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 opportunity 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 quantitative 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.

The ReSolve project brought together expertise from chemistry, engineering, toxicology, techno-economics, and life cycle assessment in order to develop safer, bio-based solvents. This article summarizes findings from the project including the further development of Cyrene (TM) and 2,2,5,5-tetramethyloxolane (TMO) as replacements for N-methylpyrrolidone (NMP) and toluene, respectively.

Three dipolar aprotic solvents were designed to possess high dipolarity and low toxicity: N,N,N ',N '-tetrabutylsuccindiamide (TBSA), N,N '-diethyl-N,N '-dibutylsuccindiamide (EBSA), and N,N '-dimethyl-N,N '-dibutylsuccindiamide (MBSA). They were synthesized catalytically by using a K60 silica catalyst in a solventless system. Their water immiscibility stands out as an unusual and useful property for dipolar aprotic solvents. They were tested in a model Heck reaction, metal-organic framework syntheses, and a selection of polymer solubility experiments in which their performances were found to be comparable to traditional solvents. Furthermore, MBSA was found to be suitable for the production of an industrially relevant membrane from polyethersulfone. An integrated approach involving in silico analysis based on available experimental information, prediction model outcomes and read across data, as well as a panel of in vitro reporter gene assays covering a broad range of toxicological endpoints was used to assess toxicity. These in silico and in vitro tests suggested no alarming indications of toxicity in the new solvents.

Since teratogenicity testing in mammals is a particular challenge from an animal welfare perspective, there is a great need for the development of alternative test systems. In this context, the zebrafish ( Danio rerio ) embryo has received increasing attention as a non-protected embryonic vertebrate in vivo model. The predictive power of zebrafish embryos for general vertebrate teratogenicity strongly depends on the correlation between fish and mammals with respect to both overall general toxicity and more specific endpoints indicative of certain modes-of-action. The present study was designed to analyze the correlation between (1) effects of valproic acid and nine of its analogues in zebrafish embryos and (2) their known neurodevelopmental effects in mice. To this end, zebrafish embryos exposed for 120 h in an extended version of the acute fish embryo toxicity test (FET; OECD TG 236) were analyzed with respect to an extended list of sublethal endpoints. Particular care was given to endpoints putatively related to neurodevelopmental toxicity, namely jitter/tremor, deformation of sensory organs (eyes) and craniofacial deformation, which might correlate to neural tube defects caused by valproic acid in mammals. A standard evaluation of lethal (LC according to OECD TG 236) and sublethal toxicity (EC) merely indicated that four out of ten compounds tested in zebrafish correlate with positive results in mouse in vivo studies. A detailed assessment of more specific effects, however, namely, jitter/tremor, small eyes and craniofacial deformation, resulted in a correspondence of 75% with in vivo mouse data. A refinement of endpoint analysis from an integration of all observations into one LC x or EC x data (as foreseen by current ecotoxicology-driven OECD guidelines) to a differential evaluation of endpoints specific of selected modes-of-action thus increases significantly the predictive power of the zebrafish embryo model for mammalian teratogenicity. However, for some of the endpoints observed, e.g., scoliosis, lordosis, pectoral fin deformation and lack of movement, further experiments are required for the identification of underlying modes-of-action and an unambiguous interpretation of their predictive power for mammalian toxicity.

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.

Repeated dose toxicity evaluation aims at assessing the occurrence of adverse effects following chronic or repeated exposure to chemicals. Non-animal approaches have gained importance in the last decades because of ethical considerations as well as due to scientific reasons calling for more human-based strategies. A critical aspect of this challenge is linked to the capacity to cover a comprehensive set of interdependent mechanisms of action, link them to adverse effects and interpret their probability to be triggered in the light of the exposure at the (sub)cellular level. Inherent to its structured nature, an ontology addressing repeated dose toxicity could be a scientific and transparent way to achieve this goal. Additionally, repeated dose toxicity evaluation through the use of a harmonized ontology should be performed in a reproducible and consistent manner, while mimicking as accurately as possible human physiology and adaptivity. In this paper, the outcome of a series of workshops organized by Cosmetics Europe on this topic is reported. As such, this manuscript shows how experts set critical elements and ways of establishing a mode-of-action ontology model as a support to risk assessors aiming to perform animal-free safety evaluation of chemicals based on repeated dose toxicity data.

