The integrated stress response-related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability.

BACKGROUND AND AIMS: Drug-induced liver injury (DILI) is one of the most frequent reasons for failure of drugs in clinical trials or market withdrawal. Early assessment of DILI risk remains a major challenge during drug development. Here, we present a mechanism-based weight-of-evidence approach able to identify certain candidate compounds with DILI liabilities due to mitochondrial toxicity. METHODS: A total of 1587 FDA-approved drugs and 378 kinase inhibitors were screened for cellular stress response activation associated with DILI using an imaging-based HepG2 BAC-GFP reporter platform including the integrated stress response (CHOP), DNA damage response (P21) and oxidative stress response (SRXN1). RESULTS: In total 389, 219 and 104 drugs were able to induce CHOP-GFP, P21-GFP and SRXN1-GFP expression at 50 µM respectively. Concentration response analysis identified 154 FDA-approved drugs as critical CHOP-GFP inducers. Based on predicted and observed (pre-)clinical DILI liabilities of these drugs, nine antimycotic drugs (e.g. butoconazole, miconazole, tioconazole) and 13 central nervous system (CNS) agents (e.g. duloxetine, fluoxetine) were selected for transcriptomic evaluation using whole-genome RNA-sequencing of primary human hepatocytes. Gene network analysis uncovered mitochondrial processes, NRF2 signalling and xenobiotic metabolism as most affected by the antimycotic drugs and CNS agents. Both the selected antimycotics and CNS agents caused impairment of mitochondrial oxygen consumption in both HepG2 and primary human hepatocytes. CONCLUSIONS: Together, the results suggest that early pre-clinical screening for CHOP expression could indicate liability of mitochondrial toxicity in the context of DILI, and, therefore, could serve as an important warning signal to consider during decision-making in drug development.

Protectiveness of NAM-based hazard assessment - which testing scope is required?

Hazard assessment (HA) requires toxicity tests to allow deriving protective points of departure (PoDs) for risk assessment irrespective of a compound's mode of action (MoA). The scope of in vitro test batteries (ivTB) thereby necessitated for systemic toxicity is still unclear. We explored the protectiveness regarding systemic toxicity of an ivTB with a scope, which was guided by previous findings from rodent studies, where examining six main targets, including liver and kidney, was sufficient to predict the guideline scope-based PoD with high probability. The ivTB comprises human in vitro models representing liver, kidney, lung and the neuronal system covering transcriptome, mitochondrial dysfunction and neuronal outgrowth. Additionally, 32 CALUX®- and 10 HepG2 BAC-GFP reporters cover a broad range of disturbance mechanisms. Eight compounds were chosen for causing adverse effects such as immunotoxicity or anemia in vivo, i.e., effects not directly covered by assays in the ivTB. PoDs derived from the ivTB and from oral repeated dose studies in rodents were extrapolated to maximum unbound plasma concentrations for comparison. The ivTB-based PoDs were one to five orders of magnitude lower than in vivo PoDs for six of eight compounds, implying that they were protective. The extent of in vitro response varied across test compounds. Especially for hematotoxic substances, the ivTB showed either no response or only cytotoxicity. Assays better capturing this type of hazard would be needed to complement the ivTB. This study highlights the potentially broad applicability of ivTBs for deriving protective PoDs of compounds with unknown MoA.

Animal tests are used to determine which amount of a chemical is toxic ('threshold of toxicity') and which organs are affected. In principle, the threshold can also be derived solely from tests with cultured cells. However, only a limited number of cell types can practically be tested, so one challenge is to determine how many and which types shall be tested. In animal studies, only few organs including liver and kidney are regularly among those most sensitively affected. We explored whether a cell-based test battery representing these sensitive organs and covering important mechanisms of toxicity can be used to derive protective human thresholds. To challenge this approach, eight chemicals were tested that primarily cause effects in organs not directly represented in our test battery. Results provided protective thresholds for most of the investigated compounds and gave indications how to further improve the approach towards a full-fledged replacement for animal tests.

Early Increases in Blood Pressure and Major Adverse Cardiovascular Events in Patients With Renal Cell Carcinoma and Thyroid Cancer Treated With VEGFR TKIs.

