Quantifying metabolism in patients with cancer

Static metabolic profiling provides a snapshot of steady-state concentrations but provides no information regarding metabolic fluxes. 

Metabolic flux analysis enables the identification of pathway-specific routes, such as de novo versus salvage nucleotide synthesis, and resolves the flux distribution between various metabolic compartments.

The integration of isotope tracing data with machine learning enables the creation of digital twins, a predictive framework that can identify patient-specific vulnerabilities to targeted therapies and dietary interventions.

Rigorous metabolic modeling frameworks are essential to delineate the dominant biosynthetic inputs for the tricarboxylic acid cycle and to map the metabolic flux toward lactate and nucleotide synthesis in heterogeneous tumor landscapes.
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https://www.cell.com/trends/cancer/fulltext/S2405-8033(26)00239-6
https://sciencemission.com/quantifying-metabolism