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Sub-chronic toxicity studies of 163 non-genotoxic chemicals were evaluated in order to predict the tumour outcome of 24-month rat carcinogenicity studies obtained from the EFSA and ToxRef databases. Hundred eleven of the 148 chemicals that did not induce putative preneoplastic lesions in the sub-chronic study also did not induce tumours in the carcinogenicity study (True Negatives). Cellular hypertrophy appeared to be an unreliable predictor of carcinogenicity. The negative predictivity, the measure of the compounds evaluated that did not show any putative preneoplastic lesion in de sub-chronic studies and were negative in the carcinogenicity studies, was 75%, whereas the sensitivity, a measure of the sub-chronic study to predict a positive carcinogenicity outcome was only 5%. The specificity, the accuracy of the sub-chronic study to correctly identify non-carcinogens was 90%. When the chemicals which induced tumours generally considered not relevant for humans (33 out of 37 False Negatives) are classified as True Negatives, the negative predictivity amounts to 97%. Overall, the results of this retrospective study support the concept that chemicals showing no histopathological risk factors for neoplasia in a sub-chronic study in rats may be considered non-carcinogenic and do not require further testing in a carcinogenicity study.

Grouping of substances and utilizing read-across of data within those groups represents an important data gap filling technique for chemical safety assessments. Categories/analogue groups are typically developed based on structural similarity and, increasingly often, also on mechanistic (biological) similarity. While read-across can play a key role in complying with legislation such as the European REACH regulation, the lack of consensus regarding the extent and type of evidence necessary to support it often hampers its successful application and acceptance by regulatory authorities. Despite a potentially broad user community, expertise is still concentrated across a handful of organizations and indi­viduals. In order to facilitate the effective use of read-across, this document presents the state of the art, summarizes insights learned from reviewing ECHA published decisions regarding the relative successes/pitfalls surrounding read-across under REACH, and compiles the relevant activities and guidance documents. Special emphasis is given to the available existing tools and approaches, an analysis of ECHA’s published final decisions associated with all levels of compliance checks and testing proposals, the consideration and expression of uncertainty, the use of biological support data, and the impact of the ECHA Read-Across Assessment Framework (RAAF) published in 2015.

The identification of compounds in complex mixtures remains challenging despite recent advances in analytical techniques. At present, no single method can detect and quantify the vast array of compounds that might be of potential interest in metabolomics studies. High performance liquid chromatography/mass spectrometry (HPLC/MS) is often considered the analytical method of choice for analysis of biofluids. The positive identification of an unknown involves matching at least two orthogonal HPLC/MS measurements (exact mass, retention index, drift time etc.) against an authentic standard. However, due to the limited availability of authentic standards, an alternative approach involves matching known and measured features of the unknown compound with computationally predicted features for a set of candidate compounds downloaded from a chemical database. Computationally predicted features include retention index, ECOM50 (energy required to decompose 50% of a selected precursor ion in a collision induced dissociation cell), drift time, whether the unknown compound is biological or synthetic and a collision induced dissociation (CID) spectrum. Computational predictions are used to filter the initial "bin" of candidate compounds. The final output is a ranked list of candidates that best match the known and measured features. In this mini review, we discuss cheminformatics methods underlying this database search-filter identification approach.

167 Received January 25, 2016; Accepted February 9, 2016; Epub February 11, 2016; http://dx.doi.org/10.14573/altex.1601252 mechanisms, so only using chemical similarity to justify the read-across will be error-prone, especially when chemically similar compounds show dissimilar toxicity phenomena. The availability of massive biological datasets for environmental compounds makes biological similarity approaches feasible within the scope of read-across. This paper, which accompanies the efforts toward Good Read-Across Practice (Ball et al.,

Read-across, i.e., filling toxicological data gaps by relating to similar chemicals for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, biological similarity based on biological data adds extra strength to this process. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of, e.g., genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances are becoming available, enabling big data approaches in read-across studies. In the context of developing Good Read-Across Practice guidance, a number of case studies using various big data sources were evaluated to assess the contribution of biological data to enriching read-across. An example is given for the US EPA's ToxCast dataset which allows read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example is given for REACH registration data that enhances read-across for acute toxicity studies. A different approach is taken using omics data to establish biological similarity: Examples are given for in vitro stem cell models and short-term in vivo repeated dose studies in rats used to support read-across and category formation. These preliminary biological data-driven read-across studies show the way towards the generation of new read-across approaches that can inform chemical safety assessment.