BACKGROUND: Although VEGFR tyrosine kinase inhibitors (TKIs) are a preferred systemic treatment approach for patients with advanced renal cell carcinoma (RCC) and thyroid carcinoma (TC), treatment-related cardiovascular (CV) toxicity is an important contributor to morbidity. However, the clinical risk assessment and impact of CV toxicities, including early significant hypertension, among real-world advanced cancer populations receiving VEGFR TKI therapies remain understudied. METHODS: In a multicenter, retrospective cohort study across 3 large and diverse US health systems, we characterized baseline hypertension and CV comorbidity in patients with RCC and those with TC who are newly initiating VEGFR TKI therapy. We also evaluated baseline patient-, treatment-, and disease-related factors associated with the risk for treatment-related early hypertension (within 6 weeks of TKI initiation) and major adverse CV events (MACE), accounting for the competing risk of death in an advanced cancer population, after VEGFR TKI initiation. RESULTS: Between 2008 and 2020, 987 patients (80.3% with RCC, 19.7% with TC) initiated VEGFR TKI therapy. The baseline prevalence of hypertension was high (61.5% and 53.6% in patients with RCC and TC, respectively). Adverse CV events, including heart failure and cerebrovascular accident, were common (occurring in 14.9% of patients) and frequently occurred early (46.3% occurred within 1 year of VEGFR TKI initiation). Baseline hypertension and Black race were the primary clinical factors associated with increased acute hypertensive risk within 6 weeks of VEGFR TKI initiation. However, early significant "on-treatment" hypertension was not associated with MACE. CONCLUSIONS: These multicenter, real-world findings indicate that hypertensive and CV morbidities are highly prevalent among patients initiating VEGFR TKI therapies, and baseline hypertension and Black race represent the primary clinical factors associated with VEGFR TKI-related early significant hypertension. However, early on-treatment hypertension was not associated with MACE, and cancer-specific CV risk algorithms may be warranted for patients initiating VEGFR TKIs.

A systems approach reveals species differences in hepatic stress response capacity.

To minimize the occurrence of unexpected toxicities in early phase preclinical studies of new drugs, it is vital to understand fundamental similarities and differences between preclinical species and humans. Species differences in sensitivity to acetaminophen (APAP) liver injury have been related to differences in the fraction of the drug that is bioactivated to the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI). We have used physiologically based pharmacokinetic modeling to identify oral doses of APAP (300 and 1000 mg/kg in mice and rats, respectively) yielding similar hepatic burdens of NAPQI to enable the comparison of temporal liver tissue responses under conditions of equivalent chemical insult. Despite pharmacokinetic and biochemical verification of the equivalent NAPQI insult, serum biomarker and tissue histopathology analyses revealed that mice still exhibited a greater degree of liver injury than rats. Transcriptomic and proteomic analyses highlighted the stronger activation of stress response pathways (including the Nrf2 oxidative stress response and autophagy) in the livers of rats, indicative of a more robust transcriptional adaptation to the equivalent insult. Components of these pathways were also found to be expressed at a higher basal level in the livers of rats compared with both mice and humans. Our findings exemplify a systems approach to understanding differential species sensitivity to hepatotoxicity. Multiomics analysis indicated that rats possess a greater basal and adaptive capacity for hepatic stress responses than mice and humans, with important implications for species selection and human translation in the safety testing of new drug candidates associated with reactive metabolite formation.

SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator.

SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara's Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.

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.

Unravelling Mechanisms of Doxorubicin-Induced Toxicity in 3D Human Intestinal Organoids.

Doxorubicin is widely used in the treatment of different cancers, and its side effects can be severe in many tissues, including the intestines. Symptoms such as diarrhoea and abdominal pain caused by intestinal inflammation lead to the interruption of chemotherapy. Nevertheless, the molecular mechanisms associated with doxorubicin intestinal toxicity have been poorly explored. This study aims to investigate such mechanisms by exposing 3D small intestine and colon organoids to doxorubicin and to evaluate transcriptomic responses in relation to viability and apoptosis as physiological endpoints. The in vitro concentrations and dosing regimens of doxorubicin were selected based on physiologically based pharmacokinetic model simulations of treatment regimens recommended for cancer patients. Cytotoxicity and cell morphology were evaluated as well as gene expression and biological pathways affected by doxorubicin. In both types of organoids, cell cycle, the p53 signalling pathway, and oxidative stress were the most affected pathways. However, significant differences between colon and SI organoids were evident, particularly in essential metabolic pathways. Short time-series expression miner was used to further explore temporal changes in gene profiles, which identified distinct tissue responses. Finally, in silico proteomics revealed important proteins involved in doxorubicin metabolism and cellular processes that were in line with the transcriptomic responses, including cell cycle and senescence, transport of molecules, and mitochondria impairment. This study provides new insight into doxorubicin-induced effects on the gene expression levels in the intestines. Currently, we are exploring the potential use of these data in establishing quantitative systems toxicology models for the prediction of drug-induced gastrointestinal toxicity.

A Transcriptomic Approach to Elucidate the Mechanisms of Gefitinib-Induced Toxicity in Healthy Human Intestinal Organoids.

