Utility of hepatocytes in predicting drug metabolism: comparison of hepatic intrinsic clearance in rats and humans in vivo and in vitro

Contribution of Japanese scientists to drug metabolism and disposition

Japanese researchers have played a pivotal role in advancing the field of drug metabolism and disposition, as demonstrated by their substantial contributions to the journal Drug Metabolism and Disposition (DMD) over the past 5 decades. This review highlights the historical and ongoing impact of Japanese scientists on DMD, celebrating their achievements in elucidating drug metabolism, membrane transport, pharmacokinetics, and toxicology. From the discovery of cytochrome P450 by Tsuneo Omura and Ryo Sato in 1962 to subsequent advances in drug transport research, Japan has maintained a leading position in the field. A geographical analysis of DMD publications reveals a notable increase in contributions from Japan during the 1980s, ranking second globally and maintaining this position through the 2000s. However, recent years have seen a slight decline in output, likely influenced by the COVID-19 pandemic and increased online journals as well as structural changes within academia and industry. Importantly, this trend is not unique to Japan. To sustain excellence and innovation in this field, it is crucial to strengthen funding for absorption, distribution, metabolism, excretion, and toxicity research and promote collaborations between academia, industry, and regulatory agencies. By prioritizing the translation of fundamental discoveries into drug development and clinical applications, scientists in this area can further advance global efforts toward achieving optimal drug efficacy and safety. This review underscores the enduring contributions of Japanese researchers to DMD and calls for renewed efforts to drive innovation and progress in this vital area of science. SIGNIFICANCE STATEMENT: Over the past 5 decades, Japanese scientists have made significant contributions to Drug Metabolism and Disposition through groundbreaking discoveries and advancements in the study of drug-metabolizing enzymes, transporters, pharmacokinetics analysis, and related areas. These contributions continue to shape the field, offering a foundation for future innovation in this area. We hope that the next generation of Japanese scientists will further solidify their global leadership in this area to advance drug development and proper pharmacotherapy.

Characterizing the Hepatic Metabolic Pathway of Ketone Ester and Subsequent Metabolites Using Human and Rat Liver Fractions

Although exogenous ketogenic dietary supplements continue to grow in popularity, their pharmacokinetic properties have not been adequately studied, thus hindering their optimal use and benefits. Here, the metabolic characteristics of one such supplement (Veech ketone mono-ester ((R)-3-hydroxybutyl(R)-3-hydroxybutyrate) (KE)) were studied along with its metabolite- (R)-1,3-butanediol ((R)-1,3-BD), both of which are precursors and undergo metabolic conversion to (R)-beta-hydroxybutyrate (BHB). The metabolism of aldol (an aldehyde intermediate between the conversion of (R)-1,3-BD to (R)-BHB was also evaluated, as it is frequently not considered in any scientific discussion. The metabolic parameters were calculated using pooled human (mixed gender) and pooled rat (male and female) liver fractions. These were later used to estimate the hepatic extraction ratio and the hepatic clearance of these molecules. KE showed rapid and non-saturable clearance in human and rat liver fractions, even at concentrations as high as 15,000 μM. In the case of (R)-1,3-BD, there was saturable metabolism in rats and humans with Km and Vmax values of 8,000 μM and 27.1 nmol/min/mg of protein (humans), 19,300 μM and 113.5 nmol/min/mg of protein (male rats), and 11,910 μM and 75.8 nmol/min/mg of protein (female rats). The metabolism of aldol showed rapid and non-saturable hepatic clearance in human liver fractions.

Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase-CYP substrates

Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug-metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO-mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO-CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fmAO) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fmi from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fmAO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fmCYP3A4, with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach.

Investigation of pharmacokinetic properties of a PEGylated bilirubin nanoparticle in male Sprague-Dawley rats using liquid chromatography-quadrupole time-of-flight mass spectrometry

Polyethylene glycol (PEG) was introduced into synthetic bilirubin 3α and a PEGylated bilirubin 3α nanoparticle (BX-001N, Brixelle®) was developed for the first time.An in vitro microsomal stability study, in vivo PK studies with intravenous bolus (IV) and subcutaneous injection (SC), and a semi-mass balance study of BX-001N were investigated to evaluate its pharmacokinetic (PK) properties in male Sprague-Dawley (SD) rats using developed liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-qTOF/MS).Following IV administration at 10 or 30 mg/kg, BX-001N showed very low clearance (0.33-0.67 mL/min/kg) with predominant distribution in the vascular system (Vd = 51.73-83.02 mL/kg). BX-001N was also very stable in vitro liver microsomal stability study.Following SC administration at 10 or 30 mg/kg, the bioavailability of BX-001N in plasma at 10 mg/kg was around 43% and showed the less dose-proportionality at 30 mg/kg dose.BX-001N was mainly excreted via the urinary pathway (86.59-92.99% of total amount of parent drug in excreta; urine and faeces) not via the biliary one.

Forecasting Fetal Buprenorphine Exposure through Maternal-Fetal Physiologically Based Pharmacokinetic Modeling

Buprenorphine readily crosses the placenta, and with greater prenatal exposure, neonatal opioid withdrawal syndrome (NOWS) likely grows more severe. Current dosing strategies can be further improved by tailoring doses to expected NOWS severity. To allow the conceptualization of fetal buprenorphine exposure, a maternal-fetal physiologically based pharmacokinetic (PBPK) model for sublingual buprenorphine was developed using Simcyp (v21.0). Buprenorphine transplacental passage was predicted from its physicochemical properties. The maternal-fetal PBPK model integrated reduced transmucosal absorption driven by lower salivary pH and induced metabolism observed during pregnancy. Maternal pharmacokinetics was adequately predicted in the second trimester, third trimester, and postpartum period, with the simulated area under the curve from 0 to 12 h, apparent clearance, and peak concentration falling within the 1.25-fold prediction error range. Following post hoc adjustment of the likely degree of individual maternal sublingual absorption, umbilical cord blood concentrations at delivery (n = 21) were adequately predicted, with a geometric mean ratio between predicted and observed fetal concentrations of 1.15 and with 95.2% falling within the 2-fold prediction error range. The maternal-fetal PBPK model developed in this study can be used to forecast fetal buprenorphine exposure and would be valuable to investigate its correlation to NOWS severity.

