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The diversity of microbial species in the gut has a strong influence on health and development of the host. Further, there are indications that the variation in expression of gut bacterial metabolic enzymes is less diverse than the taxonomic profile, underlying the importance of microbiome functionality, particularly from a toxicological perspective. To address these relationships, the gut bacterial composition of Wistar rats was altered by a 28 day oral treatment with the antibiotics tobramycin or colistin sulfate. On the basis of 16S marker gene sequencing data, tobramycin was found to cause a strong reduction in the diversity and relative abundance of the microbiome, whereas colistin sulfate had only a marginal impact. Associated plasma and fecal metabolomes were characterized by targeted mass spectrometry-based profiling. The fecal metabolome of tobramycin-treated animals had a high number of significant alterations in metabolite levels compared to controls, particularly in amino acids, lipids, bile acids (BAs), carbohydrates, and energy metabolites. The accumulation of primary BAs and significant reduction of secondary BAs in the feces indicated that the microbial alterations induced by tobramycin inhibit bacterial deconjugation reactions. The plasma metabolome showed less, but still many alterations in the same metabolite groups, including reductions in indole derivatives and hippuric acid, and furthermore, despite marginal effects of colistin sulfate treatment, there were nonetheless systemic alterations also in BAs. Aside from these treatment-based differences, we also uncovered interindividual differences particularly centering on the loss of Verrucomicrobiaceae in the microbiome, but with no apparent associated metabolite alterations. Finally, by comparing the data set from this study with metabolome alterations in the MetaMapTox database, key metabolite alterations were identified as plasma biomarkers indicative of altered gut microbiomes resulting from a wide activity spectrum of antibiotics.

Cell-based metabolomics provides multiparametric physiologically relevant readouts that can be highly advantageous for improved, biologically based decision making in early stages of compound development. Here, we present the development of a 96-well plate LC-MS/MS-based targeted metabolomics screening platform for the classification of liver toxicity modes of action (MoAs) in HepG2 cells. Different parameters of the workflow (cell seeding density, passage number, cytotoxicity testing, sample preparation, metabolite extraction, analytical method, and data processing) were optimized and standardized to increase the efficiency of the testing platform. The applicability of the system was tested with seven substances known to be representative of three different liver toxicity MoAs (peroxisome proliferation, liver enzyme induction, and liver enzyme inhibition). Five concentrations per substance, aimed at covering the complete dose-response curve, were analyzed and 221 uniquely identified metabolites were measured, annotated, and allocated in 12 different metabolite classes such as amino acids, carbohydrates, energy metabolism, nucleobases, vitamins and cofactors, and diverse lipid classes. Multivariate and univariate analyses showed a dose response of the metabolic effects, a clear differentiation between liver toxicity MoAs and resulted in the identification of metabolite patterns specific for each MoA. Key metabolites indicative of both general and mechanistic specific hepatotoxicity were identified. The method presented here offers a multiparametric, mechanistic-based, and cost-effective hepatotoxicity screening that provides MoA classification and sheds light into the pathways involved in the toxicological mechanism. This assay can be implemented as a reliable compound screening platform for improved safety assessment in early compound development pipelines. Graphical abstract

We describe a strategy using an in vitro metabolomics assay with tubular rat NRK-52E cells to investigate the Modes of Action (MoAs) of nephrotoxic compounds. Chemicals were selected according to their MoAs based on literature information: acetaminophen, 4-aminophenol and S-(trichlorovinyl-)L-cysteine (TCVC), (covalent protein binding); gentamycin, vancomycin, polymycin B and CdCl2 (lysosomal overload) and tenofovir and cidofovir (mitochondrial DNA-interaction). After treatment and harvesting of the cells, intracellular endogenous metabolites were quantified relative to vehicle control. Metabolite patterns were evaluated in a purely data-driven pattern generation process excluding published information. This strategy confirmed the assignment of the chemicals to the respective MoA except for TCVC and CdCl2. Finally, TCVC was defined as unidentified and CdCl2 was reclassified to the MoA "covalent protein binding". Hierarchical cluster analysis of 58 distinct metabolites from the patterns enabled a clear visual separation of chemicals in each MoA. The assay reproducibility was very good and metabolic responses were consistent. These results support the use of metabolome analysis in NRK-52E cells as a suitable tool for understanding and investigating the MoA of nephrotoxicants. This assay could enable the early identification of nephrotoxic compounds and finally reduce animal testing.

