Response to Metabolic Interventions
The energy metabolism model can simulate the effects of interventions targeting specific parameters. Three examples illustrate the approach.
1 CoQ10 Supplementation
Coenzyme Q10 (ubiquinone) functions as an electron carrier between Complexes I/II and Complex III. Supplementation increases the ubiquinone pool \([\text{UQ}]_{\text{total}}\), which the model predicts will increase Complex I flux (complex i) and reduce ROS production at Complex III. The predicted effect is modest in the model—a 5–15% increase in maximal ATP production rate for the parameter ranges consistent with typical supplementation doses—which aligns with the small but statistically significant improvements reported in clinical trials (Castro-Marrero et al. 2021).
2 NAD⁺ Precursor Supplementation
Supplementation with nicotinamide riboside or nicotinamide mononucleotide increases the total \(\text{NAD}^\text{+}\) pool, modeled by increasing \([\text{NAD}^+]_{\text{total}}\). The model predicts that this increases Krebs cycle flux (through the \(\text{NAD}^\text{+}\)/NADH ratio term in krebs flux) and shifts the ROS balance favorably. The predicted magnitude of benefit depends on the degree of baseline \(\text{NAD}^\text{+}\) depletion (\(\gamma\) parameter), suggesting that patients with lower baseline \(\text{NAD}^\text{+}\) levels would show greater response — a testable prediction for treatment stratification. No ME/CFS-specific NAD+ precursor RCT has been published (as of 2026); the closest evidence is Schreiber 2025 (\(n = 900\), nicotinamide 1000 mg/day in post-COVID, significant symptom reduction).
3 Prediction Limitations
The metabolic intervention models assume that the primary effect of supplementation is on the targeted metabolite pool, neglecting absorption, distribution, and metabolism of the supplement itself. Pharmacokinetic modeling of supplement bioavailability would be required for quantitative dose–response predictions. Furthermore, the models do not account for potential off-target effects or interactions between supplements.