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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.

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.

In order to replace the use of animals in toxicity testing, there is a need to predict in vivo toxic doses from concentrations that cause toxicological effects in relevant in vitro systems. The Virtual Cell Based Assay (VCBA) estimates time-dependent concentration of a test chemical in the cell and cell culture for a given in vitro system. The concentrations in the different compartments of the cell and test system are derived from ordinary differential equations, physicochemical parameters of the test chemical and properties of the cell line. The VCBA has been developed for a range of cell lines including BALB/c 3T3 cells, HepG2, HepaRG, lung A459 cells, and cardiomyocytes. The model can be used to design and refine in vitro experiments and extrapolate in vitro effective concentrations to in vivo doses that can be applied in risk assessment. In this paper, we first discuss potential applications of the VCBA: i) design of in vitro High Throughput Screening (HTS) experiments; ii) hazard identification (based on acute systemic toxicity); and iii) risk assessment. Further extension of the VCBA is discussed in the second part, exploring potential application to i) manufactured nanomaterials, ii) additional cell lines and endpoints, and considering iii) other opportunities., Highlights • VCBA as an alternative approach can be applied in the domain of nanotoxicology. • VCBA can support better testing strategies in acute toxicity. • Refinement of the VCBA taking into account biological oscillators could improve toxicity prediction. • Extensions of the VCBA can capture effects related to additional subcellular compartments.

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.

Background An increasing number of manufactured nanomaterials (NMs) are being used in industrial products and need to be registered under the REACH legislation. The hazard characterisation of all these forms is not only technically challenging but resource and time demanding. The use of non-testing strategies like read-across is deemed essential to assure the assessment of all NMs in due time and at lower cost. The fact that read-across is based on the structural similarity of substances represents an additional difficulty for NMs as in general their structure is not unequivocally defined. In such a scenario, the identification of physicochemical properties affecting the hazard potential of NMs is crucial to define a grouping hypothesis and predict the toxicological hazards of similar NMs. In order to promote the read-across of NMs, ECHA has recently published “Recommendations for nanomaterials applicable to the guidance on QSARs and Grouping”, but no practical examples were provided in the document. Due to the lack of publicly available data and the inherent difficulties of reading-across NMs, only a few examples of read-across of NMs can be found in the literature. This manuscript presents the first case study of the practical process of grouping and read-across of NMs following the workflow proposed by ECHA. Methods The workflow proposed by ECHA was used and slightly modified to present the read-across case study. The Read-Across Assessment Framework (RAAF) was used to evaluate the uncertainties of a read-across within NMs. Chemoinformatic techniques were used to support the grouping hypothesis and identify key physicochemical properties. Results A dataset of 6 nanoforms of TiO2 with more than 100 physicochemical properties each was collected. In vitro comet assay result was selected as the endpoint to read-across due to data availability. A correlation between the presence of coating or large amounts of impurities and negative comet assay results was observed. Conclusion The workflow proposed by ECHA to read-across NMs was applied successfully. Chemoinformatic techniques were shown to provide key evidence for the assessment of the grouping hypothesis and the definition of similar NMs. The RAAF was found to be applicable to NMs.

A survey was carried out to explore opportunities for waiving mammalian acute systemic toxicity tests. We were interested in finding out whether data from a sub-acute toxicity test could be used to predict the outcome of an acute systemic toxicity test. The survey was directed at experts in the field of toxicity testing, and was carried out in the context of the upcoming 2018 final registration deadline for chemicals under the EU REACH Regulation. In addition to the survey, a retrospective data analysis of chemicals that had already been registered with the European Chemicals Agency, and for which both acute and sub-acute toxicity data were available, was carried out. This data analysis was focused on chemicals that were administered via the oral route. The answers to the questionnaire showed a willingness to adopt waiving opportunities. In addition, the responses showed that data from a sub-acute toxicity test or dose-range finding study might be useful for predicting chemicals that do not require classification for acute oral toxicity (LD50 > 2000mg/kg body weight). However, with the exception of substances that fall into the non-classified category, it is difficult to predict current acute oral toxicity categories.

Hepatic steatosis is a common liver disease that can lead to hepatotoxicity. Many drugs, including the anticonvulsant valproic acid (VPA), can induce hepatic steatosis as a side effect. Besides human clinical data, VPA and some of its structural analogues have shown to induce steatosis in rodents. Transcriptomics data derived from yeast cells suggest that VPA activates several stress response pathways, which are related to hepatotoxicity. This study aims to investigate stress response pathway activation by VPA and its structural analogues by using HepG2 BAC-GFP reporter cell lines in a high throughput screening platform. Activation of different stress responses were visualized by GFP tagged to target proteins SRXN1 (Nrf2-dependent oxidative stress response), P21 (p53-dependent DNA damage), BiP (unfolded protein response) and A20 (NFkB-dependent inflammatory signaling). Cells were treated with VPA and 18 structural analogous to generate dynamic concentration and time response datasets on pathway activation using high content confocal imaging. SRXN1 activation could discriminate between stimulation of VPA and structural in vivo steatosis positive analogues and in vivo negative analogues. P21 and A20 expression was also changed upon VPA exposure, where BiP did not show a response. Additionally, we observed no cytotoxic effects in our dose range. However, cells treated with valproic analogues that cause steatosis and co-stimulated with TNFa showed an increase in apoptosis, further supporting activation of common signaling pathways by the various toxic valproic analogues that drive onset of cytotoxicity. In conclusion, our current data support the application of a high content imaging stress response reporter platform to provide biological weight-of-evidence support for read across-based risk assessment strategies by providing mechanistic mode-of-action information.