Quantitativein vitrotoin vivoextrapolation of cell-based toxicity assay results

Pluripotent stem cells: An in vitro model for nanotoxicity assessments

The advent of technology has led to an established range of engineered nanoparticles that are used in diverse applications, such as cell-cell interactions, cell-material interactions, medical therapies and the target modulation of cellular processes. The exponential increase in the utilization of nanomaterials and the growing number of associated criticisms has highlighted the potential risks of nanomaterials to human health and the ecosystem. The existing in vivo and in vitro platforms show limitations, with fluctuations being observed in the results of toxicity assessments. Pluripotent stem cells (PSCs) are viable source of cells that are capable of developing into specialized cells of the human body. PSCs can be efficiently used to screen new biomaterials/drugs and are potential candidates for studying impairments of biophysical morphology at both the cellular and tissue levels during interactions with nanomaterials and for diagnosing toxicity. Three-dimensional in vitro models obtained using PSC-derived cells would provide a realistic, patient-specific platform for toxicity assessments and in drug screening applications. The current review focuses on PSCs as an alternative in vitro platform for assessing the hazardous effects of nanomaterials on health systems and highlights the importance of PSC-derived in vitro platforms. Copyright © 2016 John Wiley & Sons, Ltd.

In vitro assays in natural products research - a matter of concentration and relevance to in vivo administration using resveratrol, α-mangostin/γ-mangostin and xanthohumol as examples

Herbal or botanical dietary supplements are an ever increasingly popular category of products in the United States and around the world. In vitro data can provide meaningful insight into the potential target and mechanism of action for a proposed active compound but may also be misused to promote a supplement to consumers with unverified health claims. In vitro data need to be considered alongside pharmacokinetic and pharmacodynamic data in preclinical animal and clinical human trials. While considerable activity of compounds and extracts in vitro may lead to further testing in vivo, in many instances, concentrations tested in cell lines or isolated targets are not achievable at the target site in vivo. Thus, whether the in vitro data are relevant to humans after oral administration is questionable. This review will discuss this discrepancy using in vitro and in vivo data of resveratrol, xanthones (α-mangostin and γ-mangostin) and xanthohumol.

An integrative test strategy for cancer hazard identification

Assessment of genotoxic and carcinogenic potential is considered one of the basic requirements when evaluating possible human health risks associated with exposure to chemicals. Test strategies currently in place focus primarily on identifying genotoxic potential due to the strong association between the accumulation of genetic damage and cancer. Using genotoxicity assays to predict carcinogenic potential has the significant drawback that risks from non-genotoxic carcinogens remain largely undetected unless carcinogenicity studies are performed. Furthermore, test systems already developed to reduce animal use are not easily accepted and implemented by either industries or regulators. This manuscript reviews the test methods for cancer hazard identification that have been adopted by the regulatory authorities, and discusses the most promising alternative methods that have been developed to date. Based on these findings, a generally applicable tiered test strategy is proposed that can be considered capable of detecting both genotoxic as well as non-genotoxic carcinogens and will improve understanding of the underlying mode of action. Finally, strengths and weaknesses of this new integrative test strategy for cancer hazard identification are presented.

Considering new methodologies in strategies for safety assessment of foods and food ingredients

Toxicology and safety assessment are changing and require new strategies for evaluating risk that are less depending on apical toxicity endpoints in animal models and relying more on knowledge of the mechanism of toxicity. This manuscript describes a number of developments that could contribute to this change and implement this in a stepwise roadmap that can be applied for the evaluation of food and food ingredients. The roadmap was evaluated in four case studies by using literature and existing data. This preliminary evaluation was shown to be useful. However, this experience should be extended by including examples where experimental work needs to be included. To further implement these new insights in toxicology and safety assessment for the area of food and food ingredients, the recommendation is that stakeholders take action in addressing gaps in our knowledge, e.g. with regard to the applicability of the roadmap for mixtures and food matrices. Further development of the threshold of toxicological concern is needed, as well as cooperation with other sectors where similar schemes are under development. Moreover, a more comprehensive evaluation of the roadmap, also including the identification of the need for in vitro experimental work is recommended.

Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems

Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice.

Addressing Early Life Sensitivity Using Physiologically Based Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation

Physiologically based pharmacokinetic (PBPK) modeling can provide an effective way to utilize in vitro and in silico based information in modern risk assessment for children and other potentially sensitive populations. In this review, we describe the process of in vitro to in vivo extrapolation (IVIVE) to develop PBPK models for a chemical in different ages in order to predict the target tissue exposure at the age of concern in humans. We present our on-going studies on pyrethroids as a proof of concept to guide the readers through the IVIVE steps using the metabolism data collected either from age-specific liver donors or expressed enzymes in conjunction with enzyme ontogeny information to provide age-appropriate metabolism parameters in the PBPK model in the rat and human, respectively. The approach we present here is readily applicable to not just to other pyrethroids, but also to other environmental chemicals and drugs. Establishment of an in vitro and in silico-based evaluation strategy in conjunction with relevant exposure information in humans is of great importance in risk assessment for potentially vulnerable populations like early ages where the necessary information for decision making is limited.

