Systems Toxicology: The Future of Risk Assessment

Physiological and transcriptomic effects of hexafluoropropylene oxide dimer acid in Caenorhabditis elegans during development

Per- and polyfluoroalkyl substances (PFAS) are chemicals resistant to degradation. While such a feature is desirable in consumer and industrial products, some PFAS, including perfluorooctanoic acid (PFOA), are toxic and bioaccumulate. Hexafluoropropylene oxide dimer acid (HFPO-DA), an emerging PFAS developed to replace PFOA, has not been extensively studied. To evaluate the potential toxicity of HFPO-DA with a cost- and time-efficient approach, we exposed C. elegans larvae for 48 h to 4 × 10^-9-4 g/L HFPO-DA in liquid media and measured developmental, behavioral, locomotor, and transcriptional effects at various exposure levels. Worms exposed to 1.5-4 g/L HFPO-DA were developmentally delayed, and progeny production was significantly delayed (p < 0.05) in worms exposed to 2-4 g/L HFPO-DA. Statistically significant differential gene expression was identified in all fourteen HFPO-DA exposure groups ranging from 1.25 × 10^-5 to 4 g/L, except for 6.25 × 10^-5 g/L. Among 10298 analyzed genes, 2624 differentially expressed genes (DEGs) were identified in the developmentally delayed 4 g/L group only, and 78 genes were differentially expressed in at least one of the thirteen groups testing 1.25 × 10^-5-2 g/L HFPO-DA exposures. Genes encoding for detoxification enzymes including cytochrome P450 and UDP glucuronosyltransferases were upregulated in 0.25-4 g/L acute exposure groups. DEGs were also identified in lower exposure level groups, though they did not share biological functions except for six ribosomal protein-coding genes. While our transcriptional data is inconclusive to infer mechanisms of toxicity, the significant gene expression differences at 1.25 × 10^-5 g/L, the lowest concentration tested for transcriptional changes, calls for further targeted analyses of low-dose HFPO-DA exposure effects.

Reciprocal interactions between anthropogenic stressors and insect microbiota

Insects play many important roles in nature due to their diversity, ecological role, and impact on agriculture or human health. They are directly influenced by environmental changes and in particular anthropic activities that constitute an important driver of change in the environmental characteristics. Insects face numerous anthropogenic stressors and have evolved various detoxication mechanisms to survive and/or resist to these compounds. Recent studies highligted the pressure exerted by xenobiotics on insect life-cycle and the important role of insect-associated bacterial microbiota in the insect responses to environmental changes. Stressor exposure can have various impacts on the composition and structure of insect microbiota that in turn may influence insect biology. Moreover, bacterial communities associated with insects can be directly or indirectly involved in detoxification processes with the selection of certain microorganisms capable of degrading xenobiotics. Further studies are needed to assess the role of insect-associated microbiota as key contributor to the xenobiotic metabolism and thus as a driver for insect adaptation to polluted habitats.

The Evolution of Regulatory Toxicology: Where is the Gardener?

There is a need for paradigm change in the methodology employed for toxicological testing and assessment. It could be said that this change is well on its way, through an evolutionary progress analogous to that of natural selection. Darwin's Theory of Evolution has defined the idea of evolution and descendancy since the last third of the 19th century. Increasingly, this concept of 'evolution' is being applied beyond the field of biology. This Comment article discusses the progress of toxicological testing in the context of 'evolutionary pressure' and deliberates how this process can help foster the development, implementation and acceptance of mechanistic and human-relevant methods in this field. By comparing the current regulatory landscape in toxicity testing and assessment to specific elements in Charles Darwin's evolutionary theory, we aim to better understand the needs and requirements for the future.

