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A hallmark of subclinical metabolic decline is impaired metabolic flexibility, which refers to the ability to switch fuel utilization between glucose and fat according to energy demand and substrate availability. Herein, we propose optimizing metabolic health with digital twins that model an individual's metabolic flexibility profile to gamify the process of health optimization and predict long-term health outcomes. We explore key characteristics of this approach from technological and socioeconomical perspectives, with the objective of reducing the burden from metabolic disorders through driving behavior change and early detection of metabolic decline.
Su et al. (Mon,) studied this question.