The Role of Extracellular Binding Proteins in the Cellular Uptake of Drugs: Impact on Quantitative In Vitro-to-In Vivo Extrapolations of Toxicity and Efficacy in Physiologically Based Pharmacokinetic-Pharmacodynamic Research

A critical component in the development of physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) models for estimating target organ dosimetry in pharmacology and toxicology studies is the understanding of the uptake kinetics and accumulation of drugs and chemicals at the cellular level. Therefore, predicting free drug concentrations in intracellular fluid will contribute to our understanding of concentrations at the site of action in cells in PBPK/PD research. Some investigators believe that uptake of drugs in cells is solely driven by the unbound fraction; conversely, others argue that the protein-bound fraction contributes a significant portion of the total amount delivered to cells. Accordingly, the current literature suggests the existence of a so-called albumin-mediated uptake mechanism(s) for the protein-bound fraction (i.e., extracellular protein-facilitated uptake mechanisms) at least in hepatocytes and cardiac myocytes; however, such mechanism(s) and cells from other organs deserve further exploration. Therefore, the main objective of this present study was to discuss further the implication of potential protein-facilitated uptake mechanism(s) on drug distribution in cells under in vivo conditions. The interplay between the protein-facilitated uptake mechanism(s) and the effects of a pH gradient, metabolism, transport, and permeation limitation potentially occurring in cells was also discussed, as this should violate the basic assumption on similar free drug concentration in cells and plasma. This was made because the published equations used to calculate drug concentrations in cells in a PBPK/PD model did not consider potential protein-facilitated uptake mechanism(s). Consequently, we corrected some published equations for calculating the free drug concentrations in cells compared with plasma in PBPK/PD modeling studies, and we proposed a refined strategy for potentially performing more accurate quantitative in vitro-to-in vivo extrapolations (IVIVEs) of toxicity (efficacy) at the cellular level from data generated in cell assays. Overall, this present study may help to optimize the human dose prediction in preclinical and clinical studies, while prescribing drugs with narrow therapeutic windows that are highly bound to extracellular proteins and/or highly ionized at the physiological pH. This may facilitate building a more accurate safety (efficacy) profile for such drugs.

In Silico Models for Ecotoxicity of Pharmaceuticals

Pharmaceuticals and their active metabolites are one of the significantly emerging environmental toxicants. The major routes of entry of pharmaceuticals into the environment are industries, hospitals, or direct disposal of unwanted or expired drugs made by the patient. The most important and distinct features of pharmaceuticals are that they are deliberately designed to have an explicit mode of action and designed to exert an effect on humans and other living systems. This distinctive feature makes pharmaceuticals and their metabolites different from other chemicals, and this necessitates the evaluation of the direct effects of pharmaceuticals in various environmental compartments as well as to living systems. In this background, the alarming situation of ecotoxicity of diverse pharmaceuticals have forced government and nongovernment regulatory authorities to recommend the application of in silico methods to provide quick information about the risk assessment and fate properties of pharmaceuticals as well as their ecological and indirect human health effects. This chapter aims to offer information regarding occurrence of pharmaceuticals in the environment, their persistence, environmental fate, and toxicity as well as application of in silico methods to provide information about the basic risk management and fate prediction of pharmaceuticals in the environment. Brief ideas about toxicity endpoints, available ecotoxicity databases, and expert systems employed for rapid toxicity predictions of ecotoxicity of pharmaceuticals are also discussed.

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

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

Empirical analysis of BMD metrics in genetic toxicology part I: in vitro analyses to provide robust potency rankings and support MOA determinations

Genetic toxicity testing has traditionally been used for hazard identification, with dichotomous classification of test results serving to identify genotoxic agents. However, the utility of genotoxicity data can be augmented by employing dose-response analysis and point of departure determination. Via interpolation from a fitted dose-response model, the benchmark dose (BMD) approach estimates the dose that elicits a specified (small) effect size. BMD metrics and their confidence intervals can be used for compound potency ranking within an endpoint, as well as potency comparisons across other factors such as cell line or exposure duration. A recently developed computational method, the BMD covariate approach, permits combined analysis of multiple dose-response data sets that are differentiated by covariates such as compound, cell type or exposure regime. The approach provides increased BMD precision for effective potency rankings across compounds and other covariates that pertain to a hypothesised mode of action (MOA). To illustrate these applications, the covariate approach was applied to the analysis of published in vitro micronucleus frequency dose-response data for ionising radiations, a set of aneugens, two mutagenic azo compounds and a topoisomerase II inhibitor. The ionising radiation results show that the precision of BMD estimates can be improved by employing the covariate method. The aneugen analysis provided potency groupings based on the BMD confidence intervals, and analyses of azo compound data from cells lines with differing metabolic capacity confirmed the influence of endogenous metabolism on genotoxic potency. This work, which is the first of a two-part series, shows that BMD-derived potency rankings can be employed to support MOA evaluations as well as facilitate read across to expedite chemical evaluations and regulatory decision-making. The follow-up (Part II) employs the combined covariate approach to analyse in vivo genetic toxicity dose-response data focussing on how improvements in BMD precision can impact the reduction and refinement of animal use in toxicological research.

