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Non-Animal Methods to Predict Skin Sensitization (I): The Cosmetics Europe Database

Sebastian Hoffmann, Nicole Kleinstreuer, Nathalie Alépée, David Allen, Anne Marie Api, Takao Ashikaga, Elodie Clouet, Magalie Cluzel, Bertrand Desprez, Nichola Gellatly, Carsten Goebel, Petra S. Kern, Martina Klaric, Jochen Kühnl, Jon F. Lalko, Silvia Martinozzi-Teissier, Karsten Mewes, Masaaki Miyazawa, Rahul Parakhia, Erwin van Vliet, Qingda Zang, Dirk Petersohn
Critical Reviews in Toxicology (2018) DOI: https://doi.org/10.1080/10408444.2018.1429385 PMID: 29474128


Publication


Abstract

Cosmetics Europe, the European Trade Association for the cosmetics and personal care industry, is conducting a multi-phase program to develop regulatory accepted, animal-free testing strategies enabling the cosmetics industry to conduct safety assessments. Based on a systematic evaluation of test methods for skin sensitization, five non-animal test methods (DPRA (Direct Peptide Reactivity Assay), KeratinoSensTM, h-CLAT (human cell line activation test), U-SENSTM, SENS-IS) were selected for inclusion in a comprehensive database of 128 substances. Existing data were compiled and completed with newly generated data, the latter amounting to one-third of all data. The database was complemented with human and local lymph node assay (LLNA) reference data, physicochemical properties and use categories, and thoroughly curated. Focused on the availability of human data, the substance selection resulted nevertheless resulted in a high diversity of chemistries in terms of physico-chemical property ranges and use categories. Predictivities of skin sensitization potential and potency, where applicable, were calculated for the LLNA as compared to human data and for the individual test methods compared to both human and LLNA reference data. In addition, various aspects of applicability of the test methods were analyzed. Due to its high level of curation, comprehensiveness, and completeness, we propose our database as a point of reference for the evaluation and development of testing strategies, as done for example in the associated work of Kleinstreuer et al. We encourage the community to use it to meet the challenge of conducting skin sensitization safety assessment without generating new animal data.

Figures


Figure 1. HRIPT no observed effect levels (NOEL) as µg/cm2 for the human potency categories.

HRIPT no observed effect levels (NOEL) as µg/cm2 for the human potency categories for 79 substances, for which Basketter et al. (2014 Basketter DA, Alepee N, Ashikaga T, Barroso J, Gilmour N, Goebel C, Hibatallah J, Hoffmann S, Kern P, Martinozzi-Teissier S, et al. 2014. Categorization of chemicals according to their relative human skin-sensitizing potency. Dermatitis. 25:11–21. [Google Scholar] ) or Api et al. (2017 Api AM, Parakhia R, O’Brien D, Basketter DA. 2017. Fragrances categorized according to relative human skin sensitization potency. Dermatitis. 28:299–307. [Google Scholar] ) reported NOEL.

Figure 2. Boxplots of six physicochemical properties for 122 substances.

Figure 3. Distribution of LLNA EC3 values for substances.

Distribution of LLNA EC3 values for substances: substances with multiple LLNA EC3 values are plotted in order from most to least potent based on the modified median (top: <10% EC3; bottom: > 10% EC3), where the y-axis is in log scale. Potency categories are delineated by horizontal dotted lines. Negative LLNA are displayed with an EC3 of 100%.

Figure 4. Plot of LLNA EC3 modified median against the six human categories for all 128 substances.

LLNA Potency categories are delineated by horizontal dotted lines. Negative LLNA are displayed with an EC3 of 100%.

Tables


Table 1. Use category of substances based on ACToR Use DB Categories in CPCat.

106 of the 128 substances were associated with more than one category.

Table 2. Contingency tables comparing human and LLNA reference data for 128 substances.

A: 2 × 2; B: 3 × 3; C: 5 × 5

Table 3. Skin sensitization potential predictivity of individual test methods.

Skin sensitization potential predictivity of individual test methods and the mechanistic domains compared to both human and LLNA reference data, incl.

Table 4. Contingency table of skin sensitization potency predictions of the SENS-IS.

Contingency table of skin sensitization potency predictions of the SENS-IS for 126 substances compared to human reference data categories (grey indicates concordant predictions).

Supplemental Materials


Supplemental Material