Prediction Of Hepatic Clearance Research Articles

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics

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.

Dynamic free fraction: concept, methodology and impact on hepatic clearance prediction using the well-stirred model

Dynamic free fraction: concept, methodology and impact on hepatic clearance prediction using the well-stirred model

Exploring the boundaries for in vitro-in vivo extrapolation: Use of isolated hepatocytes in co-culture and impact of albumin binding properties in the prediction of clearance of various drug types.

Prediction of hepatic clearance of drugs (via uptake or metabolism) from in vitro systems continues to be problematic. This is particularly the case when plasma protein binding is high. The following work explores simultaneous assessment of both clearance processes, focusing on a commercial hepatocyte-fibroblast co-culture system (HµREL), over a 24 hour period, using a series of six probe drugs (ranging in metabolic and transporter clearance and low-to-high plasma protein binding). A rat hepatocyte co-culture prototype assay was established using drug depletion (measuring both medium and total concentrations) and cell uptake kinetic analysis, both in the presence (1 and 4%) and absence of plasma protein (BSA). Secretion of endogenous albumin was monitored as a marker of viability and this reached 0.004% in incubations (at a rate similar to in vivo synthesis). Binding to stromal cells was significant and required appropriate correction factors. Drug concentration-time courses were analysed both by conventional methods and a mechanistic cell model, prior to in vivo extrapolation. CL assayed by drug depletion in conventional suspended rat hepatocytes provided a benchmark to evaluate co-culture value. Addition of albumin appeared to improve predictions for some compounds (where fu<0.1); however, for high binding drugs, albumin significantly limited quantification and thus predictions. Overall, these results indicate the prospect of reliable measurement of hepatically cleared compounds, including (of novelty) those with low metabolic turnover but high active uptake, through the longevity of co-culture systems combined with judicious sampling. Significance Statement Co-culture systems, combining hepatocytes with stromal cells, offer a more advanced tool than standard hepatocytes, with the ability to be cultured for longer periods of time, yet their potential has not been comprehensively assessed. We evaluate the strengths and limitations of the HµREL system via the use of six drugs representing various metabolic and transporter-mediated clearance pathways with various degrees of albumin binding. Studies in the presence and absence of albumin allow IVIVE and a framework to maximise their utility.

A 20-Year Research Overview: Quantitative Prediction of Hepatic Clearance Using the In Vitro-In Vivo Extrapolation Approach Based on Physiologically Based Pharmacokinetic Modeling and Extended Clearance Concept.

Understanding the extended clearance concept and establishing a physiologically based pharmacokinetic (PBPK) model are crucial for investigating the impact of changes in transporter and metabolizing enzyme abundance/functions on drug pharmacokinetics in blood and tissues. This mini-review provides an overview of the extended clearance concept and a PBPK model that includes transporter-mediated uptake processes in the liver. In general, complete in vitro and in vivo extrapolation (IVIVE) poses challenges due to missing factors that bridge the gap between in vitro and in vivo systems. By considering key in vitro parameters, we can capture in vivo pharmacokinetics, a strategy known as the top-down or middle-out approach. We present the latest progress, theory, and practice of the Cluster Gauss-Newton method, which is used for middle-out analyses. As examples of poor IVIVE, we discuss "albumin-mediated hepatic uptake" and "time-dependent inhibition" of OATP1Bs. The hepatic uptake of highly plasma-bound drugs is more efficient than what can be accounted for by their unbound concentration alone. This phenomenon is referred to as "albumin-mediated" hepatic uptake. IVIVE was improved by measuring hepatic uptake clearance in vitro in the presence of physiologic albumin concentrations. Lastly, we demonstrate the application of Cluster Gauss-Newton method-based analysis to the target-mediated drug disposition of bosentan. Incorporating saturable target binding and OATP1B-mediated hepatic uptake into the PBPK model enables the consideration of nonlinear kinetics across a wide dose range and the prediction of receptor occupancy over time. SIGNIFICANCE STATEMENT: There have been multiple instances where researchers' endeavors to unravel the underlying mechanism of poor in vitro-in vivo extrapolation have led to the discovery of previously undisclosed truths. These include 1) albumin-mediated hepatic uptake, 2) the target-mediated drug disposition in small molecules, and 3) the existence of a trans-inhibition mechanism by inhibitors for OATP1B-mediated hepatic uptake of drugs. Consequently, poor in vitro-in vivo extrapolation and the subsequent inquisitiveness of scientists may serve as a pivotal gateway to uncover hidden mechanisms.

Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance.

Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05–1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan.

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.

Primary human hepatocyte spheroids as an in vitro tool for investigating drug compounds with low clearance.

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.

A New Guidance for the Prediction of Hepatic Clearance in the Early Drug Discovery and Development from the in Vitro-to-in Vivo Extrapolation Method and an Approach for Exploring Whether an Albumin-Mediated Hepatic Uptake Phenomenon Could be Present Under in Vivo Conditions.

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.

Relevance of desorption kinetics and permeability for in vitro-based predictions of hepatic clearance in fish.

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.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

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.

Metabolic Retroversion of Piperaquine (PQ) via Hepatic Cytochrome P450-Mediated N-Oxidation and Reduction: Not an Important Contributor to the Prolonged Elimination of PQ.

As a partner antimalarial with an extremely long elimination half-life (∼30 days), piperaquine (PQ) is mainly metabolized into a pharmacologically active N-oxide metabolite [piperaquine N-oxide (PN1)] in humans. In the present work, the metabolic retroversion of PQ and PN1, potentially associated with decreased clearance of PQ, was studied. The results showed that interconversion existed for PQ and its metabolite PN1. The N-oxidation of PQ to PN1 was mainly mediated by CYP3A4, and PN1 can rapidly reduce back to PQ via cytochrome P450 (P450)/flavin-containing monooxygenase enzymes. In accordance with these findings, the P450 nonselective inhibitor (1-ABT) or CYP3A4 inhibitor (ketoconazole) inhibited the N-oxidation pathway in liver microsomes (>90%), and the reduction metabolism was inhibited by 1-ABT (>90%) or methimazole (∼50%). Based on in vitro physiologic and enzyme kinetic studies, quantitative prediction of hepatic clearance (CLH) of PQ was performed, which indicated its negligible decreased elimination in humans in the presence of futile cycling, with the unbound CLH decreasing by 2.5% (0.069 l/h per kilogram); however, a minor decrease in unbound CLH (by 12.8%) was found in mice (0.024 l/h per kilogram). After an oral dose of PQ (or PN1) to mice, the parent form predominated in the blood circulation, and PN1 (or PQ) was detected as a major metabolite. Other factors probably associated with delayed elimination of PQ (intestinal metabolism and enterohepatic circulation) did not play a key role in PQ elimination. These data suggested that the metabolic interconversion of PQ and its N-oxide metabolite contributes to but may not significantly prolong its duration in humans. SIGNIFICANCE STATEMENT: This paper investigated the interconversion metabolism of piperaquine (PQ) and its N-oxide metabolite in vitro as well as in mice. The metabolic profiles of PQ were reestablished by this futile cycling, which contributes to but may not significantly prolong its elimination in humans. Enzyme phenotyping indicated a low possibility of interaction of PQ during artemisinin drug-based combination therapy treatment.

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation.

Plasma protein-mediated uptake (PMU) and its effect on clearance (CL) prediction have been studied in various formats; however, a comprehensive analysis of the overall impact of PMU on CL parameters from hepatocyte assays (routinely used for IVIVE) has not previously been performed. The following work collated data reflecting the effect of PMU for 26 compounds with a wide variety of physicochemical, drug, and in vivo CL properties. PMU enhanced the unbound intrinsic clearance in vitro (CLint,u in vitro) beyond that conventionally calculated using fraction unbound and was correlated with the unbound fraction of drug in vitro and in plasma (fup) and absolute unbound intrinsic clearance in vivo (CLint,u in vivo) in both rat and human hepatocytes. PMU appeared to be more important for highly bound (fup < 0.1) and high CLint,u in vivo drugs. These trends were independent of species, assay conditions, ionization, and extended clearance classification system group, although the type of plasma protein used in in vitro assays may require further investigation. Such generalized trends (spanning fup 0.0008-0.99) may suggest a generic mechanism behind PMU; however, multiple drug-dependent mechanisms are also possible. Using the identified relationship between the impact of PMU on CLint,u in vitro and fup, PMU-enhanced predictions of CLint,u in vivo were calculated for both transporter substrates and metabolically cleared drugs. PMU was accurately predicted, and incorporation of predicted PMU improved the IVIVE of hepatic CL, with an average fold error of 1.17 and >50% of compounds predicted within a 2-fold error for both rat and human data sets (n ≥ 100). SIGNIFICANCE STATEMENT: Current strategies for prediction of hepatic clearance from in vitro data are recognized to be inaccurate, but they do not account for PMU. The impact of PMU on CLint,u in vitro is wide ranging and can be predicted based on fraction unbound in plasma and applied to CLint,u in vitro values obtained by standard procedures in the absence of plasma protein. Such PMU-enhanced predictions improved IVIVE, and future studies may easily incorporate this PMU relationship to provide more accurate IVIVE.

