In Vitro-in Vivo Extrapolation Research Articles

Scaling factors for the in vitro-in vivo extrapolation (IV-IVE) of renal drug and xenobiotic glucuronidation clearance.

To determine the scaling factors required for inclusion of renal drug glucuronidation clearance in the prediction of total clearance via glucuronidation (CLUGT ). Microsomal protein per gram of kidney (MPPGK) was determined for human 'mixed' kidney (n=5) microsomes (MKM). The glucuronidation activities of deferiprone (DEF), propofol (PRO) and zidovudine (AZT) by MKM and paired cortical (KCM) and medullary (KMM) microsomes were measured, along with the UGT 1A6, 1A9 and 2B7 protein contents of each enzyme source. Unbound intrinsic clearances (CLint,u,UGT ) for PRO and morphine (MOR; 3- and 6-) glucuronidation by MKM, human liver microsomes (HLM) and recombinant UGT1A9 and 2B7 were additionally determined. Data were scaled using in vitro-in vivo extrapolation (IV-IVE) approaches to assess the influence of renal CLint,u,UGT on the prediction accuracy of the calculated CLUGT values of PRO and MOR. MPPGK was 9.3±2.0mgg(-1) (mean±SD). The respective rates of DEF (UGT1A6), PRO (UGT1A9) and AZT (UGT2B7) glucuronidation by KCM were 1.4-, 5.2- and 10.5-fold higher than those for KMM. UGT 1A6, 1A9 and 2B7 were the only enzymes expressed in kidney. Consistent with the activity data, the abundance of each of these enzymes was greater in KCM than in KMM. The abundance of UGT1A9 in MKM (61.3pmolmg(-1) ) was 2.7 fold higher than that reported for HLM. Scaled renal PRO glucuronidation CLint,u,UGT was double that of liver. Renal CLint,u,UGT should be accounted for in the IV-IVE of UGT1A9 and considered for UGT1A6 and 2B7 substrates.

New IVIVE method for the prediction of total human clearance and relative elimination pathway contributions from in vitro hepatocyte and microsome data

Total human clearance is a key determinant for the pharmacokinetic behavior of drug candidates. Our group recently introduced the Extended Clearance Model (ECM) as an accurate in vitro–in vivo extrapolation (IVIVE) method for the prediction of hepatic clearance. Yet, knowledge about relative elimination pathway contributions is needed in order to predict the total human clearance of drug candidates. In the present work, a training set of 18 drug compounds was used to describe the affiliations between in vitro sinusoidal uptake clearance and the fractional contributions of hepatic (metabolic and biliary) or renal clearance to overall in vivo elimination. By means of these quantitative relationships and using a validation set of 10 diverse drug molecules covering different (sub)classes of the Extended Clearance Concept Classification System (ECCCS), the relative contributions of elimination pathways were calculated and demonstrated to well correlate with human reference data. Likewise, ECM- and pathway-based predictions of total clearances from both data sets demonstrated a strong correlation with the observed clinical values with 26 out of 28 compounds within a three-fold deviation. Hence, total human clearance and relative contributions of elimination pathways were successfully predicted by the presented method using solely hepatocyte and microsome in vitro data.

Scaling factors for the in vitro-in vivo extrapolation (IV-IVE) of renal drug and xenobiotic glucuronidation clearance.

Scaling factors for the in vitro-in vivo extrapolation (IV-IVE) of renal drug and xenobiotic glucuronidation clearance.

Pathway Based Toxicology and Fit-for-Purpose Assays.

The field of toxicity testing for non-pharmaceutical chemicals is in flux with multiple initiatives in North America and the EU to move away from animal testing to mode-of-action based in vitro assays. In this arena, there are still obstacles to overcome, such as developing appropriate cellular assays, creating pathway-based dose-response models and refining in vitro-in vivo extrapolation (IVIVE) tools. Overall, it is necessary to provide assurances that these new approaches are adequately protective of human and ecological health. Another major challenge for individual scientists and regulatory agencies is developing a cultural willingness to shed old biases developed around animal tests and become more comfortable with mode-of-action based assays in human cells. At present, most initiatives focus on developing in vitro alternatives and assessing how well these alternative methods reproduce past results related to predicting organism level toxicity in intact animals. The path forward requires looking beyond benchmarking against high dose animal studies. We need to develop targeted cellular assays, new cell biology-based extrapolation models for assessing regions of safety for chemical exposures in human populations, and mode-of-action-based approaches which are constructed on an understanding of human biology. Furthermore, it is essential that assay developers have the flexibility to 'validate' against the most appropriate mode-of-action data rather than against apical endpoints in high dose animal studies. This chapter demonstrates the principles of fit-for-purpose assay development using pathway-targeted case studies. The projects include p53-mdm2-mediated DNA-repair, estrogen receptor-mediated cell proliferation and PPARα receptor-mediated liver responses.