Toxicity is not only a function of damage mechanisms, but is also determined by cellular resilience factors. Glutathione has been reported as essential element to counteract negative influences. The present work hence pursued the question how intracellular glutathione can be elevated transiently to render cells more resistant toward harmful conditions. The antibiotic nitrofurantoin (NFT) was identified to stimulate de novo synthesis of glutathione in the human hepatoma cell line, HepG2, and in primary human hepatocytes. In intact cells, activation of NFT yielded a radical anion, which subsequently initiated nuclear-factor-erythroid 2-related-factor-2 (Nrf2)-dependent induction of glutamate cysteine ligase (GCL). Application of siRNA-based intervention approaches confirmed the involvement of the Nrf2-GCL axis in the observed elevation of intracellular glutathione levels. Quantitative activation of Nrf2 by NFT, and the subsequent rise in glutathione, were similar as observed with the potent experimental Nrf2 activator diethyl maleate. The elevation of glutathione levels, observed even 48 h after withdrawal of NFT, rendered cells resistant to different stressors such as the mitochondrial inhibitor rotenone, the redox cycler paraquat, the proteasome inhibitors MG-132 or bortezomib, or high concentrations of NFT. Repurpose of the antibiotic NFT as activator of Nrf2 could thus be a promising strategy for a transient and targeted activation of the endogenous antioxidant machinery.

The gut microbiome is vital to the health and development of an organism, specifically in determining the host response to a chemical (drug) administration. To understand this, we investigated the effects of six antibiotic (AB) treatments (Streptomycin sulfate, Roxithromycin, Sparfloxacin, Vancomycin, Clindamycin and Lincomycin hydrochloride) and diet restriction (–20%) on the gut microbiota in 28-day oral toxicity studies on Wistar rats. The fecal microbiota was determined using 16S rDNA marker gene sequencing. AB-class specific alterations were observed in the bacterial composition, whereas restriction in diet caused no observable difference. These changes associated well with the changes in the LC–MS/MS- and GC–MS-based metabolome profiles, particularly of feces and to a lesser extent of plasma. Particularly strong and AB-specific metabolic alterations were observed for bile acids in both plasma and feces matrices. Although AB-group-specific plasma metabolome changes were observed, weaker associations between fecal and plasma metabolome suggest a profound barrier between them. Numerous correlations between the bacterial families and the fecal metabolites were established, providing a holistic overview of the gut microbial functionality. Strong correlations were observed between microbiota and bile acids, lipids and fatty acids, amino acids and related metabolites. These microbiome–metabolome correlations promote understanding of the functionality of the microbiome for its host.

The use of new approach methodologies (NAMs) in support of read-across (RAx) approaches for regulatory purposes is a main goal of the EU-ToxRisk project. To bring this forward, EU-ToxRisk partners convened a workshop in close collaboration with regulatory representatives from key organizations including European regulatory agencies, such as the European Chemicals Agency (ECHA) and the European Food Safety Authority (EFSA), as well as the Scientific Committee on Consumer Safety (SCCS), national agencies from several European countries, Japan, Canada and the USA, as well as the Organisation for Economic Cooperation and Development (OECD). More than a hundred people actively participated in the discussions, bringing together diverse viewpoints across academia, regulators and industry. The discussion was organized starting from five practical cases of RAx applied to specific problems that offered the oppor-tunity to consider real examples. There was general consensus that NAMs can improve confidence in RAx, in particular in defining category boundaries as well as characterizing the similarities/dissimilarities between source and target substances. In addition to describing dynamics, NAMs can be helpful in terms of kinetics and metabolism that may play an important role in the demonstration of similarity or dissimilarity among the members of a category. NAMs were also noted as effective in providing quanti-tative data correlated with traditional no observed adverse effect levels (NOAELs) used in risk assessment, while reducing the uncertainty on the final conclusion. ​​​​​​​An interesting point of view was the advice on calibrating the number of new tests that should be carefully selected, avoiding the allure of "the more, the better". Unfortunately, yet unsurprisingly, there was no single approach befitting every case, requiring careful analysis delineating the optimal approach. Expert analysis and assessment of each specific case is still an important step in the process.

