Multi-Omics and Artificial Intelligence in Functional Food Innovation: Current Progress and Future Perspectives

Abstract

The importance of the development of functional food with bioactive compounds with scientifically proven physiological effects is significant as a good strategy to provide health and prevent chronic diseases. The development of multi-omics technologies such as genomics, transcriptomics, proteomics, metabolomics, microbiomics, and foodomics has greatly improved the understanding of the nutrient–host interactions and the molecular mechanisms involved in the functional efficacy of food. At the same time, AI has revolutionized the functional food research field by allowing for the efficient integration of multi-omics data from large cohorts, predictive modeling, the discovery of biomarkers, and the development of personalized nutrition. The review highlights the latest developments in the integration of multi-omics and AI tools in functional food innovation and their applications in bioactive compound identification, food quality and safety testing, precision nutrition, and prevention of diseases. The review also addresses nutrigenomics, nutrition of the gut microbiome, and digital health technologies of personalized functional foods using AI. Furthermore, key data integration, data standardization, explainable AI, and ethical and regulatory issues are discussed thoroughly. The prospects focus on the integration of multi-omics, wearable technology, and precision nutrition with AI to enable the rapid development of next-generation functional foods. Finally, the combination of multi-omics and AI provides a holistic systems biology view, allowing for evidence-based functional food innovation, individual nutrition for optimal health, and sustainable nutrition strategies for the benefit of the planet.