Setting the stage for next-generation risk assessment with non-animal approaches: the EU-ToxRisk project experience

In 2016, the European Commission launched the EU-ToxRisk research project to develop and promote animal-free approaches in toxicology. The 36 partners of this consortium used in vitro and in silico methods in the context of case studies (CSs). These CSs included both compounds with a highly defined target (e.g. mitochondrial respiratory chain inhibitors) as well as compounds with poorly defined molecular initiation events (e.g. short-chain branched carboxylic acids). The initial project focus was on developing a science-based strategy for read-across (RAx) as an animal-free approach in chemical risk assessment. Moreover, seamless incorporation of new approach method (NAM) data into this process (= NAM-enhanced RAx) was explored. Here, the EU-ToxRisk consortium has collated its scientific and regulatory learnings from this particular project objective. For all CSs, a mechanistic hypothesis (in the form of an adverse outcome pathway) guided the safety evaluation. ADME data were generated from NAMs and used for comprehensive physiological-based kinetic modelling. Quality assurance and data management were optimized in parallel. Scientific and Regulatory Advisory Boards played a vital role in assessing the practical applicability of the new approaches. In a next step, external stakeholders evaluated the usefulness of NAMs in the context of RAx CSs for regulatory acceptance. For instance, the CSs were included in the OECD CS portfolio for the Integrated Approach to Testing and Assessment project. Feedback from regulators and other stakeholders was collected at several stages. Future chemical safety science projects can draw from this experience to implement systems toxicology-guided, animal-free next-generation risk assessment.

State-of-the-art methods and devices for the generation, exposure, and collection of aerosols from heat-not-burn tobacco products

Tobacco harm reduction is increasingly recognized as a promising approach to accelerate the decline in smoking prevalence and smoking-related population harm. Potential modified risk tobacco products (MRTPs) must undergo a rigorous premarket toxicological risk assessment. The ability to reproducibly generate, collect, and use aerosols is critical for the characterization, and preclinical assessment of aerosol-based candidate MRTPs (cMRTPs), such as noncombusted cigarettes, also referred to as heated tobacco products, tobacco heating products, or heat-not-burn (HNB) tobacco products. HNB tobacco products generate a nicotine-containing aerosol by heating tobacco instead of burning it. The aerosols generated by HNB products are qualitatively and quantitatively highly different from cigarette smoke (CS). This constitutes technical and experimental challenges comparing the toxicity of HNB aerosols with CS. The methods and experimental setups that have been developed for the study of CS cannot be directly transposed to the study of HNB aerosols. Significant research efforts are dedicated to the development, characterization, and validation of experimental setups and methods suitable for HNB aerosols. They are described in this review, with a particular focus on the Tobacco Heating System version 2.2. This is intended to support further studies, the objective evaluation and verification of existing evidence, and the development of scientifically substantiated HNB MRTPs.

Vision of a near future: Bridging the human health-environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment

There is a growing recognition that application of mechanistic approaches to understand cross-species shared molecular targets and pathway conservation in the context of hazard characterization, provide significant opportunities in risk assessment (RA) for both human health and environmental safety. Specifically, it has been recognized that a more comprehensive and reliable understanding of similarities and differences in biological pathways across a variety of species will better enable cross-species extrapolation of potential adverse toxicological effects. Ultimately, this would also advance the generation and use of mechanistic data for both human health and environmental RA. A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions. Thanks to a thorough dialogue among all participants, key challenges, current gaps and research needs were identified, and potential solutions proposed. This discussion highlighted the common objective to progress toward more predictive, mechanistically based, data-driven and animal-free chemical safety assessments. Overall, the participants recognized that there is no single approach which would provide all the answers for bridging the gap between mechanism-based human health and environmental RA, but acknowledged we now have the incentive, tools and data availability to address this concept, maximizing the potential for improvements in both human health and environmental RA.