To elucidate if artificial sweeteners modify fecal bacterial composition and the fecal and plasma metabolomes, Wistar rats from both sexes were treated for 28 days with acesulfame potassium (40 and 120 mg/kg body weight) and saccharin (20 and 100 mg/kg body weight). Targeted MS-based metabolome profiling (plasma and feces) and fecal 16S gene sequencing were conducted. Both sweeteners exhibited only minor effects on the fecal metabolome and microbiota. Saccharin treatment significantly altered amino acids, lipids, energy metabolism and specifically, bile acids in the plasma metabolome. Additionally, sex-specific differences were observed for conjugated primary and secondary bile acids. Acesulfame potassium treated male rats showed larger alterations in glycine conjugated primary and secondary bile-acids than females. Other changes in the plasma metabolome were more profound for saccharin than acesulfame potassium, for both sexes. Changes in conjugated bile-acids in plasma, which are often associated with microbiome changes, and the absence of similarly large changes in microbiota suggest an adaptative change of the latter, rather than toxicity. Further studies with a high resolution 16S sequencing data and/or metagenomics approach, with particular emphasis on bile acids, will be required to explore the mechanisms driving this metabolic outcome of saccharin in Wistar rats.

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

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. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Drug-induced liver injury (DILI) is the most prevalent adversity encountered in drug development and clinical settings leading to urgent needs to understand the underlying mechanisms. In this study, we have systematically investigated the dynamics of the activation of cellular stress response pathways and cell death outcomes upon exposure of a panel of liver toxicants using live cell imaging of fluorescent reporter cell lines. We established a comprehensive temporal dynamic response profile of a large set of BAC-GFP HepG2 cell lines representing the following components of stress signaling: i) unfolded protein response (UPR) [ATF4, XBP1, BIP and CHOP]; ii) oxidative stress [NRF2, SRXN1, HMOX1]; iii) DNA damage [P53, P21, BTG2, MDM2]; and iv) NF-κB pathway [A20, ICAM1]. We quantified the single cell GFP expression as a surrogate for endogenous protein expression using live cell imaging over > 60 h upon exposure to 14 DILI compounds at multiple concentrations. Using logic-based ordinary differential equation (Logic-ODE), we modelled the dynamic profiles of the different stress responses and extracted specific descriptors potentially predicting the progressive outcomes. We identified the activation of ATF4-CHOP axis of the UPR as the key pathway showing the highest correlation with cell death upon DILI compound perturbation. Knocking down main components of the UPR provided partial protection from compound-induced cytotoxicity, indicating a complex interplay among UPR components as well as other stress pathways. Our results suggest that a systematic analysis of the temporal dynamics of ATF4-CHOP axis activation can support the identification of DILI risk for new candidate drugs. published

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field. © 2017, Springer-Verlag GmbH Germany.

Only few cell-based test methods are described by Organisation for Economic Co-operation and Development (OECD) test guidelines or other regulatory references (e.g., the European Pharmacopoeia). The majority of toxicity tests still falls into the category of non-guideline methods. Data from these tests may nevertheless be used to support regulatory decisions or to guide strategies to assess compounds (e.g., drugs, agrochemicals) during research and development if they fulfill basic requirements concerning their relevance, reproducibility and predictivity. Only a method description of sufficient clarity and detail allows interpretation and use of the data. To guide regulators faced with increasing amounts of data from non-guideline studies, the OECD formulated Guidance Document 211 (GD211) on method documentation for the purpose of safety assessment. As GD211 is targeted mainly at regulators, it leaves scientists less familiar with regulation uncertain as to what level of detail is required and how individual questions should be answered. Moreover, little attention was given to the description of the test system (i.e., cell culture) and the steps leading to it being established in the guidance. To address these issues, an annotated toxicity test method template (ToxTemp) was developed (i) to fulfill all requirements of GD211, (ii) to guide the user concerning the types of answers and detail of information required, (iii) to include acceptance criteria for test elements, and (iv) to define the cells sufficiently and transparently. The fully annotated ToxTemp is provided here, together with reference to a database containing exemplary descriptions of more than 20 cell-based tests.