Advancing In Vitro-In Vivo Extrapolations of Mechanism-Specific Toxicity Data Through Toxicokinetic Modeling.

International legislation, such as the European REACH regulation (registration, evaluation, authorization, and restriction of chemicals), mandates the assessment of potential risks of an ever-growing number of chemicals to the environment and human health. Although this legislation is considered one of the most important investments in consumer safety ever, the downside is that the current testing strategies within REACH rely on extensive animal testing. To address the ethical conflicts arising from these increased testing requirements, decision-makers, such as the European Chemicals Agency (ECHA), are committed to Russel and Burch's 3R principle (i.e., reduction, replacement, refinement) by demanding that animal experiments should be substituted with appropriate alternatives whenever possible. A potential solution of this dilemma might be the application of in vitro bioassays to estimate toxic effects using cells or cellular components instead of whole organisms. Although such assays are particularly useful to assess potential mechanisms of toxic action, scientists require appropriate methods to extrapolate results from the in vitro level to the situation in vivo. Toxicokinetic models are a straightforward means of bridging this gap. The present chapter describes different available options for in vitro-in vivo extrapolation (IVIVE) of mechanism-specific effects focused on fish species and also reviews the implications of confounding factors during the conduction of in vitro bioassays and their influence on the optimal choice of different dose metrics.

Effect of Age on The Hepatocellularity Number for Wistar rats.

Recently there has been a substantial increase in the number of juvenile animal toxicity studies that are conducted to support pediatric drug safety evaluation. Adequate design of juvenile toxicity studies in rats, for instance with respect to dose levels per age group, requires an understanding of age-dependent pharmacokinetics. In vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) modeling can help to anticipate age-dependent drug exposure in juvenile toxicity studies provided age-dependent profiles for animal physiology and scaling factors are available. For instance, when hepatocytes are used to predict hepatic drug clearance, the hepatocellularity (number of hepatocytes per gram liver, HPGL) is required as one of the scaling factors. Although HPGL is known for adult rats, information on the influence of age on HPGL is missing. The present work profiles the hepatocellularity number in male Wistar rats as a function of age. Using the NADPH-cytochrome P450 reductase (NCR) activity method, the mean HPGL for the adult rat (8 weeks) was 104 × 10(6) cells/gram liver (relative standard deviation 17%). This value was calculated as a ratio between NRC activities in liver homogenates and suspended hepatocytes. The HPGL values were significantly higher (p <0.001) for rat pups until 3 weeks of age compared with adults. Our results revealed that the HPGL value showed a rapid decrease after 3 weeks (end of weaning), essentially reaching adult values by 4 weeks. This age-dependent HPGL profile will be instrumental for hepatic drug clearance prediction when designing juvenile toxicity studies in Wistar rats.

In Vitro-In Vivo Extrapolation Scaling Factors for Intestinal P-Glycoprotein and Breast Cancer Resistance Protein: Part I: A Cross-Laboratory Comparison of Transporter-Protein Abundances and Relative Expression Factors in Human Intestine and Caco-2 Cells.

Over the last 5 years the quantification of transporter-protein absolute abundances has dramatically increased in parallel to the expanded use of in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetics (PBPK)-linked models, for decision-making in pharmaceutical company drug development pipelines and regulatory submissions. Although several research groups have developed laboratory-specific proteomic workflows, it is unclear if the large range of reported variability is founded on true interindividual variability or experimental variability resulting from sample preparation or the proteomic methodology used. To assess the potential for methodological bias on end-point abundance quantification, two independent laboratories, the University of Manchester (UoM) and Bertin Pharma (BPh), employing different proteomic workflows, quantified the absolute abundances of Na/K-ATPase, P-gp, and breast cancer resistance protein (BCRP) in the same set of biologic samples from human intestinal and Caco-2 cell membranes. Across all samples, P-gp abundances were significantly correlated (P = 0.04, Rs = 0.72) with a 2.4-fold higher abundance (P = 0.001) generated at UoM compared with BPh. There was a systematically higher BCRP abundance in Caco-2 cell samples quantified by BPh compared with UoM, but not in human intestinal samples. Consequently, a similar intestinal relative expression factor (REF), derived from distal jejunum and Caco-2 monolayer samples, between laboratories was found for P-gp. However, a 2-fold higher intestinal REF was generated by UoM (2.22) versus BPh (1.11). We demonstrate that differences in absolute protein abundance are evident between laboratories and they probably result from laboratory-specific methodologies relating to peptide choice.

