We present a minimal computational model of biological aging based on the dynamics of coupled oscillators. The model proposes that aging emerges primarily from progressive desynchronization among biological regulatory systems, rather than from the accumulation of component-level damage alone. A positive feedback loop -- increasing variance sigma raises synchronization cost, which depletes the regulatory buffer B and coupling strength K, which further increases sigma -- produces aging dynamics consistent with empirically observed patterns including the Gompertz mortality law. Crucially, the model generates a quantitative prediction regarding intervention efficacy: local repair of a single oscillator reduces system-wide desynchronization by (2f-f²) /n, where f is repair effectiveness and n is system complexity. This scaling law implies that local anti-aging interventions, highly effective in simple systems such as mice, lose therapeutic significance in complex systems such as humans. Global synchronization interventions, by contrast, maintain constant effectiveness independent of n. The model provides a mechanistic account of the well-documented failure to translate anti-aging findings from animal models to humans.
Piotr Czarnecki (Mon,) studied this question.