Read-across (RAx) translates available information from well-characterized chemicals tothe substance for which there is a toxicological data gap. The OECD is working on case studies to probe general applicability of RAx, and several regulations (e.g. EU-REACH) already allow this procedure to be used to waive new in vivotests. The decision to prepare a review on the state of the art of RAx as a tool for risk assessment for regulatory purposes was taken during a workshop with international experts in Ranco, Italy in July 2018. Three major issues were identified that need optimisation to allowa higher regulatory acceptance rate of the RAx procedure: (i) the definition of similarity of source and target, (ii) the translation of biological/toxicological activity of source to target, in the RAx procedure, and (iii) how to deal with issues of ADMEthat may differ between source and target. The use of new approach methodologies (NAM) was discussed as one of the most important innovations to improve the acceptability of RAx. At present, NAM data may be used to confirm chemical and toxicological similarity. In the future, the use of NAM may be broadened to fully characterize the hazard and toxicokinetic properties of RAx compounds. Concerning available guidance, documents on Good Read-Across Practice (GRAP) and on best practices to perform and evaluatethe RAx process were identified. Here, in particular the RAx guidance, being worked out by the European Commission’s H2020 project EU-ToxRisk, together with many external partners with regulatory experience, is given.

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

Transcriptomics is developing into an invaluable tool in toxicology. The aim of this study was, using a transcriptomics approach, to identify genes that respond similar to many different chemicals (including drugs and industrial compounds) in both rat liver in vivo and in cultivated hepatocytes. For this purpose, we analyzed Affymetrix microarray expression data from 162 compounds that were previously tested in a concentration-dependent manner in rat livers in vivo and in rat hepatocytes cultivated in sandwich culture. These data were obtained from the Japanese Toxicogenomics Project (TGP) and North Rhine-Westphalian (NRW) data sets, which represent 138 and 29 compounds, respectively, and have only 5 compounds in common between them. The in vitro gene expression data from the NRW data set were generated in the present study, while TGP is publicly available. For each of the data sets, the overlap between up- or down-regulated genes in vitro and in vivo was identified, and named in vitro-in vivo consensus genes. Interestingly, the in vivo-in vitro consensus genes overlapped to a remarkable extent between both data sets, and were 21-times (upregulated genes) or 12-times (down-regulated genes) enriched compared to random expectation. Finally, the genes in the TGP and NRW overlap were used to identify the upregulated genes with the highest compound coverage, resulting in a seven-gene set of Cyp1a1, Ugt2b1, Cdkn1a, Mdm2, Aldh1a1, Cyp4a3, and Ehhadh. This seven-gene set was then successfully tested with structural analogues of valproic acid that are not present in the TGP and NRW data sets. In conclusion, the seven-gene set identified in the present study responds similarly in vitro and in vivo to a wide range of different chemicals. Despite these promising results with the seven-gene set, transcriptomics with cultivated rat hepatocytes remains a challenge, because in general many genes are up- or downregulated by in vitro culture per se, respond differently to test compounds in vitro and in vivo, and/or show higher variability in the in vitro system compared to the corresponding in vivo data. published

Hexamoll

‘Omics technologies are gaining importance to support regulatory toxicity studies. Prerequisites for performing ‘omics studies considering GLP principles were discussed at the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) Workshop Applying ‘omics technologies in Chemical Risk Assessment. A GLP environment comprises a standard operating procedure system, proper pre-planning and documentation, and inspections of independent quality assurance staff. To prevent uncontrolled data changes, the raw data obtained in the respective ‘omics data recording systems have to be specifically defined. Further requirements include transparent and reproducible data processing steps, and safe data storage and archiving procedures. The software for data recording and processing should be validated, and data changes should be traceable or disabled. GLP-compliant quality assurance of ‘omics technologies appears feasible for many GLP requirements. However, challenges include (i) defining, storing, and archiving the raw data; (ii) transparent descriptions of data processing steps; (iii) software validation; and (iv) ensuring complete reproducibility of final results with respect to raw data. Nevertheless, ‘omics studies can be supported by quality measures (e.g., GLP principles) to ensure quality control, reproducibility and traceability of experiments. This enables regulators to use ‘omics data in a fit-for-purpose context, which enhances their applicability for risk assessment.