A Quantitative Source-to-Outcome Case Study To Demonstrate the Integration of Human Health and Ecological End Points Using the Aggregate Exposure Pathway and Adverse Outcome Pathway Frameworks

Exposure to environmental contaminants can lead to adverse outcomes in both human and nonhuman receptors. The Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) frameworks can mechanistically inform cumulative risk assessment for human health and ecological end points by linking together environmental transport and transformation, external exposure, toxicokinetics, and toxicodynamics. This work presents a case study of a hypothetical contaminated site to demonstrate a quantitative approach for implementing the AEP framework and linking this framework to AOPs. We construct an AEP transport and transformation model and then quantify external exposure pathways for humans, fishes, and small herbivorous mammals at the hypothetical site. A Monte Carlo approach was used to address parameter variability. Source apportionment was quantified for each species, and published pharmacokinetic models were used to estimate internal target site exposure from external exposures. Published dose-response data for a multispecies AOP network were used to interpret AEP results in the context of species-specific effects. This work demonstrates (1) the construction, analysis, and application of a quantitative AEP model, (2) the utility of AEPs for organizing mechanistic exposure data and highlighting data gaps, and (3) the advantages provided by a source-to-outcome construct for leveraging exposure data and to aid transparency regarding assumptions.

An overview of the current progress, challenges, and prospects of human biomonitoring and exposome studies

Human Biomonitoring (HB), the process for determining whether and to what extent chemical substances penetrated our bodies, serves as a useful tool to quantify human exposure to pollutants. In cases of nutrition and physiologic status, HB plays a critical role in the identification of excess or deficiency of essential nutrients. In pollutant HB studies, levels of substances measured in body fluids (blood, urine, and breast milk) or tissues (hair, nails or teeth) aid in the identification of potential health risks or associated adverse effects. However, even as a widespread practice in several countries, most HB studies reflect exposure to a single compound or mixtures which are measured at a single time point in lifecycle. On the other hand, throughout an individual's lifespan, the contact with different physical, chemical, and social stressors occurs at varying intensities, differing times and durations. Further, the interaction between stressors and body receptors leads to dynamic responses of the entire biological system including proteome, metabolome, transcriptome, and adductome. Bearing this in mind, a relatively new vision in exposure science, defined as the exposome, is postulated to expand the traditional practice of measuring a single exposure to one or few chemicals at one-time point to an approach that addresses measures of exposure to multiple stressors throughout the lifespan. With the exposome concept, the science of exposure advances to an Environment-Wide Association Perspective, which might exhibit a stronger relationship with good health or disease conditions for an individual (phenotype). Thus, this critical review focused on the current progress of HB and exposome investigations, anticipating some challenges, strategies, and future needs to be taken into account for designing future surveys.

Perspectives on In Vitro to In Vivo Extrapolations

Quantitative in vitro to in vivo extrapolation (QIVIVE) is broadly considered a prerequisite bridge from in vitro findings to a dose paradigm. Quality and relevance of cell systems are the first prerequisite for QIVIVE. Information-rich and mechanistic endpoints (biomarkers) improve extrapolations, but a sophisticated endpoint does not make a bad cell model a good one. The next need is reverse toxicokinetics (TK), which estimates the dose necessary to reach a tissue concentration that is active in vitro. The Johns Hopkins Center for Alternatives to Animal Testing (CAAT) has created a roadmap for animal-free systemic toxicity testing, in which the needs and opportunities for TK are elaborated, in the context of different systemic toxicities. The report was discussed at two stakeholder forums in Brussels in 2012 and in Washington in 2013; the key recommendations are summarized herein. Contrary to common belief and the Paracelsus paradigm of everything is toxic, the majority of industrial chemicals do not exhibit toxicity. Strengthening the credibility of negative results of alternative approaches for hazard identification, therefore, avoids the need for QIVIVE. Here, especially the combination of methods in integrated testing strategies is most promising. Two further but very different approaches aim to overcome the problem of modeling in vivo complexity: The human-on-a-chip movement aims to reproduce large parts of living organism's complexity via microphysiological systems, that is, organ equivalents combined by microfluidics. At the same time, the Toxicity Testing in the 21st Century (Tox-21c) movement aims for mechanistic approaches (adverse outcome pathways as promoted by Organisation for Economic Co-operation and Development (OECD) or pathways of toxicity in the Human Toxome Project) for high-throughput screening, biological phenotyping, and ultimately a systems toxicology approach through integration with computer modeling. These 21st century approaches also require 21st century validation, for example, by evidence-based toxicology. Ultimately, QIVIVE is a prerequisite for extrapolating Tox-21c such approaches to human risk assessment.