Prediction of pharmacokinetics of an anaplastic lymphoma kinase inhibitor in rat and monkey: application of physiologically based pharmacokinetic model as an alternative tool to minimise animal studies

The pharmacokinetic (PK) and toxicokinetic profile of a drug from its preclinical evaluation helps the researcher determine whether the drug should be tested in humans based on its safety and toxicity.Preclinical studies require time and resources and are prone to error. Moreover, according to the United States Food and Drug Administration Modernisation Act 2, animal testing is no longer mandatory for new drug development, and an animal-free alternative, such as cell-based assay and computer models, can be used.Different physiologically based PK models were developed for an anaplastic lymphoma kinase inhibitor in rats and monkeys after intravenous and oral administration using its physicochemical properties and in vitro characterisation data.The developed model was validated against the in vivo data available in the literature, and the validation results were found within the acceptable limit. A parameter sensitivity analysis was performed to identify the properties of the compound influencing the PK profile.This work demonstrates the application of the physiologically based PK model to predict the PKs of a drug, which will eventually assist in reducing the number of animal studies and save time and cost of drug discovery and development.

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Identification of PPA1 inhibitor candidates for potential repurposing in cancer medicine

Inorganic pyrophosphatase 1 (PPA1) is pivotal to cellular metabolism as it facilitates the hydrolysis of PPi-a by-product of various metabolic processes that influence cell growth and differentiation. Overexpression of PPA1 enzyme has been linked to diminished patient survival and was shown to influence tumor cell dynamics, thereby positioning it as a potential therapy target for a variety of cancers including colorectal cancer, diffuse large B-cell lymphoma, and lung adenocarcinoma. Despite this therapeutic promise, there are no known inhibitors of PPA1 as of today. In this study, we searched for potential PPA1 inhibitors using a molecular docking screen of 30 470 compounds with a history of clinical trials and/or US Food and Drug Administration approval. We specifically targeted the active pocket that coincides with the established catalytic domain. Our screen identified promising hits, which we further subjected to ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering. Subsequent molecular dynamics (MD) analyses were conducted on devazepide, quinotolast, and tarazepide-the three substances that successfully navigated all filters. MD analyses reinforced the stability of the protein-ligand complexes and confirmed ligand binding, as substantiated by our root mean square deviation, radius of gyration and secondary structures of proteins analyses. Furthermore, Molecular Mechanics Poisson-Boltzmann Surface Area calculations post-MD identified devazepide and quinotolast as showing higher binding affinities; being supported by principal component analysis, free energy landscape, and dynamic cross-correlation matrix results. Overall, our study reveals devazepide and quinotolast as potential candidates for PPA1 inhibition which could be considered for repurposing studies that need further experimental validation. These results not only reveal a potential for clinical repurposing for PPA1 inhibition but they also offer valuable insights into the development of future compounds for targeting the crucial PPA1 enzyme.

In Vitro Pharmacokinetic Behavior of Antiviral 3-Amidinophenylalanine Derivatives in Rat, Dog and Monkey Hepatocytes

Type II transmembrane serine proteases represent pharmacological targets for blocking entry and spread of influenza or coronaviruses. In this study, the depletion rates of the 3-amidinophenylalanine (3-APhA)-derived matriptase/TMPRSS2 inhibitors MI-463, MI-472, MI-485 or MI-1900 were determined by LC-MS/MS measurements over a period of 300 min using suspensions of rat, dog and cynomolgus monkey primary hepatocytes. From these in vitro pharmacokinetic (PK) experiments, intrinsic clearance values (Clint) were evaluated, and in vivo pharmacokinetic parameters (hepatic clearance, hepatic extraction ratio and bioavailability) were predicted. It was found that rat hepatocytes were the most active in the metabolism of 3-APhA derivatives (Clint 31.9–37.8 mL/min/kg), whereas dog and monkey cells displayed somewhat lower clearance of these compounds (Clint 6.6–26.7 mL/min/kg). These data support elucidation of important PK properties of anti-TMPRSS2/anti-matriptase 3-APhAs using mammalian hepatocyte models and thus contribute to the optimization of lead compounds.

Application of a Volumetric Absorptive Microsampling (VAMS)-Based Method for the Determination of Paracetamol and Four of its Metabolites as a Tool for Pharmacokinetic Studies in Obese and Non-Obese Patients

BACKGROUND

The pharmacokinetic (PK) profile of a drug is influenced by several factors, which can lead to a suboptimal dosing regimen in specific patient populations. As obesity becomes increasingly prevalent, it is important that optimized dosing schemes are available for these patients. To set up such dosing schemes, PK studies should be performed in this population. Regarding paracetamol (acetaminophen [APAP]), obese patients would benefit from a tailored dosing scheme, as both the volume of distribution and metabolism are increased compared with non-obese patients. This includes metabolism by cytochrome P450 2E1, which is involved in APAP-associated hepatotoxicity. To decrease the burden for patients in these PK studies, finger-prick sampling could be used.

OBJECTIVE

The aim of this study was to compare the quantitative determination of APAP and four metabolites in different blood-based matrices and to determine if capillary dried blood samples, collected directly following finger-prick, could serve as a tool to investigate APAP PK in obese and non-obese patients.

METHODS

In this study, we performed a clinical validation of methods for the determination of APAP and four of its metabolites (APAP-glucuronide, APAP-sulfate, APAP-mercapturate, and APAP-cysteine) in blood, plasma, and dried blood. The latter was obtained by volumetric absorptive microsampling (VAMS), either starting from the venous blood or collected directly following a finger-prick. Results were compared between the different matrices and, in addition, blood:plasma (B:P) ratios were determined for the different analytes.

RESULTS

Liquid and dried venous blood results were in good agreement. Furthermore, differences between capillary (finger-prick) and venous VAMS blood samples remained limited for most analytes. However, for APAP-cysteine, caution should be paid to the interpretation of concentrations in (dried) blood. With the exception of APAP, concentrations were higher in plasma compared with blood, with B:P ratios ranging between 0.52 and 0.65. A time-dependent change in median B:P ratio was observed for APAP and APAP-cysteine. Additionally, a time-dependent trend was seen for APAP, as well as for APAP-glucuronide and APAP-mercapturate, for the distribution between capillary and venous blood.

CONCLUSIONS

We demonstrated that finger-prick sampling is a viable alternative to conventional venous blood sampling to investigate the PK of APAP and its metabolites in obese and non-obese patients.

