We propose a novel conceptual model, the Quantum-Metabolic Genome Instability Cycle (QMGIC), linking metabolic stress, mitochondrial quantum decoherence, and genome instability. The model integrates quantum biological insights with classical molecular biology to explain a cyclic mechanism underlying the onset and propagation of mutations. This work builds on recent discoveries in mitochondrial signaling, DNA repair failure, and quantum coherence in biological systems. Understanding the QMGIC may provide a foundation for new hypotheses in aging, cancer, and mitochondrial disease.
We propose a novel conceptual model, the Quantum-Metabolic Genome Instability Cycle (QMGIC), linking metabolic stress, mitochondrial quantum decoherence, and genome instability. The model integrates quantum biological insights with classical molecular biology to explain a cyclic mechanism underlying the onset and propagation of mutations. This work builds on recent discoveries in mitochondrial signaling, DNA repair failure, and quantum coherence in biological systems. Understanding the QMGIC may provide a foundation for new hypotheses in aging, cancer, and mitochondrial disease.
This study explores the potential of quantum computing as an alternative information processing approach, utilizing quantum bits (qubits), superposition, and entanglement to significantly expand computational capabilities in the healthcare domain. It is evident that quantum mechanics has become a foundational component in the construction of our contemporary physical reality. This scientific field is distinguished by its rapid advancement and the potential to transform various aspects of our daily lives. In this era, quantum biology is of significant importance and has the potential to act as a transformative force, particularly in the field of medicine, specifically in addressing the challenges posed by cancer. Cancer is defined as a complex and abnormal alteration of cells, orchestrated through intricate signaling pathways. This transformation is characterized by the accumulation of deleterious mutations. The concept of phenocopy, representing genetic mutations influenced by the environment, challenges the linear process line of molecular biology involving DNA, RNA, and proteins. Notwithstanding the augmented focus on quantum biology in recent decades, a plethora of unresolved issues persist within the domain of cancer biology, thereby giving rise to unexplored avenues. Quantum theory has demonstrated its ability to explain models related to biological and biochemical processes, encompassing the effects of carcinogens on genes, the mechanism of interactions between chemotherapy drugs and DNA, and the understanding of DNA mutations and defective protein synthesis. Recent skepticism among quantum physicists regarding the fundamental role of quantum effects in biology has emerged, particularly with regard to open quantum systems and the impact of decoherence on the destruction of coherence necessary for significant quantum effects. The document under scrutiny herein undertakes an investigation of recent studies that are rooted in the principles of quantum physics, with a particular focus on the manner in which these principles apply to the domains of cancer biology and metabolism.
BACKGROUND: Key biological processes underlying health and disease-including electron transfer, redox regulation, and radical-mediated signaling-are fundamentally governed by quantum-mechanical principles. These processes are central to mitochondrial function, metabolism, and cellular signaling, yet their biomedical implications have remained difficult to address using classical computational approaches. RATIONALE: Recent advances in quantum computing, quantum sensing, and quantum machine learning enable direct simulation and measurement of quantum phenomena in biologically relevant systems. Hybrid quantum-classical algorithms, such as the Variational Quantum Eigensolver and Quantum Phase Estimation, now provide first-principles access to redox potentials, electronic couplings, and spin-dependent reactions that are directly linked to disease mechanisms. These developments establish the foundation for quantum biomedicine as a translational framework bridging molecular physics and clinical medicine. CONTENT: This review synthesizes current progress in the application of quantum technologies to biomedicine, emphasizing translational relevance. We discuss quantum-informed modeling of cancer metabolism and redox rewiring, protein misfolding in neurodegenerative diseases, immune and inflammatory signaling, infectious disease mechanisms, and drug discovery. We further propose a Quantum-Experimental-Clinical (QEC) pipeline that integrates quantum simulations with experimental validation and multi-omics clinical data, enabling mechanistic interpretation of disease phenotypes and identification of redox- and spin-sensitive therapeutic targets. CONCLUSION: Quantum biomedicine introduces a new mechanistic layer that links electronic-scale processes to clinical phenotypes. While current implementations are constrained by NISQ-era hardware, rapid advances in quantum algorithms and sensing technologies position quantum approaches as emerging tools in precision and translational medicine. Strategic integration of quantum methods with experimental and clinical workflows may accelerate biomarker discovery and therapeutic development. KEY POINTS: Quantum biomedicine redefines life as a dynamic equilibrium sustained by quantum coherence, tunnelling and redox resonance. Hybrid quantum-classical algorithms, such as VQE and QPE, enable first-principles modelling of redox and spin-dependent reactions with near-experimental accuracy. NISQ-era hardware supports proof-of-concept simulations of electron tunnelling and radical-pair dynamics, bridging computation with measurable biophysics. Integration of quantum simulations with spectroscopy and cryo-EM establishes a quantum-experimental-clinical (QEC) pipeline linking theory, experiment and medicine. Ethical, educational and governance frameworks are essential for equitable, transparent and sustainable implementation of quantum health technologies.