A 90-day OECD TG 413 rat inhalation study with systems toxicology endpoints demonstrates reduced exposure effects of the aerosol from the carbon heated tobacco product version 1.2 (CHTP1.2) compared with cigarette smoke. II. Systems toxicology assessment

Modified risk tobacco products (MRTPs) have the potential to reduce smoking-related health risks. The Carbon Heated Tobacco Product 1.2 (CHTP1.2) is a potential MRTP that uses a pressed carbon heat source to generate an aerosol by heating tobacco. Here, we report the results from the systems toxicology arm of a 90-day rat inhalation study (OECD test guideline 413) to assess the effects of CHTP1.2 aerosol compared with cigarette smoke (CS). Transcriptomics, proteomics, and lipidomics analyses complemented the standard endpoints. In the respiratory nasal epithelium, CS induced an adaptive tissue and inflammatory response, which was much weaker after CHTP1.2 aerosol exposure, mostly limited to the highest CHTP1.2 concentration (at twice the 3R4F CS concentration: 50 vs. 23 μg nicotine/L), in female rats. In the lungs, the effects of CS exposure included inflammatory and cellular stress responses, which were absent or much lower after CHTP1.2 aerosol exposure. Outside of the respiratory tract, CS and CHTP1.2 aerosol induced effects that were previously associated with exposure to any nicotine-containing aerosol, e.g., lower lipid concentrations in serum. Overall, this systems toxicology analysis complements and confirms the results from classical toxicological endpoints and further suggests potentially reduced respiratory health risks of CHTP1.2.

In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

During drug development, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future.

3S - Systematic, systemic, and systems biology and toxicology

A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary ¹³C-metabolic flux analysis (INST ¹³C-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

New animal-free concepts and test methods for developmental toxicity and peripheral neurotoxicity

The complex toxicological fields of repeat dose organ toxicity (RDT) and developmental and reproductive toxicity (DART) still require new concepts and approaches to achieve a fully animal-free safety assessment of chemicals. One novel approach is the generation of relevant human cell types from pluripotent stem cells, and the use of such cells for the establishment of phenotypic test methods. Due to their broad endpoints, such tests capture multiple types of toxicants, i.e. they are a readout for the activation of many adverse outcome pathways (AOPs). The 2016 Lush Science Prize was awarded for the development of one such assay, the PeriTox test, which uses human peripheral neurons generated from stem cells. The assay endpoints measure various cell functions, and these give information on the potential neurotoxicity and developmental neurotoxicity hazard of test compounds. The PeriTox test method has a high predictivity and sensitivity for peripheral neurotoxicants, and thus addresses the inherent challenges in pesticide testing and drug development. Data from the test can be obtained quickly and at a relatively high-throughput, and thus, the assay has the potential to replace animal-based safety assessment during early product development or for screening potential environmental toxicants.

Crowd-Sourced Verification of Computational Methods and Data in Systems Toxicology: A Case Study with a Heat-Not-Burn Candidate Modified Risk Tobacco Product