The evaluation of ADME and pharmacokinetic properties of decoquinate derivatives for the treatment of malaria

The emergence of Plasmodium falciparum (Pf) parasite strains tolerant of the artemisinin component and resistant to the other drug component in artemisinin combination therapies (ACTs) used for treatment now markedly complicates malaria control. Thus, development of new combination therapies are urgently required. For the non-artemisinin component, the quinolone ester decoquinate (DQ) that possesses potent activities against blood stage Pf and acts on a distinct target, namely the Pf cytochrome bc₁ complex, was first considered. However, DQ has poor drug properties including high lipophilicity and exceedingly poor aqueous solubility (0.06 μg/ml), rendering it difficult to administer. Thus, DQ was chemically modified to provide the secondary amide derivative RMB005 and the quinoline O-carbamate derivatives RMB059 and RMB060. The last possesses sub-nanomolar activities against multidrug resistant blood stages of Pf, and P. berghei sporozoite liver stages. Here we present the results of ADME analyses in vitro and pharmacokinetic analyses using C57BL/6 mice. The amide RMB005 had a maximum mean whole blood concentration of 0.49 ± 0.02 µM following oral administration; however, the area under the curve (AUC), elimination half-life (t_1/2) and bioavailability (BA) were not significantly better than those of DQ. Surprisingly, the quinoline O-carbamates which can be recrystallized without decomposition were rapidly converted into DQ in human plasma and blood samples. The maximum concentrations of DQ reached after oral administration of RMB059 and RMB060 were 0.23 ± 0.05 and 0.11 ± 0.01 µM, the DQ elimination half-lives were 4.79 ± 1.66 and 4.66 ± 1.16 h, and the DQ clearance were 19.40 ± 3.14 and 21.50 ± 3.38 respectively. Under these assay conditions, the BA of DQ could not be calculated Overall although RMB059 and -060 are labile in physiological medium with respect to the DQ parent, the potential to apply these as prodrugs is apparent from the current data coupled with their ease of preparation.

Prediction of hepatic drug clearance with a human microfluidic four-cell liver acinus microphysiology system

Predicting human hepatic clearance remains a fundamental challenge in both pharmaceutical drug development and toxicological assessments of environmental chemicals, with concerns about both accuracy and precision of in vitro-derived estimates. Suggested sources of these issues have included differences in experimental protocols, differences in cell sourcing, and use of a single cell type, liver parenchymal cells (hepatocytes). Here we investigate the ability of human microfluidic four-cell liver acinus microphysiology system (LAMPS) to make predictions as to hepatic clearance for seven representative compounds: Caffeine, Pioglitazone, Rosiglitazone, Terfenadine, Tolcapone, Troglitazone, and Trovafloxacin. The model, whose reproducibility was recently confirmed in an inter-lab comparison, was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. We calculated hepatic clearance estimates derived from experiments using LAMPS or traditional 2D cultures and compared the outcomes with both in vivo human clinical study-derived and in vitro human hepatocyte suspension culture-derived values reported in the literature. We found that, compared to in vivo clinically-derived values, the LAMPS model with iPSC-derived hepatocytes had higher precision as compared to primary cells in suspension or 2D culture, but, consistent with previous studies in other microphysiological systems, tended to underestimate in vivo clearance. Overall, these results suggest that use of LAMPS and iPSC-derived hepatocytes together with an empirical scaling factor warrants additional study with a larger set of compounds, as it has the potential to provide more accurate and precise estimates of hepatic clearance.

High-throughput PBTK models for in vitro to in vivo extrapolation

INTRODUCTION

Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.

AREAS COVERED

This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on 'httk', a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.

EXPERT OPINION

HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.

Using Chemical Structure Information to Develop Predictive Models for In Vitro Toxicokinetic Parameters to Inform High-throughput Risk-assessment

The toxicokinetic (TK) parameters fraction of the chemical unbound to plasma proteins and metabolic clearance are critical for relating exposure and internal dose when building in vitro-based risk assessment models. However, experimental toxicokinetic studies have only been carried out on limited chemicals of environmental interest (~1000 chemicals with TK data relative to tens of thousands of chemicals of interest). This work evaluated the utility of chemical structure information to predict TK parameters in silico; development of cluster-based read-across and quantitative structure-activity relationship models of fraction unbound or fub (regression) and intrinsic clearance or Cl_int (classification and regression) using a dataset of 1487 chemicals; utilization of predicted TK parameters to estimate uncertainty in steady-state plasma concentration (C_ss); and subsequent in vitro-in vivo extrapolation analyses to derive bioactivity-exposure ratio (BER) plot to compare human oral equivalent doses and exposure predictions using androgen and estrogen receptor activity data for 233 chemicals as an example dataset. The results demonstrate that fub is structurally more predictable than Cl_int. The model with the highest observed performance for fub had an external test set RMSE/σ=0.62 and R²=0.61, for Cl_int classification had an external test set accuracy = 65.9%, and for intrinsic clearance regression had an external test set RMSE/σ=0.90 and R²=0.20. This relatively low performance is in part due to the large uncertainty in the underlying Cl_int data. We show that C_ss is relatively insensitive to uncertainty in Cl_int. The models were benchmarked against the ADMET Predictor software. Finally, the BER analysis allowed identification of 14 out of 136 chemicals for further risk assessment demonstrating the utility of these models in aiding risk-based chemical prioritization.

Seeking Nonspecific Binding: Assessing the Reliability of Tissue Dilutions for Calculating Fraction Unbound

It has become commonplace (270+ article citations to date) to measure the fraction unbound (FrUn) of drugs in tissue homogenates and diluted plasma and then use a Correction Factor Equation (CFE) to extrapolate to the undiluted state. The CFE is based on assumptions of nonspecific binding with experimental use of very low drug concentrations. There are several possible determinants of apparent nonspecific binding as measured by methods such as equilibrium dialysis: true macromolecule binding and lipid partitioning along with receptor, enzyme, and transporter interactions. Theoretical calculations based on nonlinear protein binding indicate that the CFE will be most reliable to obtain FrUn when added drug concentration is small, binding constants are weak, protein concentrations are relatively high, and tissue dilution is minimal. When lipid partitioning is the sole factor determining apparent tissue binding, the CFE should be perfectly accurate. Use of very low drug concentrations, however, makes it more likely that specific binding to receptors and other targets may occur, and thus FrUn may reflect some binding to such components. Inclusion of trapped blood can clearly cause minor to marked discrepancies from purely tissue binding alone, which can be corrected. Furthermore, assessment of the occurrence of ionization/pH shifts, drug instability, and tissue metabolism may be necessary. Caution is needed in the use and interpretation of results from tissue dilution studies and other assessments of nonspecific binding, particularly for very strongly bound drugs with very small FrUn values and in tissues with metabolic enzymes, receptors, and trapped blood. SIGNIFICANCE STATEMENT: The use of tissue, plasma, and cell preparations to help obtain fraction unbound and tissue-to-plasma partition coefficients in pharmacokinetics has grown commonplace, especially for brain. This report examines theoretical, physiological, and experimental issues that need consideration before trusting such measurements and calculations.