Liver toxicity is a leading systemic toxicity of drugs and chemicals demanding more human-relevant, high throughput, cost effective in vitro solutions. In addition to contributing to animal welfare, in vitro techniques facilitate exploring and understanding the molecular mechanisms underlying toxicity. New ‘omics technologies can provide comprehensive information on the toxicological mode of action of compounds, as well as quantitative information about the multi-parametric metabolic response of cellular systems in normal and patho-physiological conditions. Here, we combined mass-spectroscopy metabolomics with an in vitro liver toxicity model. Metabolite profiles of HepG2 cells treated with 35 test substances resulted in 1114 cell supernatants and 3556 intracellular samples analyzed by metabolomics. Control samples showed relative standard deviations of about 10–15%, while the technical replicates were at 5–10%. Importantly, this procedure revealed concentration–response effects and patterns of metabolome changes that are consistent for different liver toxicity mechanisms (liver enzyme induction/inhibition, liver toxicity and peroxisome proliferation). Our findings provide evidence that identifying organ toxicity can be achieved in a robust, reliable, human-relevant system, representing a non-animal alternative for systemic toxicology. Electronic supplementary material The online version of this article (doi:10.1007/s00204-017-2079-6) contains supplementary material, which is available to authorized users.

The effects of seven nanomaterials (four amorphous silicon dioxides with or without surface functionalization, two surface-functionalized zirconium dioxides, and barium sulfate) upon 28-day oral exposure to male or female rats were investigated. The studies were performed as limit tests in accordance with OECD Test Guideline 407 applying 1,000 mg test substance/kg body weight/day. Additionally, the acute phase proteins haptoglobin and α2-macroglobulin as well as cardiac troponin I were determined, and metabolome analysis was performed in plasma samples. There were no test substance-related adverse effects for any of the seven nanomaterials. Moreover, metabolomics changes were below the threshold of effects. Since test substance organ burden was not analyzed, it was not possible to establish whether the lack of findings related to the absence of systemic exposure of the tested nanomaterials or if the substances are devoid of any potential for toxicity. The few published subacute oral or short-term inhalation studies investigating comparable nanomaterials (SiO2, ZrO2, and BaSO4) also do not report the occurrence of pronounced treatment-related findings. Overall, the results of the present survey provide a first indication that the tested nanomaterials neither cause local nor systemic effects upon subacute oral administration under the selected experimental conditions. Further investigations should aim at elucidating the extent of gastrointestinal absorption of surface-functionalized nanomaterials. Electronic supplementary material The online version of this article (doi:10.1007/s00204-014-1337-0) contains supplementary material, which is available to authorized users.

Most endocrine disruptors interact with hormone receptors or steroid biosynthesis and metabolism, thereby modifying the physiological function of endogenous hormones. Here, we present an alternative testing paradigm for detection of endocrine modes of action that replace and reduce animal testing through refinement. Receptor mediated endocrine effects were assessed using the yeast-based receptor-mediated transcriptional activation YES/YAS assays and effects on steroid hormone biosynthesis were assessed using the human cell line H295R in the steroidogenesis assay. In our testing paradigm we propose to complement the in vitro assays with a single in vivo repeated dose study in which plasma samples are analyzed for their metabolome profile in addition to classical parameters such as histopathology. The combination of these methods does not only contribute to refinement and reduction of animal testing, but also has significantly increased the efficient allocation of resources and allows for a sound assessment of the endocrine disruption potential of compounds. Thus, this proposal constitutes a potentially attractive alternative to EPA’s Endocrine Disruptor Screening Program to identify mammalian, systemic endocrine modes of action. Data on 14 reference substances for which the in vitro YES/YAS and steroidogenesis assays and the in vivo metabolome analysis were performed to assess their putative endocrine modes of action are presented here.