Kidney-on-a-Chip Technology for Drug-Induced Nephrotoxicity Screening

Improved model systems to predict drug efficacy, interactions, and drug-induced kidney injury (DIKI) are crucially needed in drug development. Organ-on-a-chip technology is a suitable in vitro system because it reproduces the 3D microenvironment. A kidney-on-a-chip can mimic the structural, mechanical, transport, absorptive, and physiological properties of the human kidney. In this review we address the application of state-of-the-art microfluidic culturing techniques, with a focus on culturing kidney proximal tubules, that are promising for the detection of biomarkers that predict drug interactions and DIKI. We also discuss high-throughput screening and the challenges for in vitro to in vivo extrapolation (IVIVE) that will need to be overcome for successful implementation.

A physiologically based toxicokinetic (PBTK) model for moderately hydrophobic organic chemicals in the European eel (Anguilla anguilla)

The European eel (Anguilla anguilla) is a facultatively catadromous fish species with a complex life cycle. Its current population status is alarming: recruitment has decreased drastically since the 1980s and its stock is still considered to be outside safe biological limits. Although there is no consensus on the reasons for this situation, it is currently thought to have resulted from a combination of different stressors, including anthropogenic contaminants. To deepen our understanding of the processes leading to the accumulation of lipophilic organic contaminants in yellow eels (i.e. the feeding, continental growth stage), we developed a physiologically based toxicokinetic model using our own data and values from the literature. Such models can predict the uptake and distribution of water-borne organic chemicals in the whole fish and in different tissues at any time during exposure. The predictive power of the model was tested against experimental data for six chemicals with n-octanol-water partitioning coefficient (log Kow) values ranging from 2.13-4.29. Model performance was excellent, with a root mean squared error of 0.28 log units. This model has the potential to help identify suitable habitats for restocking under eel management plans.

Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations

The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ.

The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism.

To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers.

The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.

A preliminary regional PBPK model of lung metabolism for improving species dependent descriptions of 1,3-butadiene and its metabolites

1,3-Butadiene (BD), a volatile organic chemical (VOC), is used in synthetic rubber production and other industrial processes. It is detectable at low levels in ambient air as well as in tobacco smoke and gasoline vapors. Inhalation exposures to high concentrations of BD have been associated with lung cancer in both humans and experimental animals, although differences in species sensitivity have been observed. Metabolically active lung cells such as Pulmonary Type I and Type II epithelial cells and club cells (Clara cells)(1) are potential targets of BD metabolite-induced toxicity. Metabolic capacities of these cells, their regional densities, and distributions vary throughout the respiratory tract as well as between species and cell types. Here we present a physiologically based pharmacokinetic (PBPK) model for BD that includes a regional model of lung metabolism, based on a previous model for styrene, to provide species-dependent descriptions of BD metabolism in the mouse, rat, and human. Since there are no in vivo data on BD pharmacokinetics in the human, the rat and mouse models were parameterized to the extent possible on the basis of in vitro metabolic data. Where it was necessary to use in vivo data, extrapolation from rat to mouse was performed to evaluate the level of uncertainty in the human model. A kidney compartment and description of downstream metabolism were also included in the model to allow for eventual use of available urinary and blood biomarker data in animals and humans to calibrate the model for estimation of BD exposures and internal metabolite levels. Results from simulated inhalation exposures to BD indicate that incorporation of differential lung region metabolism is important in describing species differences in pulmonary response and that these differences may have implications for risk assessments of human exposures to BD.

A paradigm shift in pharmacokinetic-pharmacodynamic (PKPD) modeling: rule of thumb for estimating free drug level in tissue compared with plasma to guide drug design

A basic assumption in pharmacokinetics-pharmacodynamics research is that the free drug concentration is similar in plasma and tissue, and, hence, in vitro plasma data can be used to estimate the in vivo condition in tissue. However, in a companion manuscript, it has been demonstrated that this assumption is violated for the ionized drugs. Nonetheless, these observations focus on in vitro static environments and do not challenge data with an in vivo dynamic system. Therefore, an extension from an in vitro to an in vivo system becomes the necessary next step. The objective of this study was to perform theoretical simulations of the free drug concentration in tissue and plasma by using a physiologically based pharmacokinetics (PBPK) model reproducing the in vivo conditions in human. Therefore, the effects of drug ionization, lipophilicity, and clearance have been taken into account in a dynamic system. This modeling exercise was performed as a proof of concept to demonstrate that free drug concentration in tissue and plasma may also differ in a dynamic system for passively permeable drugs that are ionized at the physiological pH. The PBPK model simulations indicated that free drug concentrations in tissue cells and plasma significantly differ for the ionized drugs because of the pH gradient effect between cells and interstitial space. Hence, a rule of thumb for potentially performing more accurate PBPK/PD modeling is suggested, which states that the free drug concentration in tissue and plasma will differ for the ionizable drugs in contrast to the neutral drugs. In addition to the pH gradient effect for the ionizable drugs, lipophilicity and clearance effects will increase or decrease the free drug concentration in tissue and plasma for each class of drugs; thus, higher will be the drug lipophilicity and clearance, lower would be the free drug concentration in plasma, and, hence, in tissue, in a dynamic in vivo system. Therefore, only considering the value of free fraction in plasma derived from a static in vitro environment might be biased to guide drug design (the old paradigm), and, hence, it is recommended to use a PBPK model to reproduce more accurately the in vivo condition in tissue (the new paradigm). This newly developed approach can be used to predict free drug concentration in diverse tissue compartments for small molecules in toxicology and pharmacology studies, which can be leveraged to optimize the pharmacokinetics drivers of tissue distribution based upon physicochemical and physiological input parameters in an attempt to optimize free drug level in tissue. Overall, this present study provides guidance on the application of plasma and tissue concentration information in PBPK/PD research in preclinical and clinical studies, which is in accordance with the recent literature.

