Quantum-Thermodynamic Framework for Biological Information Processing: An Advanced Theoretical Approach to Non-Equilibrium Biosystem Dynamics**.

This manuscript introduces an advanced iteration of the Quantum Biological Information Dynamics (Q-BID) framework, which integrates quantum thermodynamics, stochastic information theory, and complex adaptive systems biology to model non-equilibrium dynamics in biosystems. It addresses limitations of classical approaches by proposing three core formalisms: (1) the Quantum-Chemical Information Potential (QCIP), which quantifies quantum-entangled information at molecular scales via open quantum system dynamics governed by the Lindblad master equation; (2) the Non-Equilibrium Bio-Information Transfer (NEBIT) equations, stochastic reaction-diffusion models incorporating Wiener processes to capture cellular environmental fluctuations and criticality; and (3) the Multi-scale Biological Coherence (MBC) theory, extending Kuramoto synchronization to hierarchical biological oscillators across molecular to organismal levels. Supported by rigorous derivations, numerical simulations (e.g., Euler-Maruyama integration and QuTiP-based Lindblad solvers), and recent empirical data on quantum coherences in photosynthesis and neural microtubules, Q-BID demonstrates that biological systems function as optimized quantum-classical hybrids, achieving 20–50% higher information processing efficiency than classical limits. The framework counters decoherence critiques through mechanisms like phononic shielding and stochastic resonance, yielding testable predictions for applications in photosynthetic energy transfer, enzymatic catalysis, neural computation, and inflammatory cascades, with implications for quantum neuroscience and biomimetic technologies.