Understanding Interindividual Variability in the Drug Interaction of a Highly Extracted CYP1A2 Substrate Tizanidine: Application of a Permeability-Limited Multicompartment Liver Model in a Population Based Physiologically Based Pharmacokinetic Framework.

Tizanidine, a centrally acting skeletal muscle relaxant, is predominantly metabolized by CYP1A2 and undergoes extensive hepatic first-pass metabolism after oral administration. As a highly extracted drug, the systemic exposure to tizanidine exhibits considerable interindividual variability and is altered substantially when coadministered with CYP1A2 inhibitors or inducers. The aim of the current study was to compare the performance of a permeability-limited multicompartment liver (PerMCL) model, which operates as an approximation of the dispersion model, and the well stirred model (WSM) for predicting tizanidine drug-drug interactions (DDIs). Physiologically based pharmacokinetic models were developed for tizanidine, incorporating the PerMCL model and the WSM, respectively, to simulate the interaction of tizanidine with a range of CYP1A2 inhibitors and inducers. Whereas the WSM showed a tendency to underpredict the fold change of tizanidine area under the plasma concentration-time curve (AUC ratio) in the presence of perpetrators, the use of PerMCL model increased precision (absolute average-fold error: 1.32-1.42 versus 1.58) and decreased bias (average-fold error: 0.97-1.25 versus 0.63) for the predictions of mean AUC ratios as compared with the WSM. The PerMCL model captured the observed range of individual AUC ratios of tizanidine as well as the correlation between individual AUC ratios and CYP1A2 activities without interactions, whereas the WSM was not able to capture these. The results demonstrate the advantage of using the PerMCL model over the WSM in predicting the magnitude and interindividual variability of DDIs for a highly extracted sensitive substrate tizanidine. SIGNIFICANCE STATEMENT: This study demonstrates the advantages of the PerMCL model, which operates as an approximation of the dispersion model, in mitigating the tendency of the WSM to underpredict the magnitude and variability of DDIs of a highly extracted CYP1A2 substrate tizanidine when it is administered with CYP1A2 inhibitors or inducers. The physiologically based pharmacokinetic modeling approach described herein is valuable to the understanding of drug interactions of highly extracted substrates and the source of its interindividual variability.

Multistate models of developmental toxicity: Application to valproic acid-induced malformations in the zebrafish embryo.

For the determination of acute toxicity of chemicals in zebrafish (Danio rerio) embryos, the OECD test guideline 236, relative to the Fish Embryo Toxicity Test (FET), stipulates a dose-response analysis of four lethal core endpoints and a quantitative characterization of abnormalities including their time-dependency. Routinely, the data are analyzed at the different observation times separately. However, observations at a given time strongly depend on the previous effects and should be analyzed jointly with them. To solve this problem, we developed multistate models for occurrence of developmental malformations and live events in zebrafish embryos exposed to eight concentrations of valproic acid (VPA) the first five days of life. Observations were recorded daily per embryo. We statistically infer on model structure and parameters using a numerical Bayesian framework. Hatching probability rate changed with time and we compared five forms of its time-dependence; a constant rate, a piecewise constant rate with a fixed hatching time at 48 h post fertilization, a piecewise constant rate with a variable hatching time, as well as a Hill and Gaussian form. A piecewise constant function of time adequately described the hatching data. The other transition rates were conditioned on the embryo body concentration of VPA, obtained using a physiologically-based pharmacokinetic model. VPA impacted mostly the malformation probability rate in hatched and non-hatched embryos. Malformation reversion probability rates were lowered by VPA. Direct mortality was low at the concentrations tested, but increased linearly with internal concentration. The model makes full use of data and gives a finer grain analysis of the teratogenic effects of VPA in zebrafish than the OECD-prescribed approach. We discuss the use of the model for obtaining toxicological reference values suitable for inter-species extrapolation. A general result is that complex multistate models can be efficiently evaluated numerically.

A Bayesian population physiologically based pharmacokinetic absorption modeling approach to support generic drug development: application to bupropion hydrochloride oral dosage forms.