Gefitinib is a tyrosine kinase inhibitor (TKI) that selectively inhibits the epidermal growth factor receptor (EGFR), hampering cell growth and proliferation. Due to its action, gefitinib has been used in the treatment of cancers that present abnormally increased expression of EGFR. However, side effects from gefitinib therapy may occur, among which diarrhoea is most common, that can lead to interruption of the planned therapy in the more severe cases. The mechanisms underlying intestinal toxicity induced by gefitinib are not well understood. Therefore, this study aims at providing insight into these mechanisms based on transcriptomic responses induced in vitro. A 3D culture of healthy human colon and small intestine (SI) organoids was exposed to 0.1, 1, 10 and 30 µM of gefitinib, for a maximum of three days. These drug concentrations were selected using physiologically-based pharmacokinetic simulation considering patient dosing regimens. Samples were used for the analysis of viability and caspase 3/7 activation, image-based analysis of structural changes, as well as RNA isolation and sequencing via high-throughput techniques. Differential gene expression analysis showed that gefitinib perturbed signal transduction pathways, apoptosis, cell cycle, FOXO-mediated transcription, p53 signalling pathway, and metabolic pathways. Remarkably, opposite expression patterns of genes associated with metabolism of lipids and cholesterol biosynthesis were observed in colon versus SI organoids in response to gefitinib. These differences in the organoids' responses could be linked to increased activated protein kinase (AMPK) activity in colon, which can influence the sensitivity of the colon to the drug. Therefore, this study sheds light on how gefitinib induces toxicity in intestinal organoids and provides an avenue towards the development of a potential tool for drug screening and development.

Medical manifestations and health care utilization among adult MyCode participants with neurodevelopmental psychiatric copy number variants.

PURPOSE: Recurrent pathogenic copy number variants (pCNVs) have large-effect impacts on brain function and represent important etiologies of neurodevelopmental psychiatric disorders (NPDs), including autism and schizophrenia. Patterns of health care utilization in adults with pCNVs have gone largely unstudied and are likely to differ in significant ways from those of children. METHODS: We compared the prevalence of NPDs and electronic health record-based medical conditions in 928 adults with 26 pCNVs to a demographically-matched cohort of pCNV-negative controls from >135,000 patient-participants in Geisinger's MyCode Community Health Initiative. We also evaluated 3 quantitative health care utilization measures (outpatient, inpatient, and emergency department visits) in both groups. RESULTS: Adults with pCNVs (24.9%) were more likely than controls (16.0%) to have a documented NPD. They had significantly higher rates of several chronic diseases, including diabetes (29.3% in participants with pCNVs vs 20.4% in participants without pCNVs) and dementia (2.2% in participants with pCNVs vs 1.0% participants without pCNVs), and twice as many annual emergency department visits. CONCLUSION: These findings highlight the potential for genetic information-specifically, pCNVs-to inform the study of health care outcomes and utilization in adults. If, as our findings suggest, adults with pCNVs have poorer health and require disproportionate health care resources, early genetic diagnosis paired with patient-centered interventions may help to anticipate problems, improve outcomes, and reduce the associated economic burden.

Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action.

Read-across approaches often remain inconclusive as they do not provide sufficient evidence on a common mode of action across the category members. This read-across case study on thirteen, structurally similar, branched aliphatic carboxylic acids investigates the concept of using human-based new approach methods, such as in vitro and in silico models, to demonstrate biological similarity. Five out of the thirteen analogues have preclinical in vivo studies. Three out of them induced lipid accumulation or hypertrophy in preclinical studies with repeated exposure, which leads to the read-across hypothesis that the analogues can potentially induce hepatic steatosis. To confirm the selection of analogues, the expression patterns of the induced differentially expressed genes (DEGs) were analysed in a human liver model. With increasing dose, the expression pattern within the tested analogues got more similar, which serves as a first indication of a common mode of action and suggests differences in the potency of the analogues. Hepatic steatosis is a well-known adverse outcome, for which over 55 adverse outcome pathways have been identified. The resulting adverse outcome pathway (AOP) network, comprised a total 43 MIEs/KEs and enabled the design of an in vitro testing battery. From the AOP network, ten MIEs, early and late KEs were tested to systematically investigate a common mode of action among the grouped compounds. The targeted testing of AOP specific MIE/KEs shows that biological activity in the category decreases with side chain length. A similar trend was evident in measuring liver alterations in zebra fish embryos. However, activation of single MIEs or early KEs at in vivo relevant doses did not necessarily progress to the late KE "lipid accumulation". KEs not related to the read-across hypothesis, testing for example general mitochondrial stress responses in liver cells, showed no trend or biological similarity. Testing scope is a key issue in the design of in vitro test batteries. The Dempster-Shafer decision theory predicted those analogues with in vivo reference data correctly using one human liver model or the CALUX reporter assays. The case study shows that the read-across hypothesis is the key element to designing the testing strategy. In the case of a good mechanistic understanding, an AOP facilitates the selection of reliable human in vitro models to demonstrate a common mode of action. Testing DEGs, MIEs and early KEs served to show biological similarity, whereas the late KEs become important for confirmation, as progression from MIEs to AO is not always guaranteed.