Comparative assessment for rat strain differences in metabolic profiles of 14 drugs in Wistar Han and Sprague Dawley hepatocytes

Knowledge of inter-strain and inter-gender differences in drug metabolism studies is important for animal selection in pharmacokinetic and toxicological studies. The effects of rat strain and gender in in vitro metabolism were investigated in Sprague Dawley (SD) and Wister Han (WH) rats based on the hepatocyte metabolic profiles of 14 small molecule drugs. Similarities were found between the hepatocyte metabolic clearances of SD and WH strains, suggesting that only one strain can be confidently used for the evaluation of hepatic clearance. Neither strain of rat was preferable over the other to cover human metabolites. Higher similarities in metabolic pathways were found between the same gender than the same strain. Differences in metabolite identities, metabolite formation rates and potential biotransformation pathways were observed between SD and WH rat strains. Eleven metabolites from six drugs were "disproportionally" formed between SD and WH rats. The use of a specific rat strain model and gender for ADME and toxicity testing should, therefore, be carefully considered as metabolic profiles may differ, even though metabolic clearance was similar between SD and WH rats.

Ethambutol disposition in humans: Challenges and limitations of whole-body physiologically-based pharmacokinetic modelling in early drug development

Whole-body physiologically based pharmacokinetic (WB-PBPK) models have become an important tool in drug development, as they enable characterization of pharmacokinetic profiles across different organs based on physiological (systems-specific) and physicochemical (drug-specific) properties. However, it remains unclear which data are needed for accurate predictions when applying the approach to novel candidate molecules progressing into the clinic. In this work, as case study, we investigated the predictive performance of WB-PBPK models both for prospective and retrospective evaluation of the pharmacokinetics of ethambutol, considering scenarios that reflect different stages of development, including settings in which the data are limited to in vitro experiments, in vivo preclinical data, and when some clinical data are available. Overall, the accuracy of PBPK model-predicted systemic and tissue exposure was heavily dependant on prior knowledge about the eliminating organs. Whilst these findings may be specific to ethambutol, the challenges and potential limitations identified here may be relevant to a variety of drugs, raising questions about (1) the minimum requirements for prospective use of WB-PBPK models during the characterization of drug disposition and (2) implication of uncertainty for dose selection in humans.

Metabolic Stability of D-Allulose in Biorelevant Media and Hepatocytes: Comparison with Fructose and Erythritol

D-allulose, a C-3 epimer of D-fructose, is a rare monosaccharide used as a food ingredient or a sweetener. In the present study, the in vitro metabolic stability of D-allulose was examined in biorelevant media, that is, simulated gastric fluid (SGF) and fasted state simulated intestinal fluid (FaSSIF) containing digestive enzymes, and in cryopreserved human and rat hepatocytes. The hepatocyte metabolic stabilities of D-allulose were also investigated and compared with those of fructose and erythritol (a sugar-alcohol with no calorific value). D-allulose was highly stable in SGF (97.8% remained after 60 min) and in FaSSIF (101.3% remained after 240 min), indicating it is neither pH-labile nor degraded in the gastrointestinal tract. D-allulose also exhibited high levels of stability in human and rat hepatocytes (94.5–96.8% remained after 240 min), whereas fructose was rapidly metabolized (43.1–52.6% remained), which suggested these two epimers are metabolized in completely different ways in the liver. The effects of D-allulose on glucose and fructose levels were negligible in hepatocytes. Erythritol was stable in human and rat hepatocytes (102.1–102.9% remained after 240 min). Intravenous pharmacokinetic studies in rats showed D-allulose was eliminated with a mean half-life of 72.2 min and a systemic clearance of 15.8 mL/min/kg. Taken together, our results indicate that D-allulose is not metabolized in the liver, and thus, unlikely to contribute to hepatic energy production.

Prediction of Atorvastatin Pharmacokinetics in High-Fat Diet and Low-Dose Streptozotocin-Induced Diabetic Rats Using a Semiphysiologically Based Pharmacokinetic Model Involving Both Enzymes and Transporters

Atorvastatin is a substrate of cytochrome P450 3a (CYP3a), organic anion-transporting polypeptides (OATPs), breast cancer-resistance protein (BCRP), and P-glycoprotein (P-gp). We aimed to develop a semiphysiologically based pharmacokinetic (semi-PBPK) model involving both enzyme and transporters for predicting the contributions of altered function and expression of CYP3a and transporters to atorvastatin transport in diabetic rats by combining high-fat diet feeding and low-dose streptozotocin injection. Atorvastatin metabolism and transport parameters comes from in situ intestinal perfusion, primary hepatocytes, and intestinal or hepatic microsomes. We estimated the expressions and functions of these proteins and their contributions. Diabetes increased the expression of hepatic CYP3a, OATP1b2, and P-gp but decreased the expression of intestinal CYP3a, OATP1a5, and P-gp. The expression and function of intestinal BCRP were significantly decreased in 10-day diabetic rats but increased in 22-day diabetic rats. Based on alterations in CYP3a and transporters by diabetes, the developed semi-PBPK model was successfully used to predict atorvastatin pharmacokinetics after oral and intravenous doses to rats. Contributions to oral atorvastatin PK were intestinal OATP1a5 < intestinal P-gp < intestinal CYP3a < hepatic CYP3a < hepatic OATP1b2 < intestinal BRCP. Contributions of decreased expression and function of intestinal CYP3a and P-gp by diabetes to oral atorvastatin plasma exposure were almost attenuated by increased expression and function of hepatic CYP3a and OATP1b2. Opposite alterations in oral plasma atorvastatin exposure in 10- and 22-day diabetic rats may be explained by altered intestinal BCRP. In conclusion, the altered atorvastatin pharmacokinetics by diabetes was the synergistic effects of altered intestinal or hepatic CYP3a and transporters and could be predicted using the developed semi-PBPK.

Synthesis of new 5,6,7,8-tetrahydropyrido[1,2-c]pyrimidine derivatives with rigidized tryptamine moiety as potential SSRI and 5-HT1A receptor ligands

Extended studies in the 4-aryl-pyrido[1,2-c]pyrimidine group resulted in 27 new compounds (10.1-10.27), 5,6,7,8-tetrahydropyrido[1,2-c]pyrimidine derivatives. In vitro tests (RBA) were carried out for 10.1-10.27 compounds in order to determine their affinity to 5-HT_1A receptor and SERT protein. 10.1-10.3, 10.6, 10.7, 10.16 and 10.27 compounds had high binding ability to both molecular targets (5-HT_1A K_i = 8-87 nM; SERT K_i = 8-52 nM). For these compounds (10.1-10.3, 10.6, 10.7, 10.16, 10.27) further in vitro, in vivo and metabolic stability tests were performed. In vitro studies in the extended receptor profile (D₂, 5-HT_2A, 5-HT₆ and 5-HT₇) showed their selectivity towards 5-HT_1A receptor and SERT protein. In vivo tests revealed that compounds 10.7 and 10.16 had the properties of presynaptic antagonists of the 5-HT_1A receptor. The redesign of the 2H-pyrido[1,2-c]pyrimidine residue present in the terminal part towards 5,6,7,8-tetrahydropyrido[1,2-c]pyrimidine resulted in the improved metabolic stability and enhanced affinity to both molecular targets (5-HT_1A-R and SERT) compared to the precursors.