We propose a Bayesian population modeling and virtual bioequivalence assessment approach to establishing dissolution specifications for oral dosage forms. A generalizable semi-physiologically based pharmacokinetic absorption model with six gut segments and liver, connected to a two-compartment model of systemic disposition for bupropion hydrochloride oral dosage forms was developed. Prior information on model parameters for gut physiology, bupropion physicochemical properties, and drug product properties were obtained from the literature. The release of bupropion hydrochloride from immediate-, sustained- and extended-release oral dosage forms was described by a Weibull function. In vitro dissolution data were used to assign priors to the in vivo release properties of the three bupropion formulations. We applied global sensitivity analysis to identify the influential parameters for plasma bupropion concentrations and calibrated them. To quantify inter- and intra-individual variability, plasma concentration profiles in healthy volunteers that received the three dosage forms, each at two doses, were used. The calibrated model was in good agreement with both in vitro dissolution and in vivo exposure data. Markov Chain Monte Carlo samples from the joint posterior parameter distribution were used to simulate virtual crossover clinical trials for each formulation with distinct drug dissolution profiles. For each trial, an allowable range of dissolution parameters ("safe space") in which bioequivalence can be anticipated was established. These findings can be used to assure consistent product performance throughout the drug product life-cycle and to support manufacturing changes. Our framework provides a comprehensive approach to support decision-making in drug product development.

Well-tempered MCMC simulations for population pharmacokinetic models.

A full Bayesian statistical treatment of complex pharmacokinetic or pharmacodynamic models, in particular in a population context, gives access to powerful inference, including on model structure. Markov Chain Monte Carlo (MCMC) samplers are typically used to estimate the joint posterior parameter distribution of interest. Among MCMC samplers, the simulated tempering algorithm (TMCMC) has a number of advantages: it can sample from sharp multi-modal posteriors; it provides insight into identifiability issues useful for model simplification; it can be used to compute accurate Bayes factors for model choice; the simulated Markov chains mix quickly and have assured convergence in certain conditions. The main challenge when implementing this approach is to find an adequate scale of auxiliary inverse temperatures (perks) and associated scaling constants. We solved that problem by adaptive stochastic optimization and describe our implementation of TMCMC sampling in the GNU MCSim software. Once a grid of perks is obtained, it is easy to perform posterior-tempered MCMC sampling or likelihood-tempered MCMC (thermodynamic integration, which bridges the joint prior and the posterior parameter distributions, with assured convergence of a single sampling chain). We compare TMCMC to other samplers and demonstrate its efficient sampling of multi-modal posteriors and calculation of Bayes factors in two stylized case-studies and two realistic population pharmacokinetic inference problems, one of them involving a large PBPK model.

Prediction of maternal and foetal exposures to perfluoroalkyl compounds in a Spanish birth cohort using toxicokinetic modelling.

Prenatal exposures to perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) have been associated with child health outcomes, but many of these associations remain poorly characterized. The aim of this work was to provide new indicators of foetal exposure for the Spanish INMA birth cohort. First, a pregnancy and lactation physiologically based pharmacokinetic (PBPK) model was calibrated in a population framework to provide quantitative estimates for the PFOA and PFOS placental transfers in humans. The estimated distributions indicated that PFOA crosses the placental barrier at a rate three times higher than PFOS and shows a higher variability between mothers. The PBPK model was then used to back-calculate the time-varying daily intakes of the INMA mothers corrected for their individual history from a spot maternal concentration. We showed the importance of accounting for the mothers' history as different dietary intakes can result in similar measured concentrations at one time point. Finally, the foetal exposure was simulated in target organs over pregnancy using the PBPK model and the estimated maternal intakes. We showed that the pattern of PFOA and PFOS exposures varies greatly among the foetuses. About a third has levels of either one compound always higher than the levels of the other compound. The other two thirds showed different ranking of PFOA and PFOS in terms of concentrations in the target organs. Our simulated foetal exposures bring additional information to the measured maternal spot concentrations and can help to better characterize the prenatal exposure in target organs during windows of susceptibility.

Population pharmacokinetic reanalysis of a Diazepam PBPK model: a comparison of Stan and GNU MCSim.