Cynomolgus Monkey as a Clinically Relevant Model to Study Transport Involving Renal Organic Cation Transporters: In Vitro and In Vivo Evaluation.

Organic cation transporter (OCT) 2, multidrug and toxin extrusion protein (MATE) 1, and MATE2K mediate the renal secretion of various cationic drugs and can serve as the loci of drug-drug interactions (DDI). To support the evaluation of cynomolgus monkey as a surrogate model for studying human organic cation transporters, monkey genes were cloned and shown to have a high degree of amino acid sequence identity versus their human counterparts (93.7, 94.7, and 95.4% for OCT2, MATE1, and MATE2K, respectively). Subsequently, the three transporters were individually stably expressed in human embryonic kidney (HEK) 293 cells and their properties (substrate selectivity, time course, pH dependence, and kinetics) were found to be comparable to the corresponding human form. For example, six known human cation transporter inhibitors, including pyrimethamine (PYR), showed generally similar IC50 values against the monkey transporters (within sixfold). Consistent with the in vitro inhibition of metformin (MFM) transport by PYR (IC50 for cynomolgus OCT2, MATE1, and MATE2K; 1.2 ± 0.38, 0.17 ± 0.04, and 0.25 ± 0.04 µM, respectively), intravenous pretreatment of monkeys with PYR (0.5 mg/kg) decreased the clearance (54 ± 9%) and increased in the area under the plasma concentration-time curve of MFM (AUC ratio versus control = 2.23; 90% confidence interval of 1.57 to 3.17). These findings suggest that the cynomolgus monkey may have some utility in support of in vitro-in vivo extrapolations (IVIVEs) involving the inhibition of renal OCT2 and MATEs. In turn, cynomolgus monkey-enabled IVIVEs may inform human DDI risk assessment.

Characterization of transporter activities in fresh isolated primary hepatocytes of different species by using fluorescent substrates

Prediction of human pharmacokinetic profiles of drug candidates is an essential step toward first-in-human studies. However, it remains difficult to quantitatively predict hepatic clearance, particularly when hepatic uptake is mediated by transporter(s). Using 15 organic anion transporting polypeptide (OATP) substrate drugs, we tested 3 in vitro–in vivo extrapolation (IVIVE) approaches to predict overall hepatic intrinsic clearance in vivo (CLint,all,vivo). IVIVE approaches involved metabolic intrinsic clearance in human liver microsomes (CLint,met) with or without hepatocyte-to-buffer maximum unbound concentration ratio (Kp,uu,max) correction and uptake intrinsic clearance at 37°C (PSinf,37°C) in human hepatocyte suspensions. Kp,uu,max and PSinf,37°C values were determined in 2 hepatocyte batches, and all tested compounds showed temperature-dependent uptake, consistent with the fact of transporter-mediated uptake. CLint,met substantially underestimated CLint,all,vivo. By multiplying CLint,met by Kp,uu,max values, the prediction performance was much improved; however, in vitro–in vivo correlation was poor. Among the IVIVE approaches, PSinf,37°C showed the most robust correlation with CLint,all,vivo, and one of the hepatocyte batches could predict CLint,all,vivo with a minimal empirical scaling factor. These results suggested IVIVE with hepatic uptake clearance determined in hepatocyte suspensions as one of the most practical approaches for predicting CLint,all,vivo of OATP substrate drugs.

Choice of LC-MS methods for the absolute quantification of drug-metabolizing enzymes and transporters in human tissue: a comparative cost analysis.

The quantification of drug-metabolizing enzymes and transporters is important for in vitro-in vivo extrapolation (IVIVE) of xenobiotic clearance, which has become an integral part of drug development. There are different mass spectrometry-based techniques used for quantitative proteomics, and as more laboratories are opting for the use of these methods, selecting the most appropriate tool is becoming a concern. For the first time, we attempt to determine the significance of cost of different LC-MS methods of quantitative analysis of these proteins and to present a framework to objectively assess the choice of the techniques. Based on our analysis, quantification using labeled internal standards is more expensive per sample but provides higher quality data than label-free quantification. Quantification using absolute quantification synthetic peptides is the approach of choice for analyzing less than nine proteins, whereas when quantifying a defined set of proteins (10-50), such as enzymes, in a reasonably large number of samples (20-100), the quantification concatemer technique is more economical, followed by label-free quantification. When analyzing proteomes or sub-proteomes (≥500 proteins), label-free quantification is more cost-effective than the use of labeled internal standards. A cost-benefit approach is described to assess the choice of the most appropriate mass spectrometry-based approach for the quantification of proteins relevant to IVIVE.