Interlaboratory Variability in Human Hepatocyte Intrinsic Clearance Values and Trends with Physicochemical Properties

PURPOSE

To examine the interlaboratory variability in CL_int values generated with human hepatocytes and determine trends in variability and clearance prediction accuracy using physicochemical and pharmacokinetic parameters.

METHODS

Data for 50 compounds from 14 papers were compiled with physicochemical and pharmacokinetic parameter values taken from various sources.

RESULTS

Coefficients of variation were as high as 99.8% for individual compounds and variation was not dependent on the number of prediction values included in the analysis. When examining median values, it appeared that compounds with a lower number of rotatable bonds had more variability. When examining prediction uniformity, those compounds with uniform in vivo underpredictions had higher CL_{int, in vivo} values, while those with non-uniform predictions typically had lower CL_{int, in vivo} values. Of the compounds with uniform predictions, only a small number were uniformly predicted accurately. Based on this limited dataset, less lipophilic, lower intrinsic clearance, and lower protein binding compounds yield more accurate clearance predictions.

CONCLUSIONS

Caution should be taken when compiling in vitro CL_int values from different laboratories as variations in experimental procedures (such as extent of shaking during incubation) may yield different predictions for the same compound. The majority of compounds with uniform in vitro values had predictions that were inaccurate, emphasizing the need for a better mechanistic understanding of IVIVE. The non-uniform predictions, often with low turnover compounds, reaffirmed the experimental challenges for drugs in this clearance range. Separating new chemical entities by lipophilicity, intrinsic clearance, and protein binding may help instill more confidence in IVIVE predictions.

Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions

Linking in vitro bioactivity and in vivo toxicity on a dose basis enables the use of high-throughput in vitro assays as an alternative to traditional animal studies. In this study, we evaluated assumptions in the use of a high-throughput, physiologically based toxicokinetic (PBTK) model to relate in vitro bioactivity and rat in vivo toxicity data. The fraction unbound in plasma (f_up) and intrinsic hepatic clearance (Cl_int) were measured for rats (for 67 and 77 chemicals, respectively), combined with f_up and Cl_int literature data for 97 chemicals, and incorporated in the PBTK model. Of these chemicals, 84 had corresponding in vitro ToxCast bioactivity data and in vivo toxicity data. For each possible comparison of in vitro and in vivo endpoint, the concordance between the in vivo and in vitro data was evaluated by a regression analysis. For a base set of assumptions, the PBTK results were more frequently better associated than either the results from a “random” model parameterization or direct comparison of the “untransformed” values of AC₅₀ and dose (performed best in 51%, 28%, and 21% of cases, respectively). We also investigated several assumptions in the application of PBTK for IVIVE, including clearance and internal dose selection. One of the better assumptions sets–restrictive clearance and comparing free in vivo venous plasma concentration with free in vitro concentration–outperformed the random and untransformed results in 71% of the in vitro-in vivo endpoint comparisons. These results demonstrate that applying PBTK improves our ability to observe the association between in vitro bioactivity and in vivo toxicity data in general. This suggests that potency values from in vitro screening should be transformed using in vitro-in vivo extrapolation (IVIVE) to build potentially better machine learning and other statistical models for predicting in vivo toxicity in humans.

Species differences in metabolism of a new antiepileptic drug candidate, DSP-0565 [2-(2'-fluoro[1,1'-biphenyl]-2-yl)acetamide]

The metabolism and pharmacokinetics of DSP-0565 [2-(2'-fluoro[1,1'-biphenyl]-2-yl)acetamide], an antiepileptic drug candidate, was investigated in rats, dogs, and humans. In human hepatocytes, [¹⁴ C]DSP-0565 was primarily metabolized via amide bond hydrolysis to (2'-fluoro[1,1'-biphenyl]-2-yl)acetic acid (M8), while in rat and dog hepatocytes, it was primarily metabolized via both hydrolysis to M8 and hydroxylation at the benzene ring or the benzyl site to oxidized metabolites. After single oral administration of [¹⁴ C]DSP-0565 to rats and dogs, the major radioactivity fraction was recovered in the urine (71-72% of dose) with a much smaller fraction recovered in feces (23-25% of dose). As primary metabolites in their excreta, M8, oxidized metabolites, and glucuronide of DSP-0565 were detected. The contribution of metabolic pathways was estimated from metabolite profiles in their excreta: the major metabolic pathway was oxidation (57-62%) and the next highest was the hydrolysis pathway (23-33%). These results suggest that there are marked species differences in the metabolic pathways of DSP-0565 between humans and animals. Finally, DSP-0565 human oral clearance (CL/F) was predicted using in vitro-in vivo extrapolation (IVIVE) with/without animal scaling factors (SF, in vivo intrinsic clearance/in vitro intrinsic clearance). The SF improved the underestimation of IVIVE (fold error = 0.22), but the prediction was overestimated (fold error = 2.4-3.3). In contrast, the use of SF for hydrolysis pathway was the most accurate for the prediction (fold error = 1.0-1.4). Our findings suggest that understanding of species differences in metabolic pathways between humans and animals is important for predicting human metabolic clearance when using animal SF.

A Comparison of Total and Plasma Membrane Abundance of Transporters in Suspended, Plated, Sandwich-Cultured Human Hepatocytes Versus Human Liver Tissue Using Quantitative Targeted Proteomics and Cell Surface Biotinylation

Suspended (SH), plated (PH), and sandwich-cultured hepatocytes (SCH) are commonly used models to predict in vivo transporter-mediated hepatic uptake (SH or PH) or biliary (SCH) clearance of drugs. When doing so, the total and the plasma membrane abundance (PMA) of transporter are assumed not to differ between hepatocytes and liver tissue (LT). This assumption has never been tested. In this study, we tested this assumption by measuring the total and PMA of the transporters in human hepatocyte models versus LT (total only) from which they were isolated. Total abundance of OATP1B1/2B1/1B3, OCT1, and OAT2 was not significantly different between the hepatocytes and LT. The same was true for the PMA of these transporters across the hepatocyte models. In contrast, total abundance of the sinusoidal efflux transporter, MRP3, and the canalicular efflux transporters, MRP2 and P-gp, was significantly greater (P < 0.05) in SCH versus LT. Of the transporters tested, only the percentage of PMA of OATP1B1, P-gp, and MRP3, in SCH (82.8% ± 7.3%, 57.5% ± 10.9%, 69.3% ± 5.7%) was significantly greater (P < 0.05) than in SH (73.3% ± 6.4%, 27.4% ± 6.4%, 53.6% ± 4.1%). If the transporters measured in the plasma membrane are functional and the PMA in SH is representative of that in LT, these data suggest that SH, PH, and SCH will result in equal prediction of hepatic uptake clearance of drugs mediated by the transporters tested above. However, SCH will predict higher sinusoidal efflux and biliary clearance of drugs if the change in PMA of these transporters is not taken into consideration.

