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The rise of personalized nutrition is reshaping conventional dietary paradigms by shifting from generalized guidelines to individualized dietary interventions tailored to a person’s unique biological and lifestyle characteristics. This transformation is being driven by two cutting-edge technologies: artificial intelligence (AI) and three-dimensional (3D) food printing. AI facilitates the integration and analysis of diverse, high-dimensional data sources—including genomic, metabolomic, gut microbiota, biometric, and behavioral data—to generate precise, real-time nutritional recommendations. In parallel, 3D food printing offers a novel manufacturing approach that enables the physical realization of personalized meals with customized textures, nutrient profiles, and aesthetic forms. This systematic review critically examined the current landscape of AI and 3D printing in personalized nutrition. Following PRISMA guidelines, we conducted a comprehensive literature search across PubMed, Scopus, and Web of Science, identifying 38 relevant studies published between 2015 and 2025. The analysis focuses on clinical applications, consumer health solutions, and food technology innovations. Key findings indicate that AI algorithms have demonstrated effectiveness in predicting dietary needs and improving adherence, while 3D food printing has shown promise in producing tailored meals for populations with specific nutritional requirements, such as elderly and dysphagic patients. However, integration challenges persist, including concerns over algorithmic bias, data privacy, limited regulatory frameworks, and technological scalability. The review also identifies promising future directions, including the use of AI-driven digital twins, multi-omics integration, and advances in sustainable food design using byproducts. Overall, this review highlights the synergistic potential of AI and 3D printing to revolutionize personalized diets and contribute to the future of smart nutrition.
Bhuiyan et al. (Wed,) studied this question.