The aim of this study is to benchmark two Bayesian software tools, namely Stan and GNU MCSim, that use different Markov chain Monte Carlo (MCMC) methods for the estimation of physiologically based pharmacokinetic (PBPK) model parameters. The software tools were applied and compared on the problem of updating the parameters of a Diazepam PBPK model, using time-concentration human data. Both tools produced very good fits at the individual and population levels, despite the fact that GNU MCSim is not able to consider multivariate distributions. Stan outperformed GNU MCSim in sampling efficiency, due to its almost uncorrelated sampling. However, GNU MCSim exhibited much faster convergence and performed better in terms of effective samples produced per unit of time.

The Search for a Subtype-Selective PET Imaging Agent for the GABAA Receptor Complex: Evaluation of the Radiotracer [11C]ADO in Nonhuman Primates.

The myriad physiological functions of γ-amino butyric acid (GABA) are mediated by the GABA-benzodiazepine receptor complex comprising of the GABAA, GABAB, and GABAC groups. The various GABAA subunits with region-specific distributions in the brain subserve different functional and physiological roles. For example, the sedative and anticonvulsive effects of classical benzodiazepines are attributed to the α1 subunit, and the α2 and α3 subunits mediate the anxiolytic effect. To optimize pharmacotherapies with improved efficacy and devoid of undesirable side effects for the treatment of anxiety disorders, subtype-selective imaging radiotracers are required to assess target engagement at GABA sites and determine the dose-receptor occupancy relationships. The goal of this work was to characterize, in nonhuman primates, the in vivo binding profile of a novel positron emission tomography (PET) radiotracer, [11C]ADO, which has been indicated to have functional selectivity for the GABAA α2/α3 subunits. High specific activity [11C]ADO was administrated to 3 rhesus monkeys, and PET scans of 120-minute duration were performed on the Focus-220 scanner. In the blood, [11C]ADO metabolized at a fairly rapid rate, with ∼36% of the parent tracer remaining at 30 minutes postinjection. Uptake levels of [11C]ADO in the brain were high (peak standardized uptake value of ∼3.0) and consistent with GABAA distribution, with highest activity levels in cortical areas, intermediate levels in cerebellum and thalamus, and lowest uptake in striatal regions and amygdala. Tissue kinetics was fast, with peak uptake in all brain regions within 20 minutes of tracer injection. The one-tissue compartment model provided good fits to regional time-activity curves and reliable measurement of kinetic parameters. The absolute test-retest variability of regional distribution volumes ( VT) was low, ranging from 4.5% to 8.7%. Pretreatment with flumazenil (a subtype nonselective ligand, 0.2 mg/kg, intravenous [IV], n = 1), Ro15-4513 (an α5-selective ligand, 0.03 mg/kg, IV, n = 2), and zolpidem (an α1-selective ligand, 1.7 mg/kg, IV, n = 1) led to blockade of [11C]ADO binding by 96.5%, 52.5%, and 76.5%, respectively, indicating the in vivo binding specificity of the radiotracer. Using the nondisplaceable volume of distribution ( VND) determined from the blocking studies, specific binding signals, as measured by values of regional binding potential ( BPND), ranged from 0.6 to 4.4, which are comparable to those of [11C]flumazenil. In conclusion, [11C]ADO was demonstrated to be a specific radiotracer for the GABAA receptors with several favorable properties: high brain uptake, fast tissue kinetics, and high levels of specific binding in nonhuman primates. However, subtype selectivity in vivo is not obvious for the radiotracer, and thus, the search for subtype-selective GABAA radiotracers continues.

Adverse outcome pathways: opportunities, limitations and open questions.

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field.

Tobacco smoking interferes with GABAA receptor neuroadaptations during prolonged alcohol withdrawal.

Understanding the effects of tobacco smoking on neuroadaptations in GABAA receptor levels over alcohol withdrawal will provide critical insights for the treatment of comorbid alcohol and nicotine dependence. We conducted parallel studies in human subjects and nonhuman primates to investigate the differential effects of tobacco smoking and nicotine on changes in GABAA receptor availability during acute and prolonged alcohol withdrawal. We report that alcohol withdrawal with or without concurrent tobacco smoking/nicotine consumption resulted in significant and robust elevations in GABAA receptor levels over the first week of withdrawal. Over prolonged withdrawal, GABAA receptors returned to control levels in alcohol-dependent nonsmokers, but alcohol-dependent smokers had significant and sustained elevations in GABAA receptors that were associated with craving for alcohol and cigarettes. In nonhuman primates, GABAA receptor levels normalized by 1 mo of abstinence in both groups--that is, those that consumed alcohol alone or the combination of alcohol and nicotine. These data suggest that constituents in tobacco smoke other than nicotine block the recovery of GABAA receptor systems during sustained alcohol abstinence, contributing to alcohol relapse and the perpetuation of smoking.