The large-scale EU-ToxRisk project is an integrated European 'flagship' program with the vision to establish a paradigm-shift in toxicity testing and risk assessment for the 21st century by implementing mechanism-based integrated testing strategies using non-animal new approach methods (NAMs). To accomplish this the EU-ToxRisk project has united all relevant scientific disciplines covering in silico QSAR modelling, cellular toxicology, bioinformatics and PBPK modelling. We test the integration of the different NAMs in various case studies, ultimately establishing: (i) pragmatic, read-across procedures incorporating mechanistic and toxicokinetic knowledge; and (ii) ab initio hazard and risk assessment strategies of chemicals with little background information. Here we report on the results of several EU-ToxRisk read across case studies that are focused on repeated dose systemic toxicity (RDT) as well as developmental/reproduction toxicity (DART). The integration of the various NAMs in defined read across case studies allows the assessment of the overall applicability domain and contribution of these NAMs in read across approaches chemical hazard and ultimate risk assessment. Case studies are centred around several chemical groups with structural similarity and related to specific in vivo toxicity endpoints e.g. (i) microvesicular liver steatosis induced by valproic acid analogues; (ii) the prediction of teratogenic effects of valproic acid analogues; (iii) lung toxicity induced by diketones. The results established by our NAM toolbox indicate that structural similar compounds which show equal in vivo rodent toxicity also demonstrate similar responses in experimental systems in vitro. Therefore we propose that the application of NAMs can provide biological support for read across. Further challenges will be discussed.

The integrated European project, EU-ToxRisk, proudly sees itself as "flagship" exploring new alternative-to-animal approaches to chemical safety evaluation. It promotes mechanism-based toxicity testing and risk assessment according to the principles laid down for toxicology for the twenty-first century. The project was officially launched in January 2016 with a kickoff meeting in Egmond aan Zee, the Netherlands. Over 100 scientists representing academia and industry as well as regulatory authorities attended the inaugural meeting. The project will integrate advances in in vitro and in silico toxicology, read-across methods, and adverse outcome pathways. EU-ToxRisk will continue to make use of the case study strategy deployed in SEURAT-1, a FP7 initiative ended in December 2015. Even though the development of new non-animal methods is one target of EU-ToxRisk, the project puts special emphasis on their acceptance and implementation in regulatory contexts. This €30 million Horizon 2020 project involves 38 European partners and one from the USA. EU-ToxRisk aims at the "development of a new way of risk assessment." published

Metabolomics is a valuable tool to gain mechanistic insight into biological processes. It is frequently used to obtain complementary details to other ‘omics technologies such as transcriptomics or proteomics. For knowledge generation, reproducible measurements of physiological, intact, and artifact-free metabolite levels are imperative necessitating further standardization of best practices to improve reliability of research outcomes. Here we report a novel cell sample preparation method (MxP® CellCollect) for metabolomics applications using adherent mammalian cells, which reduces the time consumption and physiological stress of conventional methods such as trypsinization or cell scraping. The most common sampling procedures to detach cells from their growth surface, trypsinization and scraping were compared to the MxP® CellCollect method investigating metabolite profiles of two breast cancer cell lines (MDA-MB-231 and MCF7). Metabolite levels as well as direction of metabolite changes differed tremendously revealing issues with trypsinization and scraping risking non-physiological or misleading results in contrast to MxP® CellCollect. Differences in metabolic profiles of cells harvested by trypsinization as compared to MxP® CellCollect or scraping can be directly attributed to prolonged, medium-free incubation time during cell detachment leading to a severely energy-depleted intracellular state. Labile metabolites or metabolites with fast intracellular turnover rates such as glycolysis and TCA cycle intermediates were strongly and significantly decreased by trypsinization. The same was true for amino acids and nucleoside triphosphates. Results obtained with scraping using methanol as solvent were multifaceted. Even mild evaporation of methanol prior metabolite extraction led to temperature- and/or light-dependent degradation of labile metabolites such as nucleoside triphosphates into di- and monophosphates liberating pyrophosphate. Furthermore, lipid metabolites, in particular cell membrane lipids, were found to have significantly lower levels than measured by trypsinization or MxP® CellCollect, indicating that lipid metabolites are insufficiently detached and/or unspecifically adsorb to the hydrophobic dish and scraping tool.

Early and accurate pre-clinical and clinical biomarkers of hepatotoxicity facilitate the drug development process and the safety monitoring in clinical studies. We selected eight known model compounds to be administered to male Wistar rats to identify biomarkers of drug induced liver injury (DILI) using transcriptomics, metabolite profiling (metabolomics) and conventional endpoints. We specifically explored early biomarkers in serum and liver tissue associated with histopathologically evident acute hepatotoxicity. A tailored data analysis strategy was implemented to better differentiate animals with no treatment-related findings in the liver from animals showing evident hepatotoxicity as assessed by histopathological analysis. From the large number of assessed parameters, our data analysis strategy allowed us to identify five metabolites in serum and five in liver tissue, 58 transcripts in liver tissue and seven clinical chemistry markers in serum that were significantly associated with acute hepatotoxicity. The identified markers comprised metabolites such as taurocholic acid and putrescine (measured as sum parameter together with agmatine), classical clinical chemistry markers like AST (aspartate aminotransferase), ALT (alanine aminotransferase), and bilirubin, as well as gene transcripts like Igfbp1 (insulin-like growth factor-binding protein 1) and Egr1 (early growth response protein 1). The response pattern of the identified biomarkers was concordant across all types of parameters and sample matrices. Our results suggest that a combination of several of these biomarkers could significantly improve the robustness and accuracy of an early diagnosis of hepatotoxicity.