Systems toxicology intends to quantify the effect of toxic molecules in biological systems and unravel their mechanisms of toxicity. The development of advanced computational methods is required for analyzing and integrating high throughput data generated for this purpose as well as for extrapolating predictive toxicological outcomes and risk estimates. To ensure the performance and reliability of the methods and verify conclusions from systems toxicology data analysis, it is important to conduct unbiased evaluations by independent third parties. As a case study, we report here the results of an independent verification of methods and data in systems toxicology by crowdsourcing. The sbv IMPROVER systems toxicology computational challenge aimed to evaluate computational methods for the development of blood-based gene expression signature classification models with the ability to predict smoking exposure status. Participants created/trained models on blood gene expression data sets including smokers/mice exposed to 3R4F (a reference cigarette) or noncurrent smokers/Sham (mice exposed to air). Participants applied their models on unseen data to predict whether subjects classify closer to smoke-exposed or nonsmoke exposed groups. The data sets also included data from subjects that had been exposed to potential modified risk tobacco products (MRTPs) or that had switched to a MRTP after exposure to conventional cigarette smoke. The scoring of anonymized participants' predictions was done using predefined metrics. The top 3 performers' methods predicted class labels with area under the precision recall scores above 0.9. Furthermore, although various computational approaches were used, the crowd's results confirmed our own data analysis outcomes with regards to the classification of MRTP-related samples. Mice exposed directly to a MRTP were classified closer to the Sham group. After switching to a MRTP, the confidence that subjects belonged to the smoke-exposed group decreased significantly. Smoking exposure gene signatures that contributed to the group separation included a core set of genes highly consistent across teams such as AHRR, LRRN3, SASH1, and P2RY6. In conclusion, crowdsourcing constitutes a pertinent approach, in complement to the classical peer review process, to independently and unbiasedly verify computational methods and data for risk assessment using systems toxicology.

Stem Cell Transcriptome Responses and Corresponding Biomarkers That Indicate the Transition from Adaptive Responses to Cytotoxicity

Analysis of transcriptome changes has become an established method to characterize the reaction of cells to toxicants. Such experiments are mostly performed at compound concentrations close to the cytotoxicity threshold. At present, little information is available on concentration-dependent features of transcriptome changes, in particular, at the transition from noncytotoxic concentrations to conditions that are associated with cell death. Thus, it is unclear in how far cell death confounds the results of transcriptome studies. To explore this gap of knowledge, we treated pluripotent stem cells differentiating to human neuroepithelial cells (UKN1 assay) for short periods (48 h) with increasing concentrations of valproic acid (VPA) and methyl mercury (MeHg), two compounds with vastly different modes of action. We developed various visualization tools to describe cellular responses, and the overall response was classified as "tolerance" (minor transcriptome changes), "functional adaptation" (moderate/strong transcriptome responses, but no cytotoxicity), and "degeneration". The latter two conditions were compared, using various statistical approaches. We identified (i) genes regulated at cytotoxic, but not at noncytotoxic, concentrations and (ii) KEGG pathways, gene ontology term groups, and superordinate biological processes that were only regulated at cytotoxic concentrations. The consensus markers and processes found after 48 h treatment were then overlaid with those found after prolonged (6 days) treatment. The study highlights the importance of careful concentration selection and of controlling viability for transcriptome studies. Moreover, it allowed identification of 39 candidate "biomarkers of cytotoxicity". These could serve to provide alerts that data sets of interest may have been affected by cell death in the model system studied.

Reference compounds for alternative test methods to indicate developmental neurotoxicity (DNT) potential of chemicals: example lists and criteria for their selection and use

There is a paucity of information concerning the developmental neurotoxicity (DNT) hazard posed by industrial and environmental chemicals. New testing approaches will most likely be based on batteries of alternative and complementary (non-animal) tests. As DNT is assumed to result from the modulation of fundamental neurodevelopmental processes (such as neuronal differentiation, precursor cell migration or neuronal network formation) by chemicals, the first generation of alternative DNT tests target these processes. The advantage of such types of assays is that they capture toxicants with multiple targets and modes-of-action. Moreover, the processes modelled by the assays can be linked to toxicity endophenotypes, i.e. alterations in neural connectivity that form the basis for neurofunctional deficits in man. The authors of this review convened in a workshop to define criteria for the selection of positive/negative controls, to prepare recommendations on their use, and to initiate the setup of a directory of reference chemicals. For initial technical optimization of tests, a set of >50 endpoint-specific control compounds was identified. For further test development, an additional “test” set of 33 chemicals considered to act directly as bona fide DNT toxicants is proposed, and each chemical is annotated to the extent it fulfills these criteria. A tabular compilation of the original literature used to select the test set chemicals provides information on statistical procedures, and toxic/non-toxic doses (both for pups and dams). Suggestions are provided on how to use the >100 compounds (including negative controls) compiled here to address specificity, adversity and use of alternative test systems.

