gp, MRP2, BCRP and CYP3As. Drug-drug interaction (DDI) of CsA with victim drugs occurs via disordering interplay of transporters and enzymes. We aimed to establish a whole-body physiologically-based pharmacokinetic (PBPK) model which predicts disposition of CsA and nine victim drugs including atorvastatin, cerivastatin, pravastatin, rosuvastatin, fluvastatin, simvastatin, lovastatin, repaglinide and bosentan, as well as drug-drug interactions (DDIs) of CsA with nine victim drugs to investigate the integrated effect of enzymes and transporters in liver, intestinal and kidney on drug disposition. Predictions were compared with observations. Most of the predictions were within 0.5-2.0 folds of observations. Atorvastatin was represented to investigate individual contributions of transporters and CYP3As to atorvastatin disposition and their integrated effect. The contributions to atorvastatin disposition were hepatic OATPs >> hepatic CYP3A > intestinal CYP3As ≈ efflux transporters (P-gp/BCRP/MRP2). The results got the conclusion that the developed PBPK model characterizing the interplay of enzymes and transporters was successfully applied to predict the pharmacokinetics of 10 OATP substrates and DDIs of CsA with 9 victim drugs.

The pharmacokinetics of a drug is dependent upon the coordinate work of influx transporters, enzymes and efflux transporters (i.e., transporter-enzyme interplay). The transporter-enzyme interplay may occur in liver, kidney and intestine. The influx transporters involving drug transport are organic anion transporting polypeptides (OATPs), peptide transporters (PepTs), organic anion transporters (OATs), monocarboxylate transporters (MCTs) and organic cation transporters (OCTs). The efflux transporters are P-glycoprotein (P-gp), multidrug/toxin extrusions (MATEs), multidrug resistance-associated proteins (MRPs) and breast cancer resistance protein (BCRP). The enzymes related to drug metabolism are mainly cytochrome P450 enzymes (CYP450s) and UDP-glucuronosyltransferases (UGTs). Accumulating evidence has demonstrated that diabetes alters the expression and functions of CYP450s and transporters in a different manner, disordering the transporter-enzyme interplay, in turn affecting the pharmacokinetics of some drugs. We aimed to focus on (1) the imbalance of transporter-CYP450 interplay in the liver, intestine and kidney due to altered expressions of influx transporters (OATPs, OCTs, OATs, PepTs and MCT6), efflux transporters (P-gp, BCRP and MRP2) and CYP450s (CYP3As, CYP1A2, CYP2E1 and CYP2Cs) under diabetic status; (2) the net contributions of these alterations in the expression and functions of transporters and CYP450s to drug disposition, therapeutic efficacy and drug toxicity; (3) application of a physiologically-based pharmacokinetic model in transporter-enzyme interplay.

Generating accurate in vitro data is crucial for in vitro to in vivo extrapolation and pharmacokinetic predictions. The use of human embryonic kidney (HEK) 293 cells overexpressing organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 in protein-free buffer and 100% human plasma incubations was explored for the uptake of four OATP substrates: pravastatin, rosuvastatin, repaglinide, and pitavastatin. Differences were observed for each parameter [unbound Michaelis constant (K m,u), V max, intrinsic clearance (CLint), and unbound passive diffusion Pdif,u] obtained from the buffer and plasma incubations in both cells, and the fold differences were greatest for the highly protein bound compounds. The fold change in K m,u values ranged from 1.91 to 619, and the fold change in V max values ranged from 1.22 to 97.4. As a result, in both cells, the CLint values generated in the plasma incubations were higher by 0.762- to 31.7-fold than the values generated in the protein-free buffer. The passive diffusion was also higher in the plasma incubations for all four compounds, with a fold difference range of 1.73-23.4. These shifts in the presence and absence of human plasma suggest that plasma proteins may play a role in both the active uptake and passive diffusion processes. The results also support the idea of a transporter-induced protein-binding shift, where high protein binding may not limit the uptake of compounds that have high affinity for transporters. The addition of plasma to incubations leading to higher CLint values for transporter substrates helps mitigate the underprediction commonly noted with in vitro to in vivo extrapolation. SIGNIFICANCE STATEMENT: The current investigation brings a new perspective on how to mitigate the underprediction commonly noted with in vitro to in vivo extrapolation for OATP substrates by using HEK293 cells overexpressing OATP1B1 and OATP1B3. It also supports the idea of a transporter-induced protein-binding shift, where high protein binding may not limit the uptake of compounds that have high affinity for transporters.

This study re-examined the hepatic extraction for diazepam, the only drug for which isolated perfused rat liver (IPRL) studies have been reported not to be consistent with the well stirred model of organ elimination when only entering and exiting liver concentration measurements are available. First, the time dependency of diazepam equilibrium fraction unbound measurements from 4 to 24 hours was tested, reporting the continuing increases with time. The results showed that the time dependency of equilibrium protein-binding measurements for very highly bound drugs may be an issue that is not readily overcome. When examining C out/C in (F obs) measurements for diazepam when no protein is added to the incubation media, IPRL outcomes were consistent with previous reports showing marked underpredictability of in vivo clearance from in vitro measures of elimination in the absence of protein for very highly bound drugs, which is markedly diminished in the presence of albumin. F obs for diazepam at additional low concentrations of protein that would allow discrimination of the models of hepatic elimination produced results that were not consistent with the dispersion and parallel-tube models. Therefore, although the outcomes of this study were similar to those reported by Rowland and co-workers, when no protein is added to the perfusion media, these IPRL results for diazepam cannot be reasonably interpreted as proving that hepatic organ elimination is model-independent or as supporting the dispersion and parallel-tube models of organ elimination. SIGNIFICANCE STATEMENT: The only drug experiments for which isolated perfusion rat liver studies do not support hepatic clearance being best described by the well stirred model have been carried out with diazepam at zero protein concentration. This study repeated those studies, confirming the previous results at zero protein concentration, but the addition of low protein-binding conditions capable of differentiating the various models of hepatic elimination are more consistent with the well stirred model of hepatic elimination. These experimental studies do not support the preference for alternate models of hepatic elimination or the proposal that hepatic organ clearance is model-independent.