CHRNA4 and ANKK1 Polymorphisms Influence Smoking-Induced Nicotinic Acetylcholine Receptor Upregulation.

INTRODUCTION: Tobacco smoking leads to increased numbers of ß2*-containing nicotinic acetylcholine receptors (ß2*-nAChRs) throughout the brain, which return to nonsmoker levels over extended abstinence. The goal of the current study was to determine whether the degree of tobacco smoking-induced changes in ß2*-nAChR availability is genetically influenced. METHODS: In this study, 113 European Americans participated in one or two [(123)I]5-IA-85380 single photon emission computed tomography (SPECT) brain scans. Smokers (n = 58) participated in one scan at 7-9 days of abstinence and those who remained abstinent (n = 27) were imaged again at 6-8 weeks of abstinence. Age- and sex-matched nonsmokers (n = 55) participated in one scan. Blood samples were collected for DNA analysis and genotyped for single nucleotide polymorphisms (SNPs) in the CHRNA4 and ANKK1 gene loci. ß2*-nAChR availability was measured in the thalamus, striatum, cortical regions, and cerebellum. RESULTS: The CHRNA4 SNP rs2236196 and ANKK1 SNP rs4938015 were associated with significantly higher cerebellar and cortical ß2*-nAChR availability in smokers versus nonsmokers for specific genotypes. There were no significant differences by carrier status in the change in ß2*-nAChR availability in smokers from 7-9 days to 6-8 weeks of abstinence. CONCLUSION: This study provides evidence for genetic regulation of tobacco smoking-induced changes in ß2*-nAChR availability and suggests that ß2*-nAChR availability could be an endophenotype mediating influences of CHRNA4 variants on nicotine dependence. These results highlight individual differences in the neurochemistry of nicotine dependence and may suggest the need for individualized programs for smoking cessation. IMPLICATIONS: This study demonstrates genetic regulation of smoking-induced changes in ß2*-nAChRs throughout the brain and highlights the need for personalized programs for smoking cessation.

Investigation of ifosfamide and chloroacetaldehyde renal toxicity through integration of in vitro liver-kidney microfluidic data and pharmacokinetic-system biology models.

We have integrated in vitro and in silico data to describe the toxicity of chloroacetaldehyde (CAA) on renal cells via its production from the metabolism of ifosfamide (IFO) by hepatic cells. A pharmacokinetic (PK) model described the production of CAA by the hepatocytes and its transport to the renal cells. A system biology model was coupled to the PK model to describe the production of reactive oxygen species (ROS) induced by CAA in the renal cells. In response to the ROS production, the metabolism of glutathione (GSH) and its depletion were modeled by the action of an NFE2L2 gene-dependent pathway. The model parameters were estimated in a Bayesian context via Markov Chain Monte Carlo (MCMC) simulations based on microfluidic experiments and literature in vitro data. Hepatic IFO and CAA in vitro intrinsic clearances were estimated to be 1.85 x 10(-9) µL s(-1) cell(-1) and 0.185 x 10(-9) µL s(-1) cell(-1) ,respectively (corresponding to an in vivo intrinsic IFO clearance estimate of 1.23 l h(-1) , to be compared to IFO published values ranging from 3 to 10 l h(-1) ). After model calibration, simulations made at therapeutic doses of IFO showed CAA renal intracellular concentrations ranging from 11 to 131 µM. Intracellular CAA concentrations above 70 µM induced intense ROS production and GSH depletion. Those responses were time and dose dependent, showing transient and non-linear kinetics. Those results are in agreement with literature data reporting that intracellular CAA toxic concentrations range from 35 to 320 µM, after therapeutic ifosfamide dosing. The results were also consistent with in vitro CAA renal cytotoxicity data.

Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group.

Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.

Investigation of acetaminophen toxicity in HepG2/C3a microscale cultures using a system biology model of glutathione depletion.

