Stochastic Pharmacokinetic Escape: A Field-Theoretic Approach to Fluctuation-Induced Tumor Relapse

Abstract

Classical mathematical oncology employs deterministic mean-field models predicting that sufficiently high chemotherapy doses drive tumor density to zero. We show that this apparent cure is an artifact of neglecting demographic fluctuations. We construct a nonequilibrium stochastic PK-PD field theory combining a two-compartment pharmacokinetic model with a stochastic tumor-immune sector in the Doi-Peliti formalism, then map it to coupled multiplicative Langevin equations via the Martin-Siggia-Rose/Janssen-De Dominicis approach. In immune-depleted sanctuary sites, the dynamics reduce to a time-dependent Feller diffusion whose Fokker-Planck equation yields an analytical survival functional: demographic noise implies a strictly nonzero relapse probability for tumor micro-clusters under high-dose chemotherapy. Standard bolus administration acts as a nonselective annihilation process, driving immune fields into an absorbing state and creating a spatially immune-depleted vacuum that enables fluctuation-induced relapse -- Stochastic Pharmacokinetic Escape. We derive quantitative conditions under which metronomic dosing and adjuvant immunotherapy suppress this stochastic window of vulnerability. A model-agnostic analysis of 1461 longitudinal patient records shows that the majority of evaluable lesions exhibit a nadir followed by measurable regrowth rather than monotonic elimination; fitting the model's drift functional to these trajectories reproduces this pattern quantitatively, and a direct test of the predicted demographic-noise scaling law reveals size-dependent noise largest at the smallest observed tumor volumes, consistent with the proposed mechanism.