Toxicological interactions of cosmetic and personal care additives mixtures: An update based on measurement and simulation

Abstract

The toxicity of chemical mixtures may be misestimated, as the assessment of individual chemicals may not adequately reflect their combined toxic effects. However, numerous combinations of chemicals and various interactions make it impossible to measure all possible mixtures. Computational toxicology can help to mitigate this issue, particularly with new methodologies that rely upon alternatives to animal testing. For cosmetic and personal care additives (CPCAs), the ever-increasing of consumption has triggered their complex co-existence in the aquatic environment. To assess their ecological risks, CPCAs experimentally mix at realistic low concentrations with multi-components and different combinations needs to be examined firstly. In this study, toxicity and interactions of multi-component CPCAs mixtures were analyzed taking Daphnia magna as model organism. Also, the contributions of components to the mixture toxicity at different effect levels were discussed. Apparently, the mixture toxicity is closely related to components proportion and impacted by dilution effect. Different forms of combined toxic effects occur in different effect levels. The more components, the less interactions, and the combined toxic effect tends to be additive. Then, Quantitative Structure-Activity Relationship (QSAR) models were developed and evaluated to predict the aquatic toxicity of CPCAs mixtures at various effect levels. The model performance at the median effect level is the best. The descriptors associated most to the toxicity response of CPCA multi-component mixtures are autocorrelation and radial distribution function (RDF), which provide structural information about the spatial distribution of electronic properties and atomic mass.