We have integrated in vitro and in silico information to investigate acetaminophen (APAP) and its metabolite N-acetyl-p-benzoquinone imine (NAPQI) toxicity in liver biochip. In previous works, we observed higher cytotoxicity of HepG2/C3a cultivated in biochips when exposed to 1 mM of APAP for 72 h as compared to Petri cultures. We complete our investigation with the present in silico approach to extend the mechanistic interpretation of the intracellular kinetics of the toxicity process. For that purpose, we propose a mathematical model based on the coupling of a drug pharmacokinetic model (PK) with a systemic biology model (SB) describing the reactive oxygen species (ROS) production by NAPQI and the subsequent glutathione (GSH) depletion. The SB model was parameterized using (i) transcriptomic data, (ii) qualitative results of time lapses ROS fluorescent curves for both control and 1-mM APAP-treated experiments, and (iii) additional GSH literature data. The PK model was parameterized (i) using the in vitro kinetic data (at 160 µM, 1 mM, 10 mM), (ii) using the parameters resulting from a physiologically based pharmacokinetic (PBPK) literature model for APAP, and (iii) by literature data describing NAPQI formation. The PK-SB model predicted a ROS increase and GSH depletion due to the NAPQI formation. The transition from a detoxification phase and NAPQI and ROS accumulation was predicted for a NAPQI concentration ranging between 0.025 and 0.25 µM in the cytosol. In parallel, we performed a dose response analysis in biochips that shows a reduction of the final hepatic cell number appeared in agreement with the time and doses associated with the switch of the NAPQI detoxification/accumulation. As a result, we were able to correlate in vitro extracellular APAP exposures with an intracellular in silico ROS accumulation using an integration of a coupled mathematical and experimental liver on chip approach.

Investigation of omeprazole and phenacetin first-pass metabolism in humans using a microscale bioreactor and pharmacokinetic models.

A new in vitro microfluidic platform (integrated insert dynamic microfluidic platform, IIDMP) allowing the co-culture of intestinal Caco-2 TC7 cells and of human primary hepatocytes was used to test the absorption and first-pass metabolism of two drugs: phenacetin and omeprazole. The metabolism of these drugs by CYP1A2, CYP2C19 and CYP3A4 was evaluated by the calculation of bioavailabilities and of intrinsic clearances using a pharmacokinetic (PK) model. To demonstrate the usefulness of the device and of the PK model, predictions were compared with in vitro and in vivo results from the literature. Based on the IIDMP experiments, hepatic in vivo clearances of phenacetin and omeprazole in the IIDMP were predicted to be 3.10 ± 0.36 and 1.46 ± 0.25 ml/min/kg body weight, respectively. This appeared lower than the in vivo observed data with values ranging between 11.9-19.6 and 5.8-7.5 ml/min/kg body weight, respectively. Then the calculated hepatic and intestinal clearances led to predicting an oral bioavailability of 0.85 and 0.77 for phenacetin and omeprazole versus 0.92 and 0.78 using separate data from the simple monoculture of Caco-2 TC7 cells and hepatocytes in Petri dishes. When compared with the in vivo data, the results of oral bioavailability were overestimated (0.37 and 0.71, respectively). The feasibility of co-culture in a device allowing the integration of intestinal absorption, intestinal metabolism and hepatic metabolism in a single model was demonstrated. Nevertheless, further experiments with other drugs are needed to extend knowledge of the device to predict oral bioavailability and intestinal first-pass metabolism.

Evaluation of the sensitivity of the novel α4ß2* nicotinic acetylcholine receptor PET radioligand 18F-(-)-NCFHEB to increases in synaptic acetylcholine levels in rhesus monkeys.