Use of Segregated Hepatocyte Scaling Factors and Cross-Species Relationships to Resolve Clearance Dependence in the Prediction of Human Hepatic Clearance

Human and rat hepatocytes have a strong tendency to underpredict hepatic intrinsic clearance (CLint) and the extent of underprediction increases with increasing observed CLint In this study, application of the log average rat hepatocyte-rat in vivo empirical scaling factor (ESF) of 4.2 to human hepatocyte prediction successfully removed bias but did not improve precision. An analogous method using individual drug rat ESFs only achieved marginal improvement in accuracy but not precision. A novel approach to resolve clearance-dependent prediction, involving rat ESFs calculated for particular (order of magnitude) ranges of observed CLint (log average range, 0.12-2.1) improved human prediction precision but only modestly reduced bias. However, rat in vivo CLint was several-fold greater than human in vivo CLint and this was reflected in greater rat hepatocyte and microsome CLint, suggesting that rat metabolic enzymes are more efficient than their human counterparts, by several-fold. By applying the segregated rat ESFs followed by the human/rat CLint ratio, which was consistent regardless of CLint (log average 3.5), both accuracy and precision were improved, providing both a means of mitigating clearance dependence and reaffirming the potential role of rat hepatocytes for prediction of human metabolic CLint These cross-species observations indicate that underprediction from human in vitro systems may be predominantly consequential of an intrinsic property of the in vitro system rather than individual drug properties.

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.

Quantitative Prediction of Human Hepatic Clearance for P450 and Non-P450 Substrates from In Vivo Monkey Pharmacokinetics Study and In Vitro Metabolic Stability Tests Using Hepatocytes

Accurate prediction of human pharmacokinetics for drugs remains challenging, especially for non-cytochrome P450 (P450) substrates. Hepatocytes might be suitable for predicting hepatic intrinsic clearance (CL_int) of new chemical entities, because they can be applied to various compounds regardless of the metabolic enzymes. However, it was reported that hepatic CL_int is underestimated in hepatocytes. The purpose of the present study was to confirm the predictability of human hepatic clearance for P450 and non-P450 substrates in hepatocytes and the utility of animal scaling factors for the prediction using hepatocytes. CL_int values for 30 substrates of P450, UDP-glucuronosyltransferase, flavin-containing monooxygenase, esterases, reductases, and aldehyde oxidase in human microsomes, human S9 and human, rat, and monkey hepatocytes were estimated. Hepatocytes were incubated in serum of each species. Furthermore, CL_int values in human hepatocytes were corrected with empirical, monkey, and rat scaling factors. CL_int values in hepatocytes for most compounds were underestimated compared to observed values regardless of the metabolic enzyme, and the predictability was improved by using the scaling factors. The prediction using human hepatocytes corrected with monkey scaling factor showed the highest predictability for both P450 and non-P450 substrates among the predictions using liver microsomes, liver S9, and hepatocytes with or without scaling factors. CL_int values by this method for 80% and 90% of all compounds were within 2- and 3-fold of observed values, respectively. This method is accurate and useful for estimating new chemical entities, with no need to care about cofactors, localization of metabolic enzymes, or protein binding in plasma and incubation mixture.

Evaluation and calibration of high-throughput predictions of chemical distribution to tissues

Toxicokinetics (TK) provides critical information for integrating chemical toxicity and exposure assessments in order to determine potential chemical risk (i.e., the margin between toxic doses and plausible exposures). For thousands of chemicals that are present in our environment, in vivo TK data are lacking. The publicly available R package "httk" (version 1.8, named for "high throughput TK") draws from a database of in vitro data and physico-chemical properties in order to run physiologically-based TK (PBTK) models for 553 compounds. The PBTK model parameters include tissue:plasma partition coefficients (Kp) which the httk software predicts using the model of Schmitt (Toxicol In Vitro 22 (2):457-467, 2008). In this paper we evaluated and modified httk predictions, and quantified confidence using in vivo literature data. We used 964 rat Kp measured by in vivo experiments for 143 compounds. Initially, predicted Kp were significantly larger than measured Kp for many lipophilic compounds (log10 octanol:water partition coefficient > 3). Hence the approach for predicting Kp was revised to account for possible deficiencies in the in vitro protein binding assay, and the method for predicting membrane affinity was revised. These changes yielded improvements ranging from a factor of 10 to nearly a factor of 10,000 for 83 Kp across 23 compounds with only 3 Kp worsening by more than a factor of 10. The vast majority (92%) of Kp were predicted within a factor of 10 of the measured value (overall root mean squared error of 0.59 on log10-transformed scale). After applying the adjustments, regressions were performed to calibrate and evaluate the predictions for 12 tissues. Predictions for some tissues (e.g., spleen, bone, gut, lung) were observed to be better than predictions for other tissues (e.g., skin, brain, fat), indicating that confidence in the application of in silico tools to predict chemical partitioning varies depending upon the tissues involved. Our calibrated model was then evaluated using a second data set of human in vivo measurements of volume of distribution (Vss) for 498 compounds reviewed by Obach et al. (Drug Metab Dispos 36(7):1385-1405, 2008). We found that calibration of the model improved performance: a regression of the measured values as a function of the predictions has a slope of 1.03, intercept of - 0.04, and R2 of 0.43. Through careful evaluation of predictive methods for chemical partitioning into tissues, we have improved and calibrated these methods and quantified confidence for TK predictions in humans and rats.

Clearance Prediction Methodology Needs Fundamental Improvement: Trends Common to Rat and Human Hepatocytes/Microsomes and Implications for Experimental Methodology

Although prediction of clearance using hepatocytes and liver microsomes has long played a decisive role in drug discovery, it is widely acknowledged that reliably accurate prediction is not yet achievable despite the predominance of hepatically cleared drugs. Physiologically mechanistic methodology tends to underpredict clearance by several fold, and empirical correction of this bias is confounded by imprecision across drugs. Understanding the causes of prediction uncertainty has been slow, possibly reflecting poor resolution of variables associated with donor source and experimental methods, particularly for the human situation. It has been reported that among published human hepatocyte predictions there was a tendency for underprediction to increase with increasing in vivo intrinsic clearance, suggesting an inherent limitation using this particular system. This implied an artifactual rate limitation in vitro, although preparative effects on cell stability and performance were not yet resolved from assay design limitations. Here, to resolve these issues further, we present an up-to-date and comprehensive examination of predictions from published rat as well as human studies (where n = 128 and 101 hepatocytes and n = 71 and 83 microsomes, respectively) to assess system performance more independently. We report a clear trend of increasing underprediction with increasing in vivo intrinsic clearance, which is similar both between species and between in vitro systems. Hence, prior concerns arising specifically from human in vitro systems may be unfounded and the focus of investigation in the future should be to minimize the potential in vitro assay limitations common to whole cells and subcellular fractions.

