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The need for standardization and database development in food safety management by risk factors is rapidly growing. Leveraging our research team's expertise in food safety-related big data standardization, database construction, and big data analysis technologies, we aim to standardize big data information for food safety evaluation (medical foods, alternative foods, functional foods) and build an integrated database. This database will serve as a FoodTech data hub system, enabling food safety inspectors, industry developers, and researchers to easily utilize it. With the acceleration of an aging society, rising prevalence of chronic diseases, and increasing preference for functional foods, the adoption of medical foods to address obesity, diabetes, and other nutrition-related diseases is expected to expand. However, methods for predicting the safety of such foods and developing AI-integrated platforms remain limited. To address these challenges, our research team plans to utilize its capabilities in database construction, big data analysis, AI-based safety prediction and interpretation technologies, network pharmacology analysis, and multi-component multi-target analysis to build an advanced food safety evaluation platform. This platform will ensure accurate and rapid assessment of the safety of foods (such as medical foods, alternative foods, and functional foods) while fostering the growth of the related industries.