Reprint of PopGen: A virtual human population generator

The risk assessment of environmental chemicals and drugs is moving towards a paradigm shift in approach which seeks the full replacement animal testing with high throughput, mechanistic, in vitro systems. This new vision will be reliant on the measurement in vitro, of concentration-dependent responses where prolonged excessive perturbations of specific biochemical pathways are likely to lead to adverse health effects in an intact organism. Such an approach requires a framework, into which disparate data generated using in vitro, in silico and in chemico systems, can be integrated and utilised for quantitative in vitro-to-in vivo extrapolation (QIVIVE), ultimately to the human population level. Physiologically based pharmacokinetic (PBPK) models are ideally suited for this and are obligatory in order to translate in vitro concentration-response relationships to an exposure or dose, route and duration regime in people. In this report we describe PopGen a virtual human population generator which is a user friendly, open access web-based application for the prediction of realistic anatomical, physiological and phase 1 metabolic variation in a wide range of healthy human populations. We demonstrate how PopGen can be used for QIVIVE by providing input to a PBPK model, at an appropriate level of detail, to reconstruct exposure from human biomonitoring data. We discuss how the process of exposure reconstruction from blood biomarkers, in general, is analogous to exposure or dose reconstruction from concentration-response measurements made in proposed in vitro cell based systems which are assumed to be surrogates for target organs.

How to report and discuss ADME data in medicinal chemistry publications: in vitro data or in vivo extrapolations?

Early drug discovery projects often utilize data from ADME (absorption, distribution, metabolism, elimination) assays to benchmark data and guide discussion, rather than the predicted in vivo consequences of these data. Here, the two paradigms are compared, using evaluations of metabolic stability based on either microsomal clearance assay data or from the predicted in vivo hepatic clearance and half-life calculated through the combination of the venous well-stirred model and Øie-Tozer's model. The need for a shift in paradigm is presented, and its implications discussed. It is suggested that discussions about ADME data should revolve around potential clinical problems that are most likely to surface during the development phase, each benchmarked with a suitable variable derived from the assay data.

Stem cell-derived systems in toxicology assessment

Industrial sectors perform toxicological assessments of their potential products to ensure human safety and to fulfill regulatory requirements. These assessments often involve animal testing, but ethical, cost, and time concerns, together with a ban on it in specific sectors, make appropriate in vitro systems indispensable in toxicology. In this study, we summarize the outcome of an EPAA (European Partnership of Alternatives to Animal Testing)-organized workshop on the use of stem cell-derived (SCD) systems in toxicology, with a focus on industrial applications. SCD systems, in particular, induced pluripotent stem cell-derived, provide physiological cell culture systems of easy access and amenable to a variety of assays. They also present the opportunity to apply the vast repository of existing nonclinical data for the understanding of in vitro to in vivo translation. SCD systems from several toxicologically relevant tissues exist; they generally recapitulate many aspects of physiology and respond to toxicological and pharmacological interventions. However, focused research is necessary to accelerate implementation of SCD systems in an industrial setting and subsequent use of such systems by regulatory authorities. Research is required into the phenotypic characterization of the systems, since methods and protocols for generating terminally differentiated SCD cells are still lacking. Organotypical 3D culture systems in bioreactors and microscale tissue engineering technologies should be fostered, as they promote and maintain differentiation and support coculture systems. They need further development and validation for their successful implementation in toxicity testing in industry. Analytical measures also need to be implemented to enable compound exposure and metabolism measurements for in vitro to in vivo extrapolation. The future of SCD toxicological tests will combine advanced cell culture technologies and biokinetic measurements to support regulatory and research applications. However, scientific and technical hurdles must be overcome before SCD in vitro methods undergo appropriate validation and become accepted in the regulatory arena.

