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Non-animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?

期刊

JOURNAL OF APPLIED TOXICOLOGY
卷 38, 期 1, 页码 41-50

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WILEY
DOI: 10.1002/jat.3479

关键词

skin sensitization; integrated approaches to testing and assessment (IATA); adverse outcome pathway (AOP); local lymph node assay (LLNA); direct peptide reactivity assay (DPRA); KeratinoSens; human cell line activation test (h-CLAT); quantitative mechanistic models (QMMs)

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There is an expectation that to meet regulatory requirements, and avoid or minimize animal testing, integrated approaches to testing and assessment will be needed that rely on assays representing key events (KEs) in the skin sensitization adverse outcome pathway. Three non-animal assays have been formally validated and regulatory adopted: the direct peptide reactivity assay (DPRA), the KeratinoSens assay and the human cell line activation test (h-CLAT). There have been many efforts to develop integrated approaches to testing and assessment with the two out of three approach attracting much attention. Here a set of 271 chemicals with mouse, human and non-animal sensitization test data was evaluated to compare the predictive performances of the three individual non-animal assays, their binary combinations and the two out of three approach in predicting skin sensitization potential. The most predictive approach was to use both the DPRA and h-CLAT as follows: (1) perform DPRA - if positive, classify as sensitizing, and (2) if negative, perform h-CLAT - a positive outcome denotes a sensitizer, a negative, a non-sensitizer. With this approach, 85% (local lymph node assay) and 93% (human) of non-sensitizer predictions were correct, whereas the two out of three approach had 69% (local lymph node assay) and 79% (human) of non-sensitizer predictions correct. The findings are consistent with the argument, supported by published quantitative mechanistic models that only the first KE needs to be modeled. All three assays model this KE to an extent. The value of using more than one assay depends on how the different assays compensate for each other's technical limitations. Copyright (c) 2017 John Wiley & Sons, Ltd.

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