State of the art in non-animal approaches for skin sensitization testing: from individual test methods towards testing strategies

Abstract

The hazard assessment of skin sensitizers relies mainly on animal testing, but much progress is made in the development, validation and regulatory acceptance and implementation of non-animal predictive approaches. In this review, we provide an update on the available computational tools and animal-free test methods for the prediction of skin sensitization hazard. These individual test methods address mostly one mechanistic step of the process of skin sensitization induction. The adverse outcome pathway (AOP) for skin sensitization describes the key events (KEs) that lead to skin sensitization. In our review, we have clustered the available test methods according to the KE they inform: the molecular initiating event (MIE/KE1)-protein binding, KE2-keratinocyte activation, KE3-dendritic cell activation and KE4-T cell activation and proliferation. In recent years, most progress has been made in the development and validation of in vitro assays that address KE2 and KE3. No standardized in vitro assays for T cell activation are available; thus, KE4 cannot be measured in vitro. Three non-animal test methods, addressing either the MIE, KE2 or KE3, are accepted as OECD test guidelines, and this has accelerated the development of integrated or defined approaches for testing and assessment (e.g. testing strategies). The majority of these approaches are mechanism-based, since they combine results from multiple test methods and/or computational tools that address different KEs of the AOP to estimate skin sensitization potential and sometimes potency. Other approaches are based on statistical tools. Until now, eleven different testing strategies have been published, the majority using the same individual information sources. Our review shows that some of the defined approaches to testing and assessment are able to accurately predict skin sensitization hazard, sometimes even more accurate than the currently used animal test. A few defined approaches are developed to provide an estimate of the potency sub-category of a skin sensitizer as well, but these approaches need further independent evaluation with a new dataset of chemicals. To conclude, this update shows that the field of non-animal approaches for skin sensitization has evolved greatly in recent years and that it is possible to predict skin sensitization hazard without animal testing.

Keratinocytes improve prediction of sensitization potential and potency of chemicals with THP-1 cells

“…In vitro tests addressing single key steps (protein reactivity, keratinocyte response, dendritic cell activation) of the adverse outcome pathway (AOP) for skin sensitization have been validated for hazard identification (Ezendam et al, 2016). However, beside hazard, the prediction of skin sensitization potency is crucial for adequate risk assessment.…”

The GARD platform for potency assessment of skin sensitizing chemicals

“…However, it is characterized by certain limitations such as susceptibility to vehicle effects and issues with false-positive results (Anderson et al, 2011). Several non-animal predictive methods have been developed to reduce animal experimentation used for chemical testing including computational approaches to integrate data from different test platforms for hazard identification as recently reviewed (Ezendam et al, 2016). Three test methods for skin sensitization are accepted as test guidelines at the OECD; the ARE-NRF2 luciferase method (KeratinoSens™) assay (Andreas et al, 2011;Natsch and Emter, 2008), the Direct Peptide Reactivity Assay (DPRA) (Gerberick et al, 2004) and the human Cell Line Activation Test (h-CLAT) (Ashikaga et al, 2006).…”

“…In addition to hazard identification, information on skin sensitizer potency is imperative in order to allow quantitative risk assessment and to define exposure limits. Approaches for the prediction of skin sensitizer potency have been published and were recently reviewed by Ezendam et al (2016), such as assays targeting KE2 (epidermal equivalent sensitizer potency assay (Teunis et al, 2014), SENS-IS (Cottrez et al, 2015)) and the U-SENS assay modelling KE3 (Piroird et al, 2015). Furthermore, in silico models, often combining information from several in vitro methods, have been described, for example QSAR (Dearden et al, 2015), artificial neural networks (Tsujita-Inoue et al, 2014), probabilistic models and integrated testing strategy (ITS) approaches including a Bayesian model (Jaworska et al, 2013(Jaworska et al, , 2015Luechtefeld et al, 2015;Natsch et al, 2015).…”

“…Obviously, predicting 1B, i.e., weak sensitizers, seemed the most challenging part. Also in the LLNA, potency predictions of weak sensitizers vary more than those of strong sensitizers (Dumont et al, 2016;Hoffmann, 2015;Ezendam et al, 2016). Furthermore, 1B is a very heterogeneous group, both considering the range of LLNA EC3 concentrations (> 2%; CLP, 2016) and human potency categories associated to chemicals summarized in category 1B.…”

Evaluation of the GARD assay in a blind Cosmetics Europe study

“…Rather, it is widely proposed that assessment of hazard and/or risk should be carried out using integrated testing strategies (ITS), also referred to as integrated approaches to testing and assessment (IATA) (Jaworska and Hoffmann, 2010;Hartung et al, 2013;Rovida et al, 2015;Ezendam et al, 2016). However, the overall predictive performance of an ITS will invariably depend on the predictivity of its assay constituents.…”