Effective exposure of chemicals in in vitro cell systems: A review of chemical distribution models.

Nominal effect concentrations from in vitro toxicity assays may lead to inaccurate estimations of in vivo toxic doses because the nominal concentration poorly reflects the concentration at the molecular target in cells in vitro, which is responsible for initiating effects and can be referred to as the biologically effective dose. Chemicals can differentially distribute between in vitro assay compartments, including serum constituents in exposure medium, microtitre plate plastic, headspace and extracellular matrices. The partitioning of test chemicals to these extracellular compartments reduces the concentration at the molecular target. Free concentrations in medium and cell-associated concentrations are considered better proxies of the biologically effective dose. This paper reviews the mechanisms by which test chemicals distribute between in vitro assay compartments, and also lists the physicochemical properties driving the extent of this distribution. The mechanisms and physicochemical properties driving the distribution of test chemical in vitro help explain the makeup of mass balance models that estimate free concentrations and cell-associated concentrations in in vitro toxicity assays. A thorough understanding of the distribution processes and assumptions underlying these mass balance models helps define chemical and biological applicability domains of individual models, as well as provide a perspective on how to improve model predictivity and quantitative in vitro-in vivo extrapolations.

Chemical concentrations in cell culture compartments (C5) - free concentrations.

In biological systems (cell culture media, cells, body fluids), drugs/toxicants are usually not freely dissolved but partially bound to biomolecules; only a fraction of the chemical is free/unbound (fu). To predict pharmacological effects and toxicity, it is important that the fu of the drug is known. As the differences between free and nominal concentrations are determined by test system parameters (e.g., the protein and lipid content, and the type of surface material), comparison of nominal concentrations between two different new approach methods (NAM) may lead to faulty conclusions. The same problem exists when in vitro concentrations are compared to those in human subjects. Therefore, the respective fu of a chemical in a test system needs to be determined for in vitro-to-in vivo extrapolations (IVIVE). Besides direct measurements, prediction models can help to obtain fu. Here we describe a simplified approach to approximate fu and provide background information on the underlying assumptions. Comparative predictions and measurements of fu of various drugs are shown to exemplify the approach. Basic input data, like protein and lipid concentrations, are also provided. Beyond such test systems data, the only required chemical-specific inputs are the lipophilicity of the candidate drug and its ionization state, as determined by the dissociation constants of its acidic or basic groups. This overview is intended to be used by any lab scientist without specific toxicokinetics training to obtain an estimate of fu in a given cell culture medium.

The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods.

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.

Development of a generic zebrafish embryo PBPK model and application to the developmental toxicity assessment of valproic acid analogs.

In order to better explain, predict, or extrapolate to humans the developmental toxicity effects of chemicals to zebrafish (Danio rerio) embryos, we developed a physiologically-based pharmacokinetic (PBPK) model designed to predict organ concentrations of neutral or ionizable chemicals, up to 120 h post-fertilization. Chemicals' distribution is modeled in the cells, lysosomes, and mitochondria of ten organs of the embryo. The model's partition coefficients are calculated with sub-models using physicochemical properties of the chemicals of interest. The model accounts for organ growth and changes in metabolic clearance with time. We compared ab initio model predictions to data obtained on culture medium and embryo concentrations of valproic acid (VPA) and nine analogs during continuous dosing under the OECD test guideline 236. We further improved the predictions by estimating metabolic clearance and partition coefficients from the data by Bayesian calibration. We also assessed the performance of the model at reproducing data published by Brox et al. (2016) on VPA and 16 other chemicals. We finally compared dose-response relationships calculated for mortality and malformations on the basis of predicted whole embryo concentrations versus those based on nominal water concentrations. The use of target organ concentrations substantially shifted the magnitude of dose-response parameters and the relative toxicity ranking of chemicals studied.

Quantitative Systems Toxicology Modeling To Address Key Safety Questions in Drug Development: A Focus of the TransQST Consortium.