Effects of cigarette smoke, cessation and switching to a candidate modified risk tobacco product on the liver in Apoe -/- mice--a systems toxicology analysis

The liver is one of the most important organs involved in elimination of xenobiotic and potentially toxic substances. Cigarette smoke (CS) contains more than 7000 chemicals, including those that exert biological effects and cause smoking-related diseases. Though CS is not directly hepatotoxic, a growing body of evidence suggests that it may exacerbate pre-existing chronic liver disease. In this study, we integrated toxicological endpoints with molecular measurements and computational analyses to investigate effects of exposures on the livers of Apoe(-/- )mice. Mice were exposed to 3R4F reference CS, to an aerosol from the Tobacco Heating System (THS) 2.2, a candidate modified risk tobacco product (MRTP) or to filtered air (Sham) for up to 8 months. THS2.2 takes advantage of a "heat-not-burn" technology that, by heating tobacco, avoids pyrogenesis and pyrosynthesis. After CS exposure for 2 months, some groups were either switched to the MRTP or filtered air. While no group showed clear signs of hepatotoxicity, integrative analysis of proteomics and transcriptomics data showed a CS-dependent impairment of specific biological networks. These networks included lipid and xenobiotic metabolism and iron homeostasis that likely contributed synergistically to exacerbating oxidative stress. In contrast, most proteomic and transcriptomic changes were lower in mice exposed to THS2.2 and in the cessation and switching groups compared to the CS group. Our findings elucidate the complex biological responses of the liver to CS exposure. Furthermore, they provide evidence that THS2.2 aerosol has reduced biological effects, as compared with CS, on the livers of Apoe(-/- )mice.

Highlight report: Launch of a large integrated European in vitro toxicology project: EU-ToxRisk

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.”

Advancing Risk Assessment through the Application of Systems Toxicology

Risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from human activities. Mechanistic approaches to risk assessment have been generally referred to as systems toxicology. Systems toxicology makes use of advanced analytical and computational tools to integrate classical toxicology and quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Three presentations including two case studies involving both in vitro and in vivo approaches described the current state of systems toxicology and the potential for its future application in chemical risk assessment.

Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model

The U.S. Environmental Protection Agency (EPA) is considering high-throughput and computational methods to evaluate the endocrine bioactivity of environmental chemicals. Here we describe a multistep, performance-based validation of new methods and demonstrate that these new tools are sufficiently robust to be used in the Endocrine Disruptor Screening Program (EDSP). Results from 18 estrogen receptor (ER) ToxCast high-throughput screening assays were integrated into a computational model that can discriminate bioactivity from assay-specific interference and cytotoxicity. Model scores range from 0 (no activity) to 1 (bioactivity of 17β-estradiol). ToxCast ER model performance was evaluated for reference chemicals, as well as results of EDSP Tier 1 screening assays in current practice. The ToxCast ER model accuracy was 86% to 93% when compared to reference chemicals and predicted results of EDSP Tier 1 guideline and other uterotrophic studies with 84% to 100% accuracy. The performance of high-throughput assays and ToxCast ER model predictions demonstrates that these methods correctly identify active and inactive reference chemicals, provide a measure of relative ER bioactivity, and rapidly identify chemicals with potential endocrine bioactivities for additional screening and testing. EPA is accepting ToxCast ER model data for 1812 chemicals as alternatives for EDSP Tier 1 ER binding, ER transactivation, and uterotrophic assays.