(P23-014-25) In Korea, Developing a Predictive System for Safety Assessment of Combined and Concurrent Intake of Functional Ingredients in Health Foods and Pharmaceuticals Using Big Data

Objectives: In Korea, growing interest in healthy life has led to an increased consumption of healthy beneficial foods (HBFs, including health functional foods, food additives, and others). Additionally, with the rise in the prevalence of chronic diseases, the use of pharmaceuticals has also increased, alongside the combined consumption of HBFs and pharmaceuticals for disease prevention and treatment. These trends have led to calls for more advanced safety management policies and safety prediction systems. This study aims to develop a system that predicts the safety of multiple concurrent intakes of HBFs and interactions with pharmaceuticals.

Methods: To build a safety prediction system for combined and concurrent intake of health functional foods and pharmaceuticals, we first collect ingredients and safety data of HBFs and pharmaceuticals and develop an algorithm that can predict the safety of various ingredient combinations. Second, we aim to determine the status of combined and concurrent intake of HBFs and pharmaceuticals among Koreans. Third, based on the above two studies, we plan to derive safety evaluation priorities for combined and concurrent intake and utilize them in policy.

Results: Data collection and database construction involved collecting data distributed across each ministry and standardizing ingredient names, units, and safety information. Based on the ingredient data and safety data included in the constructed database, an algorithm was built to predict the safety of combined and concurrent intake of HBFs and pharmaceuticals. In addition, through KNHANES analysis, the consumption status of HBFs and pharmaceuticals among Koreans was identified, and the combination of frequently consumed ingredients by population class was derived.

Conclusions: The standardized nomenclature of functional ingredients provides a foundation for an accurate safety prediction system. The developed database is expected to be incorporated into a safety prediction system, providing guidelines for the safe consumption of HBFs and pharmaceuticals.

Funding Sources: This research was supported by a grant (RS-2023-00216069) from Ministry of Food and Drug Safety in 2023-2025 and the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF-5199990614253).