There is a great need for rapid testing strategies for reproductive toxicity testing, avoiding animal use. The EU Framework program 7 project ChemScreen aimed to fill this gap in a pragmatic manner preferably using validated existing tools and place them in an innovative alternative testing strategy. In our approach we combined knowledge on critical processes affected by reproductive toxicants with knowledge on the mechanistic basis of such effects. We used in silico methods for prescreening chemicals for relevant toxic effects aiming at reduced testing needs. For those chemicals that need testing we have set up an in vitro screening panel that includes mechanistic high throughput methods and lower throughput assays that measure more integrative endpoints. In silico pharmacokinetic modules were developed for rapid exposure predictions via diverse exposure routes. These modules to match in vitro and in vivo exposure levels greatly improved predictivity of the in vitro tests. As a further step, we have generated examples how to predict reproductive toxicity of chemicals using available data. We have executed formal validations of panel constituents and also used more innovative manners to validate the test panel using mechanistic approaches. We are actively engaged in promoting regulatory acceptance of the tools developed as an essential step towards practical application, including case studies for read-across purposes. With this approach, a significant saving in animal use and associated costs seems very feasible.

Several studies have documented shifts in humoral immune parameters (e.g., immunoglobulins) across the menstrual cycle in healthy women. It is thought that these shifts may reflect dynamic balancing between reproduction and pathogen defense, as certain aspects of humoral immunity may disrupt conception and may be temporarily downregulated at ovulation. If so, one could expect maximal cycle-related shifts of humoral immunity in individuals invested in reproduction – that is, women who are currently sexually active – and less pronounced shifts in women who are not reproductively active (i.e., abstinent). We investigated the interaction of sexual activity, menstrual cycle phase, and humoral immunity in a sample of 32 healthy premenopausal women (15 sexually active, 17 abstinent). Participants provided saliva samples during their menses, follicular phase, ovulation (as indicated by urine test for LH surge), and luteal phase, from which IgA was assayed. Participants also provided blood samples at menses and ovulation, from which IgG was assayed. Sexually active participants provided records of their frequency of sexual activity as well as condom use. At ovulation, sexually active women had higher IgG than abstinent women (d = 0.77), with women reporting regular condom use showing larger effects (d = 0.63) than women reporting no condom use (d = 0.11). Frequency of sexual activity predicted changes in IgA (Cohen's f2 = 0.25), with women reporting high frequency of sexual activity showing a decrease in IgA at ovulation, while women reporting low frequency or no sexual activity showing an increase in IgA at ovulation. Taken together, these findings support the hypothesis that shifts in humoral immunity across the menstrual cycle are associated with reproductive effort, and could contribute to the mechanisms by which women's physiology navigates tradeoffs between reproduction and immunity.

There is a great need for alternative testing methods for reproductive toxicants that are practical, fast, cost-effective and easy to interpret. Previously we followed a pragmatic approach using readily available tests, which was successful in predicting reproductive toxicity of chemicals [13]. This initial battery still contained apical tests and is fairly complex and low in its throughput. The current study aimed to simplify this screening battery using a mechanistic approach and a panel of high throughput CALUX reporter gene assays. A mechanistic approach was taken to validate this high throughput test battery. To this end it was challenged with two preselected sets of chemicals addressing two major apical effect classes relevant in reproductive toxicity. We found selectivity in this battery in that 82% of the compounds inducing reproductive organ deformities were predicted correctly, while for compounds inducing neural tube defects this was the case in 47% only. This is consistent with the mechanisms of toxicity covered in the battery. The most informative assays in the battery were ERalpha CALUX to measure estrogenicity and the AR-anti CALUX assay to measure androgen receptor antagonism.

Read-across is a data gap filling technique used within category and analogue approaches. It has been utilized as an alternative approach to address information requirements under various past and present regulatory programs such as the OECD High Production Volume Programme as well as the EU's Registration, Evaluation, Authorisation and restriction of CHemicals (REACH) regulation. Although read-across raises a number of expectations, many misconceptions still remain around what it truly represents; how to address its associated justification in a robust and scientifically credible manner; what challenges/issues exist in terms of its application and acceptance; and what future efforts are needed to resolve them. In terms of future enhancements, read-across is likely to embrace more biologically-orientated approaches consistent with the Toxicity in the 21st Century vision (Tox-21c). This Food for Thought article, which is notably not a consensus report, aims to discuss a number of these aspects and, in doing so, to raise awareness of the ongoing efforts and activities to enhance read-across. It also intends to set the agenda for a CAAT read-across initiative in 2014-2015 to facilitate the proper use of this technique.