&lt;i&gt;In vitro&lt;/i&gt; evidence for bakuchiol’s influence towards drug metabolism through inhibition of UDP-glucuronosyltransferase (UGT) 2B7

Inhibition of drug-metabolizing enzymes (DMEs) has been regarded as one of the most important reason for clinical drug-drug interaction. The aim of the present study is to evaluate the inhibition of bakuchiol towards UDP-glucuronosyltransferase (UGT) 2B isoforms. In vitro recombinant UGT2B-catalyzed 4-methylumbelliferone glucuronidation was used as the probe reaction. Dixon plot and Lineweaver-Burk plot were employed to determine the inhibition kinetic type, and nonlinear regression of data was utilized to calculate the inhibition kinetic parameter (Ki). In vitro-in vivo extrapolation (IVIVE) was carried out to predict in vivo inhibition magnitude. Among the tested UGT2B isoforms, UGT2B7 was inhibited by the strongest intensity. The noncompetitive inhibition was demonstrated by the results obtained from Dixon plot and Lineweaver-Burk plot. The Ki value was calculated to be 10.7 µM. In combination with the reported concentration after an intravenous administration of bakuchiol (15 mg/kg) in rats, the high risk of in vivo inhibition of bakuchiol towards UGT2B7-catalyzed metabolism of drugs was indicated. All these results provide an important information for the risk evaluation of the clinical utilization of bakuchiol.

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing.

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.

Predicting the bioconcentration of fragrance ingredients by rainbow trout using measured rates of in vitro intrinsic clearance.

Bioaccumulation in aquatic species is a critical end point in the regulatory assessment of chemicals. Few measured fish bioconcentration factors (BCFs) are available for fragrance ingredients. Thus, predictive models are often used to estimate their BCFs. Because biotransformation can reduce chemical accumulation in fish, models using QSAR-estimated biotransformation rates have been developed. Alternatively, biotransformation can be measured by in vitro methods. In this study, biotransformation rates for nine fragrance ingredients were measured using trout liver S9 fractions and used as inputs to a recently refined in vitro-in vivo extrapolation (IVIVE) model. BCFs predicted by the model were then compared to (i) in vivo BCFs, (ii) BCFs predicted using QSAR-derived biotransformation rates, (iii) BCFs predicted without biotransformation, and (iv) BCFs predicted by a well-known regression model. For fragrance ingredients with relatively low (<4.7) log K(OW) values, all models predicted BCFs below a bioaccumulation threshold of 1000. For chemicals with higher (4.7-5.8) log K(OW) values, the model incorporating measured in vitro biotransformation rates and assuming no correction for potential binding effects on hepatic clearance provided the most accurate predictions of measured BCFs. This study demonstrates the value of integrating measured biotransformation rates for prediction of chemical bioaccumulation in fish.

Lost in centrifugation: accounting for transporter protein losses in quantitative targeted absolute proteomics.

In drug development, considerable efforts are made to extrapolate from in vitro and preclinical findings to predict human drug disposition by using in vitro-in vivo extrapolation (IVIVE) approaches. Use of IVIVE strategies linked with physiologically based pharmacokinetic (PBPK) modeling is widespread, and regulatory agencies are accepting and occasionally requesting model analysis to support licensing submissions. Recently, there has been a drive to improve PBPK models by characterizing the absolute abundance of enzymes, transporters, and receptors within mammalian tissues and in vitro experimental systems using quantitative targeted absolute proteomics (QTAP). The absolute abundance of proteins relevant to processes governing drug disposition provided by QTAP will enable IVIVE-PBPK to incorporate terms for the abundance of enzymes and transporters in target populations. However, most studies that report absolute abundances of enzymes and transporter proteins do so in enriched membrane fractions so as to increase the abundance per sample, and thus the assay's sensitivity, rather than measuring the expected lower abundance in the more biologically meaningful whole cells or tissues. This communication discusses the balance between protein enrichment and potential loss during the preparation of membrane fractions from whole cells or tissues. Accounting for losses with recovery factors throughout the fractionation procedure provides a means to correct for procedural losses, thereby enabling the scaling of protein abundance from subcellular fractions to whole-cell or organ abundances. PBPK models based on corrected abundances will more closely resemble biological systems and facilitate development of more meaningful IVIVE scaling factors, producing more accurate quantitative predictions of drug disposition.

