Quantifying metabolic activity in patient tumors could advance personalized cancer targeting. Meghdadi et al. develop a digital twin framework using machine learning to quantify metabolic fluxes in tissues from patients with glioma, identifying which patients may benefit from different targeted metabolic therapies like specialized diets or pharmacologic agents.

The cortex fuels essential physiological processes with glucose-derived carbon, while gliomas fuel their aggressiveness by rerouting glucose carbon pathways and scavenging alternative carbon sources s...