Shiseido has developed two new artificial intelligence (AI)-based technologies as part of its wider commitment to create new value by integrating digital transformation (DX) with research expertise.
The technologies set out to identify safety information for cosmetic ingredients and assess the biodegradability of ingredients.
The first is a biodegradability assessment method for cosmetic ingredients.
This new technology will support the industry-wide shift towards using environmentally-friendly materials in beauty products.
The AI-based method, developed with the National Institute of Technology and Evaluation (NITE), and the Incorporated Administrative Agency (IAA), predicts the biodegradability of cosmetic ingredients based on their chemical structures, then uses those results to assess cosmetic ingredients.
It builds on an AI-based quantitative structure–activity relationship (AI-QSAR) model for predicting biodegradability developed for Japan’s Act on the Regulation of Manufacture and Evaluation of Chemical Substances.
This model allows the biodegradability of cosmetic ingredients to be assessed quickly and easily without relying on advanced expertise or exhaustive testing, streamlining processes that previously took one to two days to deliver results in real-time.
The second AI system is a safety information identification system, developed to enhance assessment accuracy and efficiency.
This technology will ensure ingredients within cosmetic products are compliant with high safety and quality standards.
The system identifies safety-related information on cosmetic ingredients and determines its relevance for safety assessment with high accuracy, quickly extracting critical information such as repeated-dose toxicity and skin sensitisation.
It sets out to reduce the risk of individual bias and oversights, and allows specialists working on the ingredients to focus on making final safety decisions.
It also enhances the precision and reliability of safety assurance to enable the effective allocation of professional resources toward new research and talent development, as well as enabling the use of ingredients previously shelved due to insufficient information.