An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library

In vitro-in vivo extrapolation (IVIVE) analyses translating high-throughput screening (HTS) data to human relevance have been limited. This study represents the first report applying IVIVE approaches and exposure comparisons using the entirety of the Tox21 federal collaboration chemical screening data, incorporating assay response efficacy and quality of concentration-response fits, and providing quantitative anchoring to first address the likelihood of human in vivo interactions with Tox21 compounds. This likelihood was assessed using a maximum blood concentration to in vitro response ratio approach (C_max/AC₅₀), analogous to decision-making methods for clinical drug-drug interactions. Fraction unbound in plasma (f_up) and intrinsic hepatic clearance (CL_int) parameters were estimated in silico and incorporated in a three-compartment toxicokinetic (TK) model to first predict C_max for in vivo corroboration using therapeutic scenarios. Toward lower exposure scenarios, 36 compounds of 3925 unique chemicals with curated activity in the HTS data using high-quality dose-response model fits and ≥40% efficacy gave "possible" human in vivo interaction likelihoods lower than median human exposures predicted in the United States Environmental Protection Agency's ExpoCast program. A publicly available web application has been designed to provide all Tox21-ToxCast dose-likelihood predictions. Overall, this approach provides an intuitive framework to relate in vitro toxicology data rapidly and quantitatively to exposures using either in vitro or in silico derived TK parameters and can be thought of as an important step toward estimating plausible biological interactions in a high-throughput risk-assessment framework.

Prediction of inter-individual variability on the pharmacokinetics of CYP2C8 substrates in human

Inter-individual variability in pharmacokinetics can lead to unexpected side effects and treatment failure, and is therefore an important factor in drug development. CYP2C8 is a major drug-metabolizing enzyme known to be involved in the metabolism of over 100 drugs. In this study, we predicted the inter-individual variability in AUC/Dose of CYP2C8 substrates in healthy volunteers using the Monte Carlo simulation. Inter-individual variability in the hepatic intrinsic clearance of CYP2C8 substrates (CL_int,h,2C8) was estimated from the inter-individual variability in pharmacokinetics of pioglitazone, which is a major CYP2C8 substrate. The coefficient of variation (CV) of CL_int,h,2C8 was estimated to be 40%. Using this value, the CVs of AUC/Dose of other major CYP2C8 substrates, rosiglitazone and amodiaquine, were predicted to validate the estimated CV of CL_int,h,2C8. As a result, the reported CVs of both substrates were within the 2.5-97.5 percentile range of the predicted CVs. Furthermore, the CVs of AUC/Dose of the CYP2C8 substrates loperamide and chloroquine, which are affected by renal clearance, were also successfully predicted. Combining this value with previously reported CVs of other CYPs, we were able to successfully predict the inter-individual variability in pharmacokinetics of various drugs in clinical.

httk: R Package for High-Throughput Toxicokinetics

Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentrations resulting from chemical exposure, and a "reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput screening. We have created four toxicokinetic models within the R software package httk. These models are designed to be parameterized using high-throughput in vitro data (plasma protein binding and hepatic clearance), as well as structure-derived physicochemical properties and species-specific physiological data. The package contains tools for Monte Carlo sampling and reverse dosimetry along with functions for the analysis of concentration vs. time simulations. The package can currently use human in vitro data to make predictions for 553 chemicals in humans, rats, mice, dogs, and rabbits, including 94 pharmaceuticals and 415 ToxCast chemicals. For 67 of these chemicals, the package includes rat-specific in vitro data. This package is structured to be augmented with additional chemical data as they become available. Package httk enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.

httk: R Package for High-Throughput Toxicokinetics

Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentrations resulting from chemical exposure, and a "reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput screening. We have created four toxicokinetic models within the R software package httk. These models are designed to be parameterized using high-throughput in vitro data (plasma protein binding and hepatic clearance), as well as structure-derived physicochemical properties and species-specific physiological data. The package contains tools for Monte Carlo sampling and reverse dosimetry along with functions for the analysis of concentration vs. time simulations. The package can currently use human in vitro data to make predictions for 553 chemicals in humans, rats, mice, dogs, and rabbits, including 94 pharmaceuticals and 415 ToxCast chemicals. For 67 of these chemicals, the package includes rat-specific in vitro data. This package is structured to be augmented with additional chemical data as they become available. Package httk enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.

Unusual gastrointestinal and cutaneous toxicities by bleomycin, etoposide, and cisplatin: a case report with pharmacogenetic analysis to personalize treatment

The standard treatment of testicular germ cell tumors is based on the combination of bleomycin, etoposide, and cisplatin (PEB). However, this treatment may be associated with severe adverse reactions, such as hematological and non-hematological toxicities. Here, we report a case of a patient suffering from severe PEB-related toxicities, to whom pharmacogenetic analyses were performed, comprising a panel of genes involved in PEB metabolism. The analysis revealed the presence of a complex pattern of polymorphisms in GSTP1, UGT1A1 (TA)6/7, UGT1A7, and ABCB1. The present case shows that a pharmacogenetic approach can help in the management of adverse drug reactions in order to predict, prevent, and personalize treatments.

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

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

Online monitoring of hepatic rat metabolism by coupling a liver biochip and a mass spectrometer

A microfluidic liver biochip was coupled with a mass spectrometer to detect in real time the drug metabolism of hepatocytes.

3D engineered In vitro hepatospheroids for studying drug toxicity and metabolism

Drug toxicity is one of the reasons for late stage drug attrition, because of hepatotoxicity. Various in vitro liver models like primary human hepatocytes, immortalized human hepatic cell lines, liver slices and microsomes have been used; but limited by viability, hepatic gene expression and function. The 3D-engineered construct of hepatocyte-like-cells (HLCs) differentiated from stem cells, may provide a limitless source of hepatocytes with improved reproducibility. Towards this end, we used hepatospheroids (diameter=50-80μm) differentiated from human-umbilical-cord-mesenchymal stem cells (hUC-MSCs) on 3D scaffold GEVAC (Gelatin-vinyl-acetate-copolymer) as in vitro model for studying drug metabolism/toxicity. Our data demonstrated that hUC-MSCs-derived-hepatospheroids cultured on GEVAC expressed significantly higher drug-metabolizing enzymes (CYPs) both at mRNA and activity level compared to 2D culture, using HR-LC/MS. We further showed that hepatospheroids convert phenacetin (by CYP1A2) and testosterone (by CYP3A4) to their human-specific metabolites acetaminophen and 6β-hydroxytestosterone with a predictive clearance rate of 0.011ml/h/10⁶ cells and 0.021ml/h/10⁶ cells respectively, according to first-order kinetics. Hepatotoxicity was confirmed by exposing hepatospheroids to ethanol and acetaminophen; ROS generation, cell viability, cytoskeleton structure, elevation of liver function enzymes, i.e. AST and ALT, was analyzed. To the best of our knowledge, this is the first report to use hUC-MSCs-derived-hepatospheroids on GEVAC as in vitro model for drug metabolism/toxicity study; which can replace the conventional 2D-models used in drug development.

