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Shiseido Develops New Technology to Advance the Cosmetics Industry’s Shift Toward Biodegradable Materials

Degradable and Recyclable Center 2026-02-26 19:30:26
On February 25, Shiseido Co., Ltd. announced the development of two new technologies based on artificial intelligence (AI), aimed at evaluating the biodegradability of cosmetic ingredients and identifying safety information.

Evaluate the biodegradability of cosmetic ingredients using AI

Shiseido has established "Sustainable Innovation: Creating Circular Value" as its core R&D strategy, prioritizing environmental impact factors in the selection of raw materials. To support the entire industry's transition toward using more environmentally friendly materials, Shiseido has developed an AI method to predict the biodegradability of cosmetic ingredients. An artificial intelligence model trained on the chemical structures of biodegradable ingredients and their degradation processes can determine whether the ingredients can be broken down into natural substances such as water and carbon dioxide.

This method is based on an artificial intelligence-based quantitative structure-activity relationship (AI-QSAR) model, a research outcome from Japan's Ministry of Economy, Trade and Industry's commissioned project on chemical safety measures in fiscal year 2022, originally developed for Japan's Chemical Substances Control Law (CSCL). Shiseido conducted novel biodegradability tests, compared the experimentally measured values with the AI-QSAR model's predicted values, and iteratively refined the model in stages, ultimately achieving highly accurate predictions of the biodegradability of cosmetic ingredients.

The AI-QSAR model evaluation method does not rely on the advanced expertise of professionals or conduct extensive experiments, and can quickly and easily assess the biodegradability of cosmetic ingredients, shortening the original evaluation process from 1-2 months to real-time results. In the future, Shiseido plans to promote this AI technology across the entire cosmetics industry to drive the development of technologies that can reduce the overall environmental impact of the industry.

2. A System for Rapid Identification of Cosmetic Ingredient Safety Information

Since establishing its Safety Research Department in 1963, Shiseido has accumulated over 60 years of research experience in safety assessment methodologies. Starting in 2003, the company also began AI research to enhance safety assessment methods using cutting-edge technologies. Safety assessment consists of three stages: (1) reviewing vast amounts of existing information, including internal and external literature; (2) evaluating toxicity—such as irritancy, allergenicity, and genotoxicity—through predictive testing; and (3) conducting final confirmation via human testing. Gathering critical information requires profound expertise and substantial time. A major challenge historically has been insufficient information, making safety assessment extremely difficult and consequently rendering certain ingredients unusable.

Shiseido has developed a system capable of highly accurately identifying safety-related information about cosmetic ingredients and determining its relevance to safety assessments. This system can rapidly extract key information for evaluation items—such as repeated-dose toxicity and skin sensitization—and identify the relevance of literature. This reduces the risk of individual bias and oversights, enabling experts to focus on making final safety decisions.

This study has enhanced the accuracy and reliability of safety assurance, enabling professional resources to be effectively allocated toward new research and talent development. Furthermore, it has allowed previously shelved ingredients—due to insufficient information—to be utilized, paving the way for future innovation in cosmetics.

Looking ahead, Shiseido will continue to advance its digital transformation by expanding the use of AI and strengthening data collaboration with external research institutions. The company aims to create innovations that surpass previous experiences and further accelerate research and development.

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