Drug Distribution to Human Tissues: Prediction and Examination of the Basic Assumption in In Vivo Pharmacokinetics-Pharmacodynamics (PK/PD) Research

The tissue:plasma partition coefficients (Kp ) are good indicators of the extent of tissue distribution. Therefore, advanced tissue composition-based models were used to predict the Kp values of drugs under in vivo conditions on the basis of in vitro and physiological input data. These models, however, focus on animal tissues and do not challenge the predictions with human tissues for drugs. The first objective of this study was to predict the experimentally determined Kp values of seven human tissues for 26 drugs. In all, 95% of the predicted Kp values are within 2.5-fold error of the observed values in humans. Accordingly, these results suggest that the tissue composition-based model used in this study is able to provide accurate estimates of drug partitioning in the studied human tissues. Furthermore, as the Kp equals to the ratio of total concentration between tissue and plasma, or the ratio of unbound fraction between plasma (fup ) and tissue (fut ), this parameter Kp would deviate from the unity. Therefore, the second objective was to examine the corresponding relationships between fup and fut values experimentally determined in humans for several drugs. The results also indicate that fup may significantly deviate to fut ; the discrepancies are governed by the dissimilarities in the binding and ionization on both sides of the membrane, which were captured by the tissue composition-based model. Hence, this violated the basic assumption in in vivo pharmacokinetics-pharmacodynamics (PK/PD) research, since the free drug concentration in tissue and plasma was not equal particularly for the ionizable drugs due to the pH gradient effect on the fraction of unionized drug in plasma (fuip ) and tissue (fuit ) (i.e., fup × fuip × total plasma concentration = fut × fuit × total tissue concentration, and, hence, the free drug concentration in plasma and tissue differed by fuip/fuit). Therefore, this assumption should be adjusted for the ionized drugs, and, hence, a mathematical correction to the basic assumption of similar free drug concentration in plasma and tissues can be derived from the tissue composition-based model. Note that this assumption will be further challenged in a dynamic in vivo system in a companion manuscript. Overall, this study was a first attempt to predict the in vivo Kp values for specific human tissues by considering separately the effect of fup and fut , with the aim of facilitating the use of physiologically-based PK (PBPK) model in PK/PD studies.

Assessment of health risks resulting from early-life exposures: Are current chemical toxicity testing protocols and risk assessment methods adequate?

Abstract Over the last couple of decades, the awareness of the potential health impacts associated with early-life exposures has increased. Global regulatory approaches to chemical risk assessment are intended to be protective for the diverse human population including all life stages. However, questions persist as to whether the current testing approaches and risk assessment methodologies are adequately protective for infants and children. Here, we review physiological and developmental differences that may result in differential sensitivity associated with early-life exposures. It is clear that sensitivity to chemical exposures during early-life can be similar, higher, or lower than that of adults, and can change quickly within a short developmental timeframe. Moreover, age-related exposure differences provide an important consideration for overall susceptibility. Differential sensitivity associated with a life stage can reflect the toxicokinetic handling of a xenobiotic exposure, the toxicodynamic response, or both. Each of these is illustrated with chemical-specific examples. The adequacy of current testing protocols, proposed new tools, and risk assessment methods for systemic noncancer endpoints are reviewed in light of the potential for differential risk to infants and young children.

In vitro models for neurotoxicology research

The nervous system has a highly complex organization, including many cell types with multiple functions, with an intricate anatomy and unique structural and functional characteristics; the study of its (dys)functionality following exposure to xenobiotics, neurotoxicology, constitutes an important issue in neurosciences.

Interpreting in vitro developmental toxicity test battery results: The consideration of toxicokinetics

In the EU collaborative project ChemScreen an alternative, in vitro assay-based test strategy was developed to screen compounds for reproductive toxicity. A toxicokinetic modeling approach was used to allow quantitative comparison between effective concentrations in the in vitro test battery and observations of developmental toxicity in vivo. This modeling strategy is based on (1) the definition of relevant observations of toxicity in vivo, (2) simulation of the corresponding systemic concentrations in vivo by toxicokinetic modeling, and (3) correction for differences in protein binding and lipid partitioning between plasma and in vitro test media. The test results of a feasibility study with a number of known reproductive toxicants has been described previously (Piersma et al. [15]). In the present paper, we take a more detailed look at the toxicokinetics of these compounds, and add the analysis of some compounds from subsequent studies. We discuss how the consideration of toxicokinetics allowed comparison between test systems with differing test medium composition, has helped to interpret the in vitro findings in light of in vivo observations, and to gain confidence in the predictive value of the test battery outcomes. The same toxicokinetic modeling strategy, in reverse order, can now be used for risk assessment purposes to predict toxic doses in vivo from effective concentrations in vitro.

Biotransformation in vitro: An essential consideration in the quantitative in vitro-to-in vivo extrapolation (QIVIVE) of toxicity data

Early consideration of the multiplicity of factors that govern the biological fate of foreign compounds in living systems is a necessary prerequisite for the quantitative in vitro-in vivo extrapolation (QIVIVE) of toxicity data. Substantial technological advances in in vitro methodologies have facilitated the study of in vitro metabolism and the further use of such data for in vivo prediction. However, extrapolation to in vivo with a comfortable degree of confidence, requires continuous progress in the field to address challenges such as e.g., in vitro evaluation of chemical-chemical interactions, accounting for individual variability but also analytical challenges for ensuring sensitive measurement technologies. This paper discusses the current status of in vitro metabolism studies for QIVIVE extrapolation, serving today's hazard and risk assessment needs. A short overview of the methodologies for in vitro metabolism studies is given. Furthermore, recommendations for priority research and other activities are provided to ensure further widespread uptake of in vitro metabolism methods in 21st century toxicology. The need for more streamlined and explicitly described integrated approaches to reflect the physiology and the related dynamic and kinetic processes of the human body is highlighted i.e., using in vitro data in combination with in silico approaches.

