Current approaches to skin sensitisation risk assessment are dependent upon the availability of information regarding two fundamental parameters. Firstly, data relating to the relative skin sensitising potency of the chemical, and secondly, information regarding likely conditions of human exposure. During the past two decades, much has been achieved in terms of refining methods capable of informing these parameters. For example, the development of the local lymph node assay (LLNA) has made it possible to predict skin sensitising hazard, and to determine relative skin sensitising potency, in a way that was not possible previously. Taken together with accurate information about predicted exposure, such potency data can be used to facilitate the derivation of effective risk assessments. However, although the LLNA provides an integrated assessment of skin sensitising activity, it does require the use of experimental animals and there is growing enthusiasm for designing robust alternative approaches that will reduce or obviate that need. Progress is being made in defining alternative experimental strategies that avoid animal use, but it is clear that accurate characterisation of skin sensitisation hazards will require the effective integration of various sources of information. For this reason, we exemplify here one possible approach that, in theory, provides a framework for not only the identification of skin sensitising chemicals, but also the estimation of relative sensitising potency. This paradigm depends upon development of an understanding of the various biological, biochemical and chemical factors that impact on the allergenic properties of chemicals and the acquisition of skin sensitisation, and an ability to measure these in vitro.

Abstract Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven risk assessment approach that integrates new approach methodologies (NAMs) to assure safety without the use of animal testing. These principles were applied to a hypothetical safety assessment of 0.1% coumarin in face cream and body lotion. For the purpose of evaluating the use of NAMs, existing animal and human data on coumarin were excluded. Internal concentrations (plasma Cmax) were estimated using a physiologically based kinetic model for dermally applied coumarin. Systemic toxicity was assessed using a battery of in vitro NAMs to identify points of departure (PoDs) for a variety of biological effects such as receptor-mediated and immunomodulatory effects (Eurofins SafetyScreen44 and BioMap Diversity 8 Panel, respectively), and general bioactivity (ToxCast data, an in vitro cell stress panel and high-throughput transcriptomics). In addition, in silico alerts for genotoxicity were followed up with the ToxTracker tool. The PoDs from the in vitro assays were plotted against the calculated in vivo exposure to calculate a margin of safety with associated uncertainty. The predicted Cmax values for face cream and body lotion were lower than all PoDs with margin of safety higher than 100. Furthermore, coumarin was not genotoxic, did not bind to any of the 44 receptors tested and did not show any immunomodulatory effects at consumer-relevant exposures. In conclusion, this case study demonstrated the value of integrating exposure science, computational modeling and in vitro bioactivity data, to reach a safety decision without animal data.

Risk assessment methodologies in toxicology have remained largely unchanged for decades. The default approach uses high dose animal studies, together with human exposure estimates, and conservative assessment (uncertainty) factors or linear extrapolations to determine whether a specific chemical exposure is 'safe' or 'unsafe'. Although some incremental changes have appeared over the years, results from all new approaches are still judged against this process of extrapolating high-dose effects in animals to low-dose exposures in humans. The US National Research Council blueprint for change, entitled Toxicity Testing in the 21st Century: A Vision and Strategy called for a transformation of toxicity testing from a system based on high-dose studies in laboratory animals to one founded primarily on in vitro methods that evaluate changes in normal cellular signalling pathways using human-relevant cells or tissues. More recently, this concept of pathways-based approaches to risk assessment has been expanded by the description of 'Adverse Outcome Pathways' (AOPs). The question, however, has been how to translate this AOP/TT21C vision into the practical tools that will be useful to those expected to make safety decisions. We have sought to provide a practical example of how the TT21C vision can be implemented to facilitate a safety assessment for a commercial chemical without the use of animal testing. To this end, the key elements of the TT21C vision have been broken down to a set of actions that can be brought together to achieve such a safety assessment. Such components of a pathways-based risk assessment have been widely discussed, however to-date, no worked examples of the entire risk assessment process exist. In order to begin to test the process, we have taken the approach of examining a prototype toxicity pathway (DNA damage responses mediated by the p53 network) and constructing a strategy for the development of a pathway based risk assessment for a specific chemical in a case study mode. This contribution represents a 'work-in-progress' and is meant to both highlight concepts that are well-developed and identify aspects of the overall process which require additional development. To guide our understanding of what a pathways-based risk assessment could look like in practice, we chose to work on a case study chemical (quercetin) with a defined human exposure and to bring a multidisciplinary team of chemists, biologists, modellers and risk assessors to work together towards a safety assessment. Our goal was to see if the in vitro dose response for quercetin could be sufficiently understood to construct a TT21C risk assessment without recourse to rodent carcinogenicity study data. The data presented include high throughput pathway biomarkers (p-H2AX, p-ATM, p-ATR, p-Chk2, p53, p-p53, MDM2 and Wip1) and markers of cell-cycle, apoptosis and micronuclei formation, plus gene transcription in HT1080 cells. Eighteen point dose response curves were generated using flow cytometry and imaging to determine the concentrations...

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