Omics data have been increasingly generated with limited demonstrated value in drug safety assessment. The TransQST consortium was launched to use omics and other data in mechanistic-based quantitative systems toxicology (QST) models to evaluate their potential use in species translation.

Towards grouping concepts based on new approach methodologies in chemical hazard assessment: the read-across approach of the EU-ToxRisk project.

Read-across is one of the most frequently used alternative tools for hazard assessment, in particular for complex endpoints such as repeated dose or developmental and reproductive toxicity. Read-across extrapolates the outcome of a specific toxicological in vivo endpoint from tested (source) compounds to "similar" (target) compound(s). If appropriately applied, a read-across approach can be used instead of de novo animal testing. The read-across approach starts with structural/physicochemical similarity between target and source compounds, assuming that similar structural characteristics lead to similar human hazards. In addition, similarity also has to be shown for the toxicokinetic and toxicodynamic properties of the grouped compounds. To date, many read-across cases fail to demonstrate toxicokinetic and toxicodynamic similarities. New concepts, in vitro and in silico tools are needed to better characterise these properties, collectively called new approach methodologies (NAMs). This white paper outlines a general read-across assessment concept using NAMs to support hazard characterization of the grouped compounds by generating data on their dynamic and kinetic properties. Based on the overarching read-across hypothesis, the read-across workflow suggests targeted or untargeted NAM testing also outlining how mechanistic knowledge such as adverse outcome pathways (AOPs) can be utilized. Toxicokinetic models (biokinetic and PBPK), enriched by in vitro parameters such as plasma protein binding and hepatocellular clearance, are proposed to show (dis)similarity of target and source compound toxicokinetics. Furthermore, in vitro to in vivo extrapolation is proposed to predict a human equivalent dose, as potential point of departure for risk assessment. Finally, the generated NAM data are anchored to the existing in vivo data of source compounds to predict the hazard of the target compound in a qualitative and/or quantitative manner. To build this EU-ToxRisk read-across concept, case studies have been conducted and discussed with the regulatory community. These case studies are briefly outlined.

Modeling Exposure to Understand and Predict Kidney Injury.

Exposure is a critically important aspect to consider in the study and management of drug-induced kidney injury. Although blood concentrations of kidney toxicants often may provide a valid surrogate measure of kidney exposure, the kidney has several unique physiological and biochemical properties that lend themselves to accumulation or exclusion of some drugs at sites of toxicity. In such cases, an understanding of these pharmacokinetic mechanisms can be as important as understanding the underlying mechanisms of toxicity. Physiologically based pharmacokinetic models, which mathematically codify such mechanisms in a biologically plausible form, increasingly are being used for developing an understanding of pharmacokinetics across patient populations, drug-drug interactions, and pharmacokinetic-pharmacodynamic relationships. This perspective provides a review of the physiological and biochemical mechanisms as well as the physiochemical properties that theoretically could drive drug accumulation or exclusion within the kidney, along with examples in which these mechanisms have proven important in driving the manifestation of toxicity in vivo. In addition, an overview of the structure, applications, and limitations of existing kidney physiologically based pharmacokinetic models is provided. Finally, a perspective on gaps and associated challenges to such models in the field of toxicology is discussed briefly.

Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue associated with high fat, high sugar diets. However, the molecular mechanisms mediating NAFLD pathogenesis are only partially understood. Here we adopt an iterative multi-scale, systems biology approach coupled to in vitro experimentation to investigate the roles of sugar and fat metabolism in NAFLD pathogenesis. The use of fructose as a sweetening agent is controversial; to explore this, we developed a predictive model of human monosaccharide transport, signalling and metabolism. The resulting quantitative model comprising a kinetic model describing monosaccharide transport and insulin signalling integrated with a hepatocyte-specific genome-scale metabolic network (GSMN). Differential kinetics for the utilisation of glucose and fructose were predicted, but the resultant triacylglycerol production was predicted to be similar for monosaccharides; these predictions were verified by in vitro data. The role of physiological adaptation to lipid overload was explored through the comprehensive reconstruction of the peroxisome proliferator activated receptor alpha (PPARα) regulome integrated with a hepatocyte-specific GSMN. The resulting qualitative model reproduced metabolic responses to increased fatty acid levels and mimicked lipid loading in vitro. The model predicted that activation of PPARα by lipids produces a biphasic response, which initially exacerbates steatosis. Our data support the evidence that it is the quantity of sugar rather than the type that is critical in driving the steatotic response. Furthermore, we predict PPARα-mediated adaptations to hepatic lipid overload, shedding light on potential challenges for the use of PPARα agonists to treat NAFLD.

Correction to: Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease.

[This corrects the article DOI: 10.1186/s12953-018-0131-y.].