Physiology-based IVIVE predictions of tramadol from in vitro metabolism data.

To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (Simcyp®). Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLintH) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults.

In vitro evidence of baicalein's inhibition of the metabolism of zidovudine (AZT).

Herb-drug interaction (HDI) has been regarded as a key factor limiting the clinical application of herbs and drugs. Potential baicalein-zidovudine (AZT) interaction was predicted in the present study. In vitro evaluation of baicalein's inhibition towards human liver microsomes (HLMs)-catalyzed metabolism of zidovudine (AZT) was performed. Dixon and Lineweaver-Burk plots were used to determine the inhibition kinetic type, and second plot with the slopes from Lineweaver-Burk plot versus the concentrations of baicalein was employed to calculate the inhibition parameter (Ki). In combination with the in vivo concentration of baicalein, in vitro-in vivo extrapolation (IVIVE) was carried out to predict in vivo baicalein-AZT interaction. Competitive inhibition of baicalein towards AZT metabolism was demonstrated, and the Ki value was calculated to be 101.2 µM. The value of AUCi/AUC was calculated to be 2. Potential baicalein-AZT interaction was indicated in the present study, indicating the need for monitoring when AZT is co-administrated with baicalein or baicalein-containing herbs.

In Vitro–In Vivo Extrapolation Method to Predict Human Renal Clearance of Drugs

Renal clearance is a key determinant of the elimination of drugs. To date, only few in vitro-in vivo extrapolation (IVIVE) approaches have been described to predict the renal organ clearance as the net result of glomerular filtration, tubular secretion, and tubular reabsorption. In this study, we measured in LLC-PK1 cells the transport of 20 compounds that cover all four classes of the Biopharmaceutical Drug Disposition System. These data were incorporated into a novel kidney model to predict all renal clearance processes in human. We showed that filtration and secretion were main contributors to the renal organ clearance for all compounds, whereas reabsorption was predominant for compounds assigned to classes 1 and 2. Our results suggest that anionic drugs were not significantly secreted in LLC-PK1 cells, resulting in under-predicted clearances. When all study compounds were included a high overall correlation between the reported and predicted renal organ clearances was obtained (R² = 0.83). The prediction accuracy in terms of percentage within twofold and threefold error was 70% and 95%, respectively. In conclusion, our novel IVIVE method allowed to predict the human renal organ clearance and the contribution of each underlying process.

Simultaneous Quantification of the Abundance of Several Cytochrome P450 and Uridine 5′-Diphospho-Glucuronosyltransferase Enzymes in Human Liver Microsomes Using Multiplexed Targeted Proteomics

Cytochrome P450 (P450) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes mediate a major proportion of phase I and phase II metabolism of xenobiotics. In vitro-in vivo extrapolation (IVIVE) of hepatic clearance in conjunction with physiologically-based pharmacokinetics (PBPK) has become common practice in drug development. However, prediction of xenobiotic kinetics in virtual populations requires knowledge of both enzyme abundances and the extent to which these correlate. A multiplexed quantification concatemer (QconCAT) strategy was used in this study to quantify the expression of several P450 and UGT enzymes simultaneously and to establish correlations between various enzyme abundances in 24 individual liver samples (ages 27-66, 14 male). Abundances were comparable to previously reported values, including CYP2C9 (40.0 ± 26.0 pmol mg(-1)), CYP2D6 (11.9 ± 13.2 pmol mg(-1)), CYP3A4 (68.1 ± 52.3 pmol mg(-1)), UGT1A1 (33.6 ± 34.0 pmol mg(-1)), and UGT2B7 (82.9 ± 36.1 pmol mg(-1)), expressed as mean ± S.D. Previous reports of correlations in expression of various P450 (CYP3A4/CYP3A5*1/*3, CYP2C8/CYP2C9, and CYP3A4/CYP2B6) were confirmed. New correlations were demonstrated between UGTs [including UGT1A6/UGT1A9 (r(s) = 0.82, P < 0.0001) and UGT2B4/UGT2B15 (r(s) = 0.71, P < 0.0001)]. Expression of some P450 and UGT enzymes were shown to be correlated [including CYP1A2/UGT2B4 (r(s) = 0.67, P = 0.0002)]. The expression of CYP3A5 in individuals with *1/*3 genotype (n = 11) was higher than those with *3/*3 genotype (n = 10) (P < 0.0001). No significant effect of gender or history of smoking or alcohol use on enzyme expression was observed; however, expression of several enzymes declined with age. The correlation matrix produced for the first time by this study can be used to generate more realistic virtual populations with respect to abundance of various enzymes.

