2019 Elsevier - Toxicology In vitro 57 (2019) 154-163
L'Oréal Research & Innovation, Aulnay Sous Bois, France; Adriaens Consulting, Aalter, Belgium; Kao Corporation, Safety Science Research, Kanagawa, Japan; D. Bagley, Colgate-Palmolive Co., Piscataway, NJ, USA; Cosmetics Europe - The Personal Care Association, Brussels, Belgium; Chanel Parfums Beauté, Neuilly sur Seine, France; Henkel AG & Co. KGaA, Düsseldorf, Germany; Beiersdorf AG, Hamburg, Germany; Kao Corporation, S.A., Barcelona, Spain; HP Inc., Barcelona, Spain; VITO NV (Flemish Institute for Technological Research), Mol, Belgium l The Procter & Gamble Company, Egham, United Kingdom

Development of a defined approach for eye irritation or serious eye damage for liquids

Development of a defined approach for eye irritation or serious eye damage for liquids, neat and in dilution, based on cosmetics Europe analysis of in vitro STE and BCOP test methods 


The focus of Cosmetics Europe's programme on serious eye damage/eye irritation is on development of testing strategies and defined approaches for identification of ocular effects of chemicals in the context of OECD's Guidance Document on an Integrated Approach on Testing and Assessment (IATA) for Serious Eye Damage and Eye Irritation.

Cosmetics Europe created a comprehensive database of chemicals for which in vitro data are available with corresponding historical in vivo Draize eye data. This database allowed further exploration of the initially proposed strategies from the CON4EI project and to identify opportunities for refinement. The current analysis focused on the development of a defined approach, applicable to liquid non-surfactant chemicals, neat and in dilution, that can distinguish between the three UN GHS categories (Cat. 1, Cat. 2, and No Cat.). Combining the modified-protocol Short Time Exposure (STE) test method (OECD TG 491 with extension to highly volatile substances) with the Bovine Corneal Opacity and Permeability Laser Light-Based Opacitometer (BCOP LLBO) test method in a Bottom-Up approach identified 81.2% Cat. 1, 56.3% Cat. 2, and 85.3% No. Cat correctly, with an NPV of 96.7% and a PPV of 68.6%. Therefore, the performance of the defined approach was better than the
standalone test methods.