Comparative Assessment of Extrapolation Methods Based on the Conventional Free Drug Hypothesis and Plasma Protein-Mediated Hepatic Uptake Theory for the Hepatic Clearance Predictions of Two Drugs Extensively Bound to Both the Albumin And Alpha-1-Acid Glycoprotein.

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 fup-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.

In Vitro to In Vivo Extrapolation of Metabolic Clearance for UGT Substrates Using Short-Term Suspension and Long-Term Co-cultured Human Hepatocytes.

The use of micro-patterned co-cultured hepatocytes for human hepatic clearance predictions has previously been demonstrated using drugs metabolized by cytochrome P450 enzymes. The present study evaluates the in vitro to in vivo extrapolation (IVIVE) performance for UDP-glucuronosyltransferase (UGT) substrates. In vitro intrinsic clearances for 13 drugs mainly cleared by UGTs were determined using HepatoPac and suspended hepatocytes. The in vivo intrinsic clearance was predicted from in vitro intrinsic clearance and compared with weighted mean in vivo intrinsic clearance estimated from several clinical studies. A conventional scaling methodology accounting for protein binding in plasma and incubation medium was used for the IVIVE assuming that only free drug is accessible at the site of metabolism. The in vivo hepatic intrinsic clearance was predicted within threefold error for six and nine out of thirteen drugs using suspended hepatocytes and HepatoPac, respectively. A reduced under-estimation of hepatic intrinsic clearance was observed in the average fold error (AFE) in HepatoPac (AFE, 0.69) compared with the suspended hepatocytes (AFE, 0.37). The current study shows reasonable performance of hepatic clearance prediction of drugs mainly metabolized by UGT enzymes using HepatoPac with a similar under-prediction bias as obtained in the reported IVIVEs for cytochrome P450 substrates. This study provides a validation of the approach for drugs cleared via UGT conjugation mechanisms and discusses potential causes for outlier behavior considering pharmacokinetic or physicochemical properties.

P232 - Prediction of hepatic clearance and partitioning in rat for improved BSEP inhibition risk assessment in humans

P232 - Prediction of hepatic clearance and partitioning in rat for improved BSEP inhibition risk assessment in humans

P161 - Quantitative metabolic profiling of slowly cleared chemicals in in vitro models including 3D liver spheroid and hepatopac and hepatic clearance predictions from in vitro data using gastroplus PBPK modelling following topical application

P161 - Quantitative metabolic profiling of slowly cleared chemicals in in vitro models including 3D liver spheroid and hepatopac and hepatic clearance predictions from in vitro data using gastroplus PBPK modelling following topical application

P126 - Observed vs. predicted effects of protein binding: Improving in vivo predictions of hepatic clearance, intracellular concentration and IC50 values

P126 - Observed vs. predicted effects of protein binding: Improving in vivo predictions of hepatic clearance, intracellular concentration and IC50 values

Prediction of Hepatic Clearance of Stereoselective Metabolism of Carvedilol in Liver Microsomes and Hepatocytes of Sprague-Dawley and Cytochrome P450 2D-Deficient Dark Agouti Rats

Hepatic clearance (CLh) of carvedilol (CAR), which is eliminated via stereoselective metabolism by the CYP2D subfamily of cytochromes P450 (CYPs), was predicted using liver microsomes and hepatocytes from Sprague-Dawley (SD) rats and CYP2D-deficient Dark Agouti (DA) rats to determine the usefulness of prediction method. Plasma concentrations of CAR following intravenous injection to DA rats were higher than those in SD rats. The volume of distribution at steady state and total clearance (CLtot) of S-CAR were approximately two times greater than those of R-CAR in both strains. CLh predicted from in vitro studies using DA rat liver microsomes was different from that obtained from in vivo studies. In contrast, in vitro CLh prediction using DA rat hepatocytes was nearly identical to the CLh observed in DA rats in vivo, and was lower than that in SD rats. The predicted CLh in vitro using hepatocytes correlated well with the observed CLtot in vivo, which is expected to be nearly the same as CLh. These results suggest that in vitro metabolic studies using hepatocytes are more relevant with regard to stereoselectively predicting CLh of CAR than those using liver microsomes.