In the late 1980s vinclozolin was tested for prenatal developmental toxicity in rats for registration purposes in USA. At 1000 mg/kg bw, 95% of all fetuses were female upon visual inspection (ano-genital distance determination). Anti-androgenic effects (AA) were also noted in a subsequent 2-generation study. These findings triggered mechanistic investigations at BASF and at US-EPA. Results published by the latter were the starting point of the endocrine disruption (ED) discussion in the 1990s. AA effects of vinclozolin are mediated by two metabolites, which have an antagonistic effect on the androgen receptor. Currently, determination of ED has become a major end-point in toxicology testing and the US-EPA has set up an elaborated testing paradigm to fulfill this requirement. Future screening for ED can be improved making use of new technologies. ED modes of action can be determined by three alternative (3R) methods. Steroid synthesis in H295R cells (1), androgen-receptor binding in modified yeast (2) and metabolomics (3). Using vinclozolin as a case study, results indicate: (1) an effect on steroid synthesis in vitro, (2) an antagonistic effect on the androgen receptor and (3) that the metabolome profile of vinclozolin is similar to that of other receptor mediated anti-androgens (e.g. flutamide).

In spite of over 20 years of effort, no single in vitro assay has been developed and validated as a full regulatory replacement for the Draize Eye Irritation test. However, companies have been using in vitro methods to screen new formulations and in some cases as their primary assessment of eye irritation potential for many years. The present report shows the outcome of an Expert Meeting convened by the European Centre for the Validation of Alternative Methods in February 2005 to identify test strategies for eye irritation. In this workshop test developers/users were requested to nominate methods to be considered as a basis for the identification of such testing strategies. Assays were evaluated and categorized based on their proposed applicability domains (e.g., categories of irritation severity, modes of action, chemical class, physicochemical compatibility). The analyses were based on the data developed from current practice and published studies, the ability to predict depth of injury (within the applicable range of severity), modes of action that could be addressed and compatibility with different physiochemical forms. The difficulty in predicting the middle category of irritancy (e.g. R36, GHS Categories 2A and 2B) was recognized. The testing scheme proposes using a Bottom-Up (begin with using test methods that can accurately identify non-irritants) or Top-Down (begin with using test methods that can accurately identify severe irritants) progression of in vitro tests (based on expected irritancy). Irrespective of the starting point, the approach would identify non-irritants and severe irritants, leaving all others to the (mild/moderate) irritant GHS 2/R36 categories. © 2009 Elsevier Ltd.

BASF’s Experimental Toxicology and Ecology unit and metanomics GmbH implemented a project to predict toxicological risks by measuring metabolite profiles in rat plasma from short-term repeated dose studies in rats. Metabolome analysis in plasma was performed after 7, 14 and 28 days and relative endogenous metabolite levels in treated rats versus controls were analyzed. Sets of common metabolite level changes were arranged to characterize several toxicological MOAs (so-called MOA patterns). A MetaMapTox databasewithmore than 500 reference compounds was developed. Some chemicals can be produced as mixtures or as pure enantiomers. The chiral properties of the molecules may have different effects on biological entities. The purpose of this studywas to compare toxicological properties of mixtures and their corresponding pure enantiomers regarding metabolite levels. Metabolome analysis of two different mixtures and their respective enantiomers indicated no biological relevant differences regarding thequalitative toxicity towards the assumed target organs as well as the quantitative amount of the toxicity, thereby confirming the toxicity equivalence of the enantiomers. The present results can be seen as proof of concept for the use of metabolomics concerning toxicological assessment of enantiomers. For complete evaluation, it will be interesting to test more enantiomers with different toxicological properties.