An adverse outcome pathway framework for neural tube and axial defects mediated by modulation of retinoic acid homeostasis

Developmental toxicity can be caused through a multitude of mechanisms and can therefore not be captured through a single simple mechanistic paradigm. However, it may be possible to define a selected group of overarching mechanisms that might allow detection of the vast majority of developmental toxicants. Against this background, we have explored the usefulness of retinoic acid mediated regulation of neural tube and axial patterning as a general mechanism that, when perturbed, may result in manifestations of developmental toxicity that may cover a large part of malformations known to occur in experimental animals and in man. Through a literature survey, we have identified key genes in the regulation of retinoic acid homeostasis, as well as marker genes of neural tube and axial patterning, that may be used to detect developmental toxicants in in vitro systems. A retinoic acid-neural tube/axial patterning adverse outcome pathway (RA-NTA AOP) framework was designed. The framework was tested against existing data of flusilazole exposure in the rat whole embryo culture, the zebrafish embryotoxicity test, and the embryonic stem cell test. Flusilazole is known to interact with retinoic acid homeostasis, and induced common and unique NTA marker gene changes in the three test systems. Flusilazole-induced changes were similar in directionality to gene expression responses after retinoic acid exposure. It is suggested that the RA-NTA framework may provide a general tool to define mechanistic pathways and biomarkers of developmental toxicity that may be used in alternative in vitro assays for the detection of embryotoxic compounds.

A multi-parameter in vitro screen in human stem cell-derived cardiomyocytes identifies ponatinib-induced structural and functional cardiac toxicity

Ponatinib, a multi-targeted TKI and potent pan-ABL inhibitor, approved for the treatment of Ph + ALL and CML, was temporarily withdrawn from the U.S. market due to severe vascular adverse events. Cardiac-specific toxicities including myocardial infarction, severe congestive heart failure, and cardiac arrhythmias have also been shown with ponatinib. Targeted oncology agents such as ponatinib have transformed cancer treatment but often induce toxicity due to inhibition of survival pathways shared by both cancer and cardiac cells. These toxicities are often missed by the standard preclinical toxicity assessment methods, which include human Ether-à-go-go-related gene (hERG) and animal toxicity testing. In this study, we show that a multiparameter in vitro toxicity screening approach using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) accurately predicted the cardiac toxicity potential of ponatinib. This in vitro model evaluated ponatinib's effect on the overall cell health, mitochondrial stress, and function of hiPSC-CM and also provided mechanistic insight into the signaling pathways and cellular structures altered with treatment. We show here that ponatinib rapidly inhibits prosurvival signaling pathways, induces structural cardiac toxicity (as shown by actin cytoskeleton damage, mitochondrial stress, cell death, and troponin secretion), and disrupts cardiac cell beating. Most of these effects occurred at doses between 10× and 50× ponatinib's Cmax, a dose range shown to be relevant for accurate prediction of in vivo toxicity. Together these studies show that a comprehensive in vitro screening tool in a more relevant human cardiac cell model can improve the detection of cardiac toxicity with targeted oncology agents such as ponatinib.

A framework for the next generation of risk science

OBJECTIVES

In 2011, the U.S. Environmental Protection Agency initiated the NexGen project to develop a new paradigm for the next generation of risk science.

METHODS

The NexGen framework was built on three cornerstones: the availability of new data on toxicity pathways made possible by fundamental advances in basic biology and toxicological science, the incorporation of a population health perspective that recognizes that most adverse health outcomes involve multiple determinants, and a renewed focus on new risk assessment methodologies designed to better inform risk management decision making.

RESULTS

The NexGen framework has three phases. Phase I (objectives) focuses on problem formulation and scoping, taking into account the risk context and the range of available risk management decision-making options. Phase II (risk assessment) seeks to identify critical toxicity pathway perturbations using new toxicity testing tools and technologies, and to better characterize risks and uncertainties using advanced risk assessment methodologies. Phase III (risk management) involves the development of evidence-based population health risk management strategies of a regulatory, economic, advisory, community-based, or technological nature, using sound principles of risk management decision making.

CONCLUSIONS

Analysis of a series of case study prototypes indicated that many aspects of the NexGen framework are already beginning to be adopted in practice.

Use of in vitro data in developing a physiologically based pharmacokinetic model: Carbaryl as a case study