PBPK and its Virtual Populations: the Impact of Physiology on Pediatric Pharmacokinetic Predictions of Tramadol.

In pediatric PBPK models, age-related changes in the body are known to occur. Given the sparsity of and the variability associated with relevant physiological parameters, different PBPK software providers may vary in their system's data. In this work, three commercially available PBPK software packages (PK-Sim®, Simcyp®, and Gastroplus®) were investigated regarding their differences in system-related information, possibly affecting clearance prediction. Three retrograde PBPK clearance models were set up to enable prediction of pediatric tramadol clearance. These models were qualified in terms of total, CYP2D6, and renal clearance in adults. Tramadol pediatric clearance predictions from PBPK were compared with a pooled popPK model covering clearance ranging from neonates to adults. Fold prediction errors were used to evaluate the results. Marked differences in liver clearance prediction between PBPK models were observed. In general, the prediction bias of total clearance was greatest at the youngest population and decreased with age. Regarding CYP2D6 and renal clearance, important differences exist between PBPK software tools. Interestingly, the PBPK model with the shortest CYP2D6 maturation half-life (PK-Sim) agreed best with the in vivo CYP2D6 maturation model. Marked differences in physiological data explain the observed differences in hepatic clearance prediction in early life between the various PBPK software providers tested. Consensus on the most suited pediatric data to use should harmonize and optimize pediatric clearance predictions. Moreover, the combination of bottom-up and top-down approaches, using a convenient probe substrate, has the potential to update system-related parameters in order to better represent pediatric physiology.

Supplemental Analysis of the Prediction of Hepatic Clearance of Binary Mixtures of Bisphenol A and Naproxen Determined in an Isolated Perfused Rat Liver Model to Promote the Understanding of Potential Albumin-Facilitated Hepatic Uptake Mechanism

The hepatic clearance (CL) of bisphenol A (BPA) in the isolated perfused rat liver (IPRL) model has been studied for the impact of albumin (ALB) binding and coadministration with naproxen (NAP) in a companion manuscript (Bounakta et al. Xenobiotica. 2017;3:1-13.). We reported that the extrapolations of hepatic CL of BPA, NAP, and the binary mixtures between 2 ALB concentrations did not follow the free drug hypothesis; however, potential ALB-facilitated hepatic uptake mechanism(s) were highly suspected. Therefore, the objective of the present study was to reanalyze the IPRL data to provide a deeper quantitative extrapolation of CL; however, the focus was made on the impact of ALB binding on the intrinsic clearance (CLint) versus unbound CLint instead of only the global hepatic CL to verify whether the concept of ALB-facilitated hepatic uptake still holds for these 2 additional parameters for binary mixtures. Firstly, the variations in CLint that were observed between the IPRL model using no ALB and ALB in the perfusates were compared to the corresponding variations in the unbound fraction measured in the perfusates (fup) according to the free drug hypothesis, or to the variations in the fup values adjusted for potential ALB-facilitated uptake mechanism (i.e., fup-adjusted). The parameter fup-adjusted showed a greater predictability compared to fup (average fold error ∼ 1 vs. 5.2), suggesting that both the free and bound drug moieties should be available for hepatic uptake. Secondly, the supplemental data analysis showed a greater decrease in unbound Km than in Vmax resulting in increased uptake CLint of the unbound drug (Vmax/unbound Km) with increased ALB concentration at a given substrate concentration, which is compatible with an ALB-facilitated hepatic uptake mechanism. Interestingly, the unbound CLint increased by a factor that corresponds to the bound drug moiety also assumed available for hepatic uptake. These additional findings corroborate the recent literature. Overall, this study showed the importance of quantifying any differential of ALB concentration (in vitro vs. in vivo or hypoalbuminemia in vivo vs. hyperalbuminemia in vivo) in the IPRL-based, in vitro-to-in vivo or in vivo-to-in vivo extrapolation–based or physiologically based pharmacokinetics–based CL prediction of chemical-drug interactions between xenobiotics significantly bound to ALB.