Understanding and predicting the properties of cosmetic compact powders – PredCOMPACT

In the production of cosmetic powders, the lack of reproducibility control is frequently encountered during production, in most cases related to the variable properties of the raw materials as well as the robustness of the manufacturing process. The development of formulations and processes is often empirical since the know-how associated with their design and the derived methodological knowledge are not formally modelled. The few fundamental studies found in the literature about the topic support this argument. Unlike the cosmetic one, several studies have been conducted on investigating and modelling the compression process in the pharmaceutical domain. These studies, conclusive in a pharmaceutical context, allow us to consider adapting this approach to cosmetic powders. This project aims to understand and predict the properties of compact powders by experimental and mechanistic approaches coupled with numerical methods. The challenge is twofold. First, to correlate the powder ingredients' physicochemical properties and the formulated mixtures with the compacts' physicochemical, mechanical, coloured and sensory properties. Second, to understand the mechanisms involved during the compaction process to establish predictive
models, using artificial intelligence (AI) tools to design an intelligent and data-driven compaction process. The results obtained will provide a positive ecological impact in the development and production phases of the cosmetics compacts, inscribing this project in objective 12, "Responsible Consumption and Production", of sustainable development.