Regime-Dependent Control in Biomedical Systems A Structural Resolution to Divergent Patient Responses

Contemporary biomedical research continues to struggle with a persistent and unresolved problem: identical interventions often produce stable yet divergent patient outcomes, even under controlled protocols. This work introduces a regime-dependent control framework for biomedical systems, showing that response divergence is not a consequence of noise, genetics, or incomplete biomarkers, but a structural property of bounded biological regulatory systems. Rather than proposing new biological mechanisms or models, the framework reframes biomedical systems as control processes operating across distinct regulatory regimes, where identical inputs may yield internally consistent but divergent outcomes depending on regime occupancy. The record includes: A concise mathematical framework formalizing regime-dependent response behavior A minimal executable Python demonstrator illustrating divergence without stochastic or genetic assumptions A one-page conceptual lens designed for rapid understanding and citation This upload is intentionally model-agnostic, data-independent, and future-proof. It is designed for researchers in biomedical science, systems biology, pharmacology, and AI-assisted medicine who seek structural understanding, not incremental parameter tuning.