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Read-across can increase confidence in the Next Generation Risk Assessment for skin sensitisation: A case study with
Françoise Gautier1, Fleur Tourneix1, Hind Assaf Vandecasteele1
1L'Oréal, Research & Innovation, Aulnay-sous-Bois, France; L'Oréal, Research & Innovation, Clichy, France.
Abstract:
Historically skin sensitisation risk assessment for cosmetic ingredients was based on animal models, however regulatory demands have led to Next Generation Risk Assessment (NGRA), using data from New Approach Methodologies (NAM) and Defined Approaches (DA). This case study was meant to investigate if the use of resorcinol at 0.2% in a face cream was safe and a maximum use concentration could be defined. The NAM data and DA predictions could not provide sufficient confidence to determine a point of departure (POD). Therefore, the application of read-across was explored to increase the level of confidence. Analogue searches in various tools and databases using "mode of action" and "chemical structural features" retrieved 535 analogues. After refinement by excluding analogues without a defined structure, similar reactivity profile and skin sensitisation data, 39 analogues remained. A final selection was made based on three approaches: expert judgment, chemical similarity or Local Lymph Node Assay data (LLNA). All read-across approaches supported a moderate potency. A POD derived from the LLNA EC3 of 3.6% was determined leading to a favourable NGRA conclusion and a maximum use concentration of 0.36%. This was supported by a traditional risk assessment based on the available animal data for resorcinol.
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