In vitro-derived information has been increasingly used to support and improve human health risk assessment for exposure to chemicals. Physiologically based pharmacokinetic (PBPK) modeling is a key component in the movement toward in vitro-based risk assessment, providing a tool to integrate diverse experimental data and mechanistic information to relate in vitro effective concentrations to equivalent human exposures. One of the challenges, however, in the use of PBPK models for this purpose has been the need for extensive chemical-specific parameters. With the remarkable advances in in vitro methodologies in recent years, in vitro-derived parameters can now be easily incorporated into PBPK models. In this study we demonstrate an in vitro data based parameterization approach to develop a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model, using carbaryl as a case study. In vitro experiments were performed to provide the chemical-specific pharmacokinetic (PK) and pharmacodynamic (PD) parameters for carbaryl in the PBPK model for this compound. Metabolic clearance and cholinesterase (ChE) interaction parameters for carbaryl were measured in rat and human tissues. These in vitro PK and PD data were extrapolated to parameters in the whole body PBPK model using biologically appropriate scaling. The PBPK model was then used to predict the kinetics and ChE inhibition dynamics of carbaryl in vivo. This case study with carbaryl provides a reasonably successful example of utilizing the in vitro to in vivo extrapolation (IVIVE) approach for PBPK model development. This approach can be applied to other carbamates with an anticholinesterase mode of action as well as to environmental chemicals in general with further refinement of the current shortcomings in the approach. It will contribute to minimizing the need for in vivo human data for PBPK model parameterization and evaluation in human risk assessments.

Understanding receptor-mediated effects in rainbow trout: in vitro-in vivo extrapolation using physiologically based toxicokinetic models

The European REACH regulation requires the use of animal experimentation to assess the risk of industrial chemicals. However, the 3R principle (reduction, replacement, refinement) demands the use of suitable alternative test methods. Many dossiers submitted for the authorization of chemicals have attempted to provide the required data without performing new experiments, relying heavily on in silico methods; in vitro assays were scarcely used. We propose a methodology that uses physiologically based toxicokinetic (PBTK) models to extrapolate in vitro data to the in vivo level. We collected experimental results for in vitro and in vivo ethoxyresorufin-O-deethylase and vitellogenin induction following chemical exposure and compared those results with model predictions. We found that the predictive power of aqueous chemical concentrations was limited; median effect concentrations (EC50s) based on internal concentrations in fish correlated better with in vitro EC50s. Our data show that in vitro assays could offer a substitute for fish studies when combined with PBTK models.

Network pharmacology strategies toward multi-target anticancer therapies: from computational models to experimental design principles

Polypharmacology has emerged as novel means in drug discovery for improving treatment response in clinical use. However, to really capitalize on the polypharmacological effects of drugs, there is a critical need to better model and understand how the complex interactions between drugs and their cellular targets contribute to drug efficacy and possible side effects. Network graphs provide a convenient modeling framework for dealing with the fact that most drugs act on cellular systems through targeting multiple proteins both through on-target and off-target binding. Network pharmacology models aim at addressing questions such as how and where in the disease network should one target to inhibit disease phenotypes, such as cancer growth, ideally leading to therapies that are less vulnerable to drug resistance and side effects by means of attacking the disease network at the systems level through synergistic and synthetic lethal interactions. Since the exponentially increasing number of potential drug target combinations makes pure experimental approach quickly unfeasible, this review depicts a number of computational models and algorithms that can effectively reduce the search space for determining the most promising combinations for experimental evaluation. Such computational-experimental strategies are geared toward realizing the full potential of multi-target treatments in different disease phenotypes. Our specific focus is on system-level network approaches to polypharmacology designs in anticancer drug discovery, where we give representative examples of how network-centric modeling may offer systematic strategies toward better understanding and even predicting the phenotypic responses to multi-target therapies.

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.

Evaluation of simple in vitro to in vivo extrapolation approaches for environmental compounds

As part of an effort to support in silico/in vitro based risk assessment, we evaluated the accuracy associated with conducting simple in vitro to in vivo extrapolation (IVIVE) for environmental compounds using available in vitro human metabolism data. The IVIVE approach was applied to a number of compounds with a wide range of properties spanning the diversity of characteristics of environmental compounds, and where possible the resulting estimates of the in vivo steady-state blood concentration were compared with estimates derived on the basis of human in vivo kinetic data. There appears to be a systematic bias in the estimation of intrinsic clearance (Clint) from in vitro versus in vivo data, with in vitro based estimates underestimating in vivo clearance for small values of Clint but with the opposite relationship at large values of Clint. Nevertheless, the resulting estimates of Css were in good agreement. The chief drawback of the simple approach used in this study, which performs the IVIVE prediction for the parent compound only, is that it is not applicable for toxicity associated with a metabolite.

Metabolomics in toxicology and preclinical research

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

PopGen: A virtual human population generator

The risk assessment of environmental chemicals and drugs is moving towards a paradigm shift in approach which seeks the full replacement animal testing with high throughput, mechanistic, in vitro systems. This new vision will be reliant on the measurement in vitro, of concentration-dependent responses where prolonged excessive perturbations of specific biochemical pathways are likely to lead to adverse health effects in an intact organism. Such an approach requires a framework, into which disparate data generated using in vitro, in silico and in chemico systems, can be integrated and utilised for quantitative in vitro-to-in vivo extrapolation (QIVIVE), ultimately to the human population level. Physiologically based pharmacokinetic (PBPK) models are ideally suited for this and are obligatory in order to translate in vitro concentration-response relationships to an exposure or dose, route and duration regime in people. In this report we describe PopGen, a virtual human population generator which is a user friendly, open access web-based application for the prediction of realistic anatomical, physiological and phase 1 metabolic variation in a wide range of healthy human populations. We demonstrate how PopGen can be used for QIVIVE by providing input to a PBPK model, at an appropriate level of detail, to reconstruct exposure from human biomonitoring data. We discuss how the process of exposure reconstruction from blood biomarkers, in general, is analogous to exposure or dose reconstruction from concentration-response measurements made in proposed in vitro cell based systems which are assumed to be surrogates for target organs.

