Fluxomics in precision nutrition: integrating dynamic metabolic profiling with multiomics

Precision nutrition requires tools that move beyond static dietary biomarkers toward approaches that capture the dynamic nature of human metabolism. Fluxomics, the study of metabolic fluxes, offers valuable opportunities to enrich nutritional research by revealing temporal patterns of dietary responses and clarifying mechanisms that underlie inter-individual variability. In this review, we examine how fluxomics, when combined with metabolomics and broader multiomics approaches, can help identify responder and nonresponder phenotypes, refine metabotype-based dietary recommendations, and strengthen causal inference in nutrition studies. We outline the methodological foundations of fluxomics, including stable isotope tracer administration, high-resolution MS and NMR, and computational frameworks that translate isotopomer data into quantitative flux maps. We further examine recent advances in postprandial profiling, isotopic tracing, and longitudinal repeated-measure designs that are expanding the translational potential of fluxomics in nutrition research. Artificial intelligence is positioned as a supportive analytical layer that facilitates the integration, scalability and interpretation of complex datasets in fluxomics-informed precision nutrition. Finally, we discuss current challenges related to standardization, reproducibility, scalability, and ethical governance. Addressing these barriers through well-designed longitudinal interventions in diverse populations will be essential to advance fluxomics from experimental settings toward more targeted and equitable precision nutrition strategies.