Non-animal methods to predict skin sensitization (II): an assessment of defined approaches

Abstract

Skin sensitization is a toxicity endpoint of widespread concern, for which the mechanistic understanding and concurrent necessity for non-animal testing approaches have evolved to a critical juncture, with many available options for predicting sensitization without using animals. Cosmetics Europe and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods collaborated to analyze the performance of multiple non-animal data integration approaches for the skin sensitization safety assessment of cosmetics ingredients. The Cosmetics Europe Skin Tolerance Task Force (STTF) collected and generated data on 128 substances in multiple in vitro and in chemico skin sensitization assays selected based on a systematic assessment by the STTF. These assays, together with certain in silico predictions, are key components of various non-animal testing strategies that have been submitted to the Organization for Economic Cooperation and Development as case studies for skin sensitization. Curated murine local lymph node assay (LLNA) and human skin sensitization data were used to evaluate the performance of six defined approaches, comprising eight non-animal testing strategies, for both hazard and potency characterization. Defined approaches examined included consensus methods, artificial neural networks, support vector machine models, Bayesian networks, and decision trees, most of which were reproduced using open source software tools. Multiple non-animal testing strategies incorporating in vitro, in chemico, and in silico inputs demonstrated equivalent or superior performance to the LLNA when compared to both animal and human data for skin sensitization.

Adjustment of a no expected sensitization induction level derived from Bayesian network integrated testing strategy for skin sensitization risk assessment

“…For 20.6% (29/141) of sensitizers, the potency was under-predicted and in 17.1% (30/175) it was over-predicted. Importantly, while these predictions were performed without either the pre-processing step of selecting data from their physic-chemical applicability domains, or the post-processing step of MA correction, these results were better than, or equal to, those of the smaller dataset obtained using both processing steps (Kleinstreuer et al, 2018); LLNA hazard outcomes demonstrated 83.2% (99/119) accuracy, and potency accuracy was 67.8% (78/115). These results suggested that the processing steps did not necessarily improve prediction accuracy.…”

“…For example, the sequential testing strategy (STS) provides hazard and potency classification based on DPRA and h-CLAT data. In addition, the integrated testing strategy (ITS) provides hazard and potency classification by using the quantitative parameters of DPRA and h-CLAT, and the result from a commercial in silico tool (DEREK Nexus) that identifies structural alerts for sensitization (Nukada et al, 2013;Takenouchi et al, 2015;Kleinstreuer et al, 2018). However, the STS and ITS do not address KE2.…”

Towards a tiered test strategy for plant protection products to address mixture toxicity by alternative approaches in human health assessment

“…49 Multiple IATAs have been published for skin sensitisation [50][51][52][53][54] and the OECD has published guidance on the background and reporting of skin sensitisation IATA. 49 A quantitative evaluation of approaches designed for hazard identification has been summarised by Kleinstreuer et al, 55 who report accuracies of 70.1% and 88.3% for the BASF 'two out of three' approach 50 and 88.3% for the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) support vector machine approach, 54 respectively. However, these evaluations were conducted on single substances.…”

Skin sensitization: Uncertainties, challenges, and opportunities for improved risk assessment

“…One perceived limitation of the in vitro methods that have been validated to date is that they each seek to identify contact allergens as a function of a single key event in the AOP for skin sensitization. For this reason, the prevailing view currently is that these methods should not be used in isolation, but rather as part of integrated testing platforms that incorporate two or more separate assays, in, for example, defined approaches (DAs) . Although this strategy might appear to be sensible, integration of different test systems has to be considered carefully if overall accuracy is going to be enhanced rather than compromised .…”

“…The OECD test methods were developed and validated to allow the distinction between sensitizers and non‐sensitizers, so the question here is whether non‐animal methods (OECD Test Guideline methods or others), when used either alone or combined, can provide an estimation of human skin‐sensitizing potency to enable the use of a PoD in the risk assessment. Progress has been reported, but it is not yet clear how best to deploy such methods for potency assessment, how well they will perform in practice, and whether additional information or test methods will be required to inform a potency assessment, for example, measurement of the T cell response . Continued evaluation of DAs and integrated approaches to testing and assessment (IATAs) against benchmark in vivo (LLNA and/or human) data, and case studies evaluating risk assessment outcomes for historical materials with animal data with respect to risk assessment based on non‐animal data and clinical experience, are required to build a consensus on how to apply non‐animal data within DAs and IATAs for risk assessment decision‐making …”