The implementation of the EU CLP Regulation for mixtures in 2015 led to a reduction of the cut-off levels for mixtures containing severely irritating or corrosive ingredients. As a result, most everyday detergents would be required to carry the same corrosive pictogram on the label as caustic or highly acidic specialty cleaners. However, in most cases, calculation-derived skin and eye hazard classifications do not reflect in-market experience and consumer understanding of the hazardous properties of household detergents. The detergent industry responded to this situation by forming the Detergent Industry Network ‘DetNet’. It is a transparent process that supports mixture classification decisions by sharing data, expertise, and best practices between manufacturers of detergent and cleaning products. At the core of DetNet is its database providing access to compositional information and toxicological data on more than 240 detergents and cleaning products. This paper describes and discusses the main features of DetNet, its organisational structure and database. Based on a case study, the process and functioning of DetNet to support a scientifically sound classification of an untested mixture for skin and eye effects based on data available for similar mixtures is demonstrated.
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Petry et al. (2024) studied this question.
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