A framework incorporating the impact of exposure scenarios and application conditions on risk assessment of chemicals applied to skin

PURPOSE

1. To develop a framework for exposure calculation via the dermal route to meet the needs of 21st century toxicity testing and refine current approaches; 2. To demonstrate the impact of exposure scenario and application conditions on the plasma concentration following dermal exposure.

METHOD

A workflow connecting a dynamic skin penetration model with a generic whole-body physiologically-based pharmacokinetic (PBPK) model was developed. The impact of modifying exposure scenarios and application conditions on the simulated steady-state plasma concentration and exposure conversion factor was investigated for 9 chemicals tested previously in dermal animal studies which did not consider kinetics in their experimental designs.

RESULTS

By simulating the animal study scenarios and exposure conditions, we showed that 7 studies were conducted with finite dose exposures, 1 with both finite and infinite dose exposures (in these 8 studies, an increase in the animal dose resulted in an increase in the simulated steady-state plasma concentrations (C p,ss)), while 1 study was conducted with infinite dose exposures only (an increase in the animal dose resulted in identical C p,ss). Steady-state plasma concentrations were up to 30-fold higher following an infinite dose scenario vs. a finite dose scenario, and up to 40-fold higher with occlusion vs. without. Depending on the chemical, the presence of water as a vehicle increased or decreased the steady-state plasma concentration, the largest difference being a factor of 16.

CONCLUSIONS

The workflow linking Kasting's model of skin penetration and whole-body PBPK enables estimation of plasma concentrations for various applied doses, exposure scenarios and application conditions. Consequently, it provides a quantitative, mechanistic tool to refine dermal exposure calculations methodology for further use in risk assessment.

Prediction of dose-hepatotoxic response in humans based on toxicokinetic/toxicodynamic modeling with or without in vivo data: a case study with acetaminophen

In the present legislations, the use of methods alternative to animal testing is explicitly encouraged, to use animal testing only 'as a last resort' or to ban it. The use of alternative methods to replace kinetics or repeated dose in vivo tests is a challenging issue. We propose here a strategy based on in vitro tests and QSAR (Quantitative Structure Activity Relationship) models to calibrate a dose-response model predicting hepatotoxicity. The dose response consists in calibrating and coupling a PBPK (physiologically-based pharmacokinetic) model with a toxicodynamic model for cell viability. We applied our strategy to acetaminophen and compared three different ways to calibrate the PBPK model: only with in vitro and in silico methods, using rat data or using all available data including data on humans. Some estimates of kinetic parameters differed substantially among the three calibration processes, but, at the end, the three models were quite comparable in terms of liver toxicity predictions and close to the usual range of human overdose. For the model based on alternative methods, the good adequation with the two other models resulted from an overestimated renal elimination rate which compensated for the underestimation of the metabolism rate. Our study points out that toxicokinetics/toxicodynamics approaches, based on alternative methods and modelling only, can predict in vivo liver toxicity with accuracy comparable to in vivo methods.

Analysis of the Cytotoxic Potential of Anisomelic Acid Isolated from Anisomeles malabarica

Anisomelic acid (AA), one of the major compounds in Anisomeles malabarica, was tested for its cytotoxicity and apoptosis-inducing potential in breast and cervical cancer cells. The MTT assay for cell viability indicated that AA is cytotoxic to all of the four cell lines tested in a dose- and duration-dependent manner. Acridine Orange & Ethidium Bromide (AO & EB) and Hoechst 33258 staining of AA-treated cells revealed typical apoptotic morphology such as condensed chromatin and formation of apoptotic bodies. The comet assay revealed DNA strand break(s), indicating that AA induces DNA damage which culminates in apoptosis. Thus, the study revealed the anti-proliferative and apoptosis-inducing properties of AA in both breast and cervical cancer cells. Therefore, anisomelic acid offers potential for application in breast and cervical cancer therapy.

A mechanistic, model-based approach to safety assessment in clinical development

Assessing the safety of pharmacotherapies is a primary goal of clinical trials in drug development. The low frequency of relevant side effects, however, often poses a significant challenge for risk assessment. Methodologies allowing robust extrapolation of safety statistics based on preclinical data and information from clinical trials with limited numbers of patients are hence needed to further improve safety and efficacy in the drug development process. Here, we present a generic systems pharmacology approach integrating prior physiological and pharmacological knowledge, preclinical data, and clinical trial results, which allows predicting adverse event rates related to drug exposure. Possible fields of application involve high-risk populations, novel drug candidates, and different dosing scenarios. As an example, the approach is applied to simvastatin and pravastatin and the prediction of myopathy rates in a population with a genotype leading to a significantly increased myopathy risk.CPT: Pharmacometrics & Systems Pharmacology (2012) 1, e13; doi:10.1038/psp.2012.14; advance online publication 7 November 2012.