In order to improve our healthcare system, it is undeniable that the future of modern medicine must focus on a more preventive and personalized approach, notably based on the individual characteristics specific to each patient. In this perspective, clinical metabolomics, which focuses on metabolites, emerges as a particularly interesting and promising approach. Indeed, this science reflects the internal and external stimuli received by an individual, thus capturing their physiological and/or pathological state. Close to the phenotype, it represents the interface between the patient, their genes, and their environment in the broadest sense. Its translational nature requires the conjunction of several expertise areas, both in analytical, biostatistical, and clinical levels. Combined with other data, it allows the generation of predictive or diagnostic models useful for early detection and monitoring of pathologies, taking into account notably the individual characteristics of patients. There are, of course, many obstacles and challenges to overcome for metabolomics to transition into clinical practice, but it is evident that this innovative approach will, in the years to come, find its place among the tools available to clinicians in a more personalized vision of patient care.

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