Toward a new paradigm for the efficient in vitro–in vivo extrapolation of metabolic clearance in humans from hepatocyte data

The objective of this study was to follow up a previous study on a comparative analysis of diverse in vitro–in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs from intrinsic clearance (CLint) data determined in microsomal incubations, but using hepatocyte data instead. Six IVIVE methods were compared: the “conventional and conventional bias‐corrected methods,” the “regression equation method,” the “direct scaling method,” the “Berezhkovskiy's method,” and the “novel IVIVE method of Poulin et al.” offering a new paradigm. A large and diverse dataset of 49 drugs were collected from the literature for hepatocyte data in human. Based on all statistical parameters, this study confirms that the novel IVIVE method of Poulin et al. shows the greatest prediction performance among the IVIVE methods tested by using hepatocyte data. The superior prediction performance of this novel IVIVE method is again most pronounced for (a) drugs highly bound in blood, (b) drugs bound to albumin, and (c) low CL drugs. Because the novel IVIVE method has been developed particularly to improve the prediction accuracy for drugs with such properties, this study confirms its utility. Furthermore, the results of the current comparative analysis performed using hepatocyte data confirm the findings of a previous analysis made with microsomal data. Overall, the proposed novel IVIVE method offers a new paradigm for the prediction of hepatic metabolic CL particularly for drugs, which have the aforementioned properties, and, hence, this would contribute to a more accurate CL prediction for small molecules in drug discovery and development, interspecies scaling, and can potentially be used for the optimization of driving factors of CL in an attempt to facilitate the simulation of drug disposition by using the physiologically based pharmacokinetics (PBPK) model. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 102:3239–3251, 2013

A Mechanistic Framework for In Vitro–In Vivo Extrapolation of Liver Membrane Transporters: Prediction of Drug–Drug Interaction Between Rosuvastatin and Cyclosporine

Background and ObjectivesThe interplay between liver metabolising enzymes and transporters is a complex process involving system-related parameters such as liver blood perfusion as well as drug attributes including protein and lipid binding, ionisation, relative magnitude of passive and active permeation. Metabolism- and/or transporter-mediated drug–drug interactions (mDDIs and tDDIs) add to the complexity of this interplay. Thus, gaining meaningful insight into the impact of each element on the disposition of a drug and accurately predicting drug–drug interactions becomes very challenging. To address this, an in vitro–in vivo extrapolation (IVIVE)-linked mechanistic physiologically based pharmacokinetic (PBPK) framework for modelling liver transporters and their interplay with liver metabolising enzymes has been developed and implemented within the Simcyp Simulator®.MethodsIn this article an IVIVE technique for liver transporters is described and a full-body PBPK model is developed. Passive and active (saturable) transport at both liver sinusoidal and canalicular membranes are accounted for and the impact of binding and ionisation processes is considered. The model also accommodates tDDIs involving inhibition of multiple transporters. Integrating prior in vitro information on the metabolism and transporter kinetics of rosuvastatin (organic-anion transporting polypeptides OATP1B1, OAT1B3 and OATP2B1, sodium-dependent taurocholate co-transporting polypeptide [NTCP] and breast cancer resistance protein [BCRP]) with one clinical dataset, the PBPK model was used to simulate the drug disposition of rosuvastatin for 11 reported studies that had not been used for development of the rosuvastatin model.ResultsThe simulated area under the plasma concentration–time curve (AUC), maximum concentration (C max) and the time to reach C max (t max) values of rosuvastatin over the dose range of 10–80 mg, were within 2-fold of the observed data. Subsequently, the validated model was used to investigate the impact of coadministration of cyclosporine (ciclosporin), an inhibitor of OATPs, BCRP and NTCP, on the exposure of rosuvastatin in healthy volunteers.ConclusionThe results show the utility of the model to integrate a wide range of in vitro and in vivo data and simulate the outcome of clinical studies, with implications for their design.Electronic supplementary materialThe online version of this article (doi:10.1007/s40262-013-0097-y) contains supplementary material, which is available to authorized users.