OBJECTIVE: 18F-(-)-NCFHEB (also known as 18F-(-)-Flubatine) is a new radioligand to image α4ß2* nicotinic acetylcholine receptors in vivo with positron emission tomography (PET), with faster kinetics than previous radioligands such as 18F-2-F-A85380. The goal of this study was to assess the sensitivity of 18F-(-)-NCFHEB-PET to increases in synaptic acetylcholine concentration induced by acetylcholinesterase inhibitors. METHODS: Two rhesus monkeys were scanned four times each on a Focus 220 scanner: first at baseline, then during two bolus plus infusions of physostigmine (0.06-0.28 mg/kg), and finally following a bolus injection of donepezil (0.25 mg/kg). The arterial input function and the plasma free fraction fP were measured. 18F-(-)-NCFHEB volume of distribution VT was estimated using the multilinear analysis MA1 and then normalized by plasma free fraction fP . RESULTS: 18F-(-)-NCFHEB fP was 0.89±0.04. At baseline, 18F-(-)-NCFHEB VT /fP ranged from 7.9±1.3 mL plasma/cm3 tissue in the cerebellum to 34.3±8.4 mL plasma/cm3 tissue in the thalamus. Physostigmine induced a dose-dependent reduction of 18F-(-)-NCFHEB VT /fP of 34±9% in the putamen, 32±8% in the thalamus, 25±8% in the cortex, and 23±10% in the hippocampus. With donepezil, 18F-(-)-NCFHEB VT /fP was reduced by 24±2%, 14+3% and 14±5%, 10±6% in the same regions. CONCLUSION: 18F-(-)-NCFHEB can be used to detect changes in synaptic acetylcholine concentration and is a promising tracer to study acetylcholine dynamics with shorter scan durations than previous radioligands.

First pass intestinal and liver metabolism of paracetamol in a microfluidic platform coupled with a mathematical modeling as a means of evaluating ADME processes in humans.

We developed a microfluidic platform to investigate paracetamol intestinal and liver first pass metabolism. This approach was coupled with a mathematical model to estimate intrinsic in vitro parameters and to predict in vivo processes. The kinetic modeling estimated the paracetamol and paracetamol sulfate permeabilities, the sulfate and glucuronide effluxes in the intestine compartment. Based on a gut model, we estimated intrinsic intestinal clearance of between 26 and 77 L/h for paracetamol in humans, a permeability of 10 L/h, and a gut availability between 0.17 and 0.53 (compared to 0.95-1 in vivo). The role played by the liver in paracetamol metabolism was estimated via in vitro intrinsic clearances of 7.6, 13.6, and 11.5 µL/min/10(6) cells for HepG2/C3a, rat primary hepatocytes, and human primary hepatocytes, respectively. Based on a parallel tube model to describe the liver, the paracetamol hepatic clearance, and the paracetamol hepatic availability in humans were estimated at 6.5 mL/min/kg of bodyweight (BDW) and 0.7, respectively (when compared to 5 mL/min/kg of BDW and 0.77 to 0.88 for in vivo values, respectively). The drug availability was predicted ranging between 0.24 and 0.41 (0.88 in vivo). The overall approach provided a first step in an integrated strategy combining in silico/in vitro methods based on microfluidic for evaluating drug absorption, distribution and metabolism processes.

PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA--EURL ECVAM ADME workshop.

Information on toxicokinetics is critical for animal-free human risk assessment. Human external exposure must be translated into human tissue doses and compared with in vitro actual cell exposure associated to effects (in vitro-in vivo comparison). Data on absorption, distribution, metabolism and excretion in humans (ADME) could be generated using in vitro and QSAR tools. Physiologically-based toxicokinetic (PBTK) computer modelling could serve to integrate disparate in vitro and in silico findings. However, there are only few freely-available PBTK platforms currently available. And although some ADME parameters can be reasonably estimated in vitro or in silico, important gaps exist. Examples include unknown or limited applicability domains and lack of (high-throughput) tools to measure penetration of barriers, partitioning between blood and tissues and metabolic clearance. This paper is based on a joint EPAA--EURL ECVAM expert meeting. It provides a state-of-the-art overview of the availability of PBTK platforms as well as the in vitro and in silico methods to parameterise basic (Tier 1) PBTK models. Five high-priority issues are presented that provide the prerequisites for wider use of non-animal based PBTK modelling for animal-free chemical risk assessment.

A Bayesian framework for virtual comparative trials and bioequivalence assessments.