The Use of In Vitro Data and Physiologically-Based Pharmacokinetic Modeling to Predict Drug Metabolite Exposure: Desipramine Exposure in Cytochrome P4502D6 Extensive and Poor Metabolizers Following Administration of Imipramine

Major circulating drug metabolites can be as important as the drugs themselves in efficacy and safety, so establishing methods whereby exposure to major metabolites following administration of parent drug can be predicted is important. In this study, imipramine, a tricyclic antidepressant, and its major metabolite desipramine were selected as a model system to develop metabolite prediction methods. Imipramine undergoes N-demethylation to form the active metabolite desipramine, and both imipramine and desipramine are converted to hydroxylated metabolites by the polymorphic enzyme CYP2D6. The objective of the present study is to determine whether the human pharmacokinetics of desipramine following dosing of imipramine can be predicted using static and dynamic physiologically-based pharmacokinetic (PBPK) models from in vitro input data for CYP2D6 extensive metabolizer (EM) and poor metabolizer (PM) populations. The intrinsic metabolic clearances of parent drug and metabolite were estimated using human liver microsomes (CYP2D6 PM and EM) and hepatocytes. Passive diffusion clearance of desipramine, used in the estimation of availability of the metabolite, was predicted from passive permeability and hepatocyte surface area. The predicted area under the curve (AUCm/AUCp) of desipramine/imipramine was 12- to 20-fold higher in PM compared with EM subjects following i.v. or oral doses of imipramine using the static model. Moreover, the PBPK model was able to recover simultaneously plasma profiles of imipramine and desipramine in populations with different phenotypes of CYP2D6. This example suggested that mechanistic PBPK modeling combined with information obtained from in vitro studies can provide quantitative solutions to predict in vivo pharmacokinetics of drugs and major metabolites in a target human population.

A Pharmacokinetic Modeling Approach to Predict the Contribution of Active Metabolites to Human Efficacious Dose

A preclinical drug candidate, MRK-1 (Merck candidate drug parent compound), was found to elicit tumor regression in a mouse xenograft model. Analysis of samples from these studies revealed significant levels of two circulating metabolites, whose identities were confirmed by comparison with authentic standards using liquid chromatography-tandem mass spectrometry. These metabolites were found to have an in vitro potency similar to that of MRK-1 against the pharmacological target and were therefore thought to contribute to the observed efficacy. To predict this contribution in humans, a pharmacokinetic (PK) modeling approach was developed. At the mouse efficacious dose, the areas under the plasma concentration time curves (AUCs) of the active metabolites were normalized by their in vitro potency compared with MRK-1. These normalized metabolite AUCs were added to that of MRK-1 to yield a composite efficacious unbound AUC, expressed as "parent drug equivalents," which was used as the target AUC for predictions of the human efficacious dose. In vitro and preclinical PK studies afforded predictions of the PK of MRK-1 and the two active metabolites in human as well as the relative pathway flux to each metabolite. These were used to construct a PK model (Berkeley Madonna, version 8.3.18; Berkeley Madonna Inc., University of California, Berkeley, CA) and to predict the human dose required to achieve the target parent equivalent exposure. These predictions were used to inform on the feasibility of the human dose in terms of size, frequency, formulation, and likely safety margins, as well as to aid in the design of preclinical safety studies.

Virtual Experiments Enable Exploring and Challenging Explanatory Mechanisms of Immune-Mediated P450 Down-Regulation

Hepatic cytochrome P450 levels are down-regulated during inflammatory disease states, which can cause changes in downstream drug metabolism and hepatotoxicity. Long-term, we seek sufficient new insight into P450-regulating mechanisms to correctly anticipate how an individual’s P450 expressions will respond when health and/or therapeutic interventions change. To date, improving explanatory mechanistic insight relies on knowledge gleaned from in vitro, in vivo, and clinical experiments augmented by case reports. We are working to improve that reality by developing means to undertake scientifically useful virtual experiments. So doing requires translating an accepted theory of immune system influence on P450 regulation into a computational model, and then challenging the model via in silico experiments. We build upon two existing agent-based models—an in silico hepatocyte culture and an in silico liver—capable of exploring and challenging concrete mechanistic hypotheses. We instantiate an in silico version of this hypothesis: in response to lipopolysaccharide, Kupffer cells down-regulate hepatic P450 levels via inflammatory cytokines, thus leading to a reduction in metabolic capacity. We achieve multiple in vitro and in vivo validation targets gathered from five wet-lab experiments, including a lipopolysaccharide-cytokine dose-response curve, time-course P450 down-regulation, and changes in several different measures of drug clearance spanning three drugs: acetaminophen, antipyrine, and chlorzoxazone. Along the way to achieving validation targets, various aspects of each model are falsified and subsequently refined. This iterative process of falsification-refinement-validation leads to biomimetic yet parsimonious mechanisms, which can provide explanatory insight into how, where, and when various features are generated. We argue that as models such as these are incrementally improved through multiple rounds of mechanistic falsification and validation, we will generate virtual systems that embody deeper credible, actionable, explanatory insight into immune system-drug metabolism interactions within individuals.

Hepatic Clearance Prediction of Nine Human Immunodeficiency Virus Protease Inhibitors in Rat

This study aimed to determine the rate-limiting step in the overall hepatic clearance of the marketed human immunodeficiency virus (HIV) protease inhibitors (PI) in rats by predicting the experimentally determined hepatic in vivo clearance of these drugs based on in vitro clearance values for uptake and/or metabolism. In vitro uptake and metabolic clearance values were determined in suspended rat hepatocytes and rat liver microsomes, respectively. In vivo hepatic clearance was determined after intravenous bolus administration in rats. Excellent in vitro-in vivo correlation (IVIVC; R(2) = 0.80) was observed when metabolic intrinsic Cl values were used, which were determined in vitro at a single concentration corresponding to the blood concentration observed in rats in vivo at the mean residence time. On the contrary, poor IVIVC was observed when in vitro metabolic Cl values based on full Michaelis-Menten profiles were used. In addition, the use of uptake Cl values or a combination of both uptake and metabolic clearance data led to poor predictions of in vivo clearance. Although our findings indicate a key role for metabolism in the hepatic clearance of several HIV PI in rats, subsequent simulations revealed that inhibition of hepatic uptake can lead to altered hepatic clearance for several of these drugs.