Introduction: In virtual bioequivalence (VBE) assessments, pharmacokinetic models informed with in vitro data and verified with small clinical trials' data are used to simulate otherwise unfeasibly large trials. Simulated VBE trials are assessed in a frequentist framework as if they were real despite the unlimited number of virtual subjects they can use. This may adequately control consumer risk but imposes unnecessary risks on producers. We propose a fully Bayesian model-integrated VBE assessment framework that circumvents these limitations. Methods: We illustrate our approach with a case study on a hypothetical paliperidone palmitate (PP) generic long-acting injectable suspension formulation using a validated population pharmacokinetic model published for the reference formulation. BE testing, study power, type I and type II error analyses or their Bayesian equivalents, and safe-space analyses are demonstrated. Results: The fully Bayesian workflow is more precise than the frequentist workflow. Decisions about bioequivalence and safe space analyses in the two workflows can differ markedly because the Bayesian analyses are more accurate. Discussion: A Bayesian framework can adequately control consumer risk and minimize producer risk . It rewards data gathering and model integration to make the best use of prior information. The frequentist approach is less precise but faster to compute, and it can still be used as a first step to narrow down the parameter space to explore in safe-space analyses.

A guide to developing population files for physiologically-based pharmacokinetic modeling in the Simcyp Simulator.

The Simcyp Simulator is a software platform widely used in the pharmaceutical industry to conduct stochastic physiologically-based pharmacokinetic (PBPK) modeling. This approach has the advantage of combining routinely generated in vitro data on drugs and drug products with knowledge of biology and physiology parameters to predict a priori potential pharmacokinetic changes in absorption, distribution, metabolism, and excretion for populations of interest. Combining such information with pharmacodynamic knowledge of drugs enables planning for potential dosage adjustment when clinical studies are feasible. Although the conduct of dedicated clinical studies in some patient groups (e.g., with hepatic or renal diseases) is part of the regulatory path for drug development, clinical studies for all permutations of covariates potentially affecting pharmacokinetics are impossible to perform. The role of PBPK in filling the latter gap is becoming more appreciated. This tutorial describes the different input parameters required for the creation of a virtual population giving robust predictions of likely changes in pharmacokinetics. It also highlights the considerations needed to qualify the models for such contexts of use. Two case studies showing the step-by-step development and application of population files for obese or morbidly obese patients and individuals with Crohn's disease are provided as the backbone of our tutorial to give some hands-on and real-world examples.

Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.

BACKGROUND: Understanding the variability across the human population with respect to toxicodynamic responses after exposure to chemicals, such as environmental toxicants or drugs, is essential to define safety factors for risk assessment to protect the entire population. Activation of cellular stress response pathways are early adverse outcome pathway (AOP) key events of chemical-induced toxicity and would elucidate the estimation of population variability of toxicodynamic responses. OBJECTIVES: We aimed to map the variability in cellular stress response activation in a large panel of primary human hepatocyte (PHH) donors to aid in the quantification of toxicodynamic interindividual variability to derive safety uncertainty factors. METHODS: High-throughput transcriptomics of over 8,000 samples in total was performed covering a panel of 50 individual PHH donors upon 8 to 24 h exposure to broad concentration ranges of four different toxicological relevant stimuli: tunicamycin for the unfolded protein response (UPR), diethyl maleate for the oxidative stress response (OSR), cisplatin for the DNA damage response (DDR), and tumor necrosis factor alpha (TNFα) for NF-κB signaling. Using a population mixed-effect framework, the distribution of benchmark concentrations (BMCs) and maximum fold change were modeled to evaluate the influence of PHH donor panel size on the correct estimation of interindividual variability for the various stimuli. RESULTS: Transcriptome mapping allowed the investigation of the interindividual variability in concentration-dependent stress response activation, where the average of BMCs had a maximum difference of 864-, 13-, 13-, and 259-fold between different PHHs for UPR, OSR, DDR, and NF-κB signaling-related genes, respectively. Population modeling revealed that small PHH panel sizes systematically underestimated the variance and gave low probabilities in estimating the correct human population variance. Estimated toxicodynamic variability factors of stress response activation in PHHs based on this dataset ranged between 1.6 and 6.3. DISCUSSION: Overall, by combining high-throughput transcriptomics and population modeling, improved understanding of interindividual variability in chemical-induced activation of toxicity relevant stress pathways across the human population using a large panel of plated cryopreserved PHHs was established, thereby contributing toward increasing the confidence of in vitro-based prediction of adverse responses, in particular hepatotoxicity. https://doi.org/10.1289/EHP11891.