This work presents a rigorous, cross-domain review of mechanisms in living systems that exhibit mathematical parallels with quantum error correction (QEC). Rather than relying on metaphor or loose analogy, the paper traces concrete isomorphisms between stabilizer codes, decoherence-free subspaces, dynamical decoupling, and the specific molecular architectures that sustain high-fidelity biological information. The review synthesizes evidence across three domains—genomic stability, neural information processing, and metabolic coherence—and examines proton tunneling, tautomer suppression, nuclear spin protection, microtubule lattice codes, excitonic transport, ENAQT, vibronic stabilizers, and the radical-pair magnetoreception model. By comparing these biological processes to formal properties of QEC (Knill–Laflamme conditions, threshold theorems, syndrome extraction, and topological protection), the work argues that biological robustness can be understood as an evolved form of error-correcting architecture. The conclusion highlights the role of noise-structured environments, energetic cost constraints, and threshold behavior, and proposes that QEC-style mechanisms may be universal to life operating near the quantum–classical boundary.
DNA replication upholds genomic integrity with remarkable precision, rectifying inaccuracies that emerge from quantum-level phenomena. This paper introduces a novel framework that models this biological process using the formalism of quantum error correction .We propose that genetic information encoded in DNA base pairs can be represented as the codespace of a Biological Stabilizer Code , where cellular proofreading and mismatch repair mechanisms function as an active error correction protocol.We provide comprehensive proofs that illustrate the code’s capacity to preferentially rectify the most likely types of mutations, thereby guaranteeing elevated logical fidelity. We establish a biological equivalent of the quantum threshold theorem, demonstrating that high-fidelity replication can be achieved if the inherent mutation rate falls below a critical threshold. The performance of the BSC is corroborated through simulations conducted in Qiskit, which reveal its superior efficacy compared to symmetric codes under biologically plausible noise conditions. This research establishes a quantitative relationship between the principles of fault-tolerant quantum computation and the mechanisms that uphold the stability of life’s genetic code.
Time may be viewed as an emergent consequence of increasing information entropy. I explore a toy quantum‑information model in which DNA is treated as an open quantum system. In this framework, weak, time‑dependent perturbations (potentially arising from thermal fluctuations, ionic microfields, metabolic noise, or electromagnetic signals) bias the micro‑timing of events during replication and repair. These slight timing shifts can influence the fate of transient electronic and protonic configurations (including short‑lived tautomeric states driven by proton‑transfer tunnelling), subtly altering mutation probabilities. To test this idea, I map nucleotides in the Mycobacterium tuberculosis genome to constrained qubit states and quantify informational structure using Shannon and von Neumann entropies and coding to non‑coding correlation metrics. Simulations of Hamiltonian dynamics under physiologically plausible perturbations show that real genomic segments exhibit distinctive dynamical signatures compared with controls. I also examine a variant in which a weak, slowly varying external signal is introduced as a background "beat" against which DNA dynamics can be compared. Because a Doppler shift in electromagnetic waves encodes the flow of time through the relative motion of source and observer, a cosmic microwave background (CMB) with a tiny frequency drift provides a conceptual clock and a source of informational entropy: it feeds a time‑correlated input into the DNA quantum system, allowing the molecule to sample cosmic time and translate it into a biological scale by modulating tunnelling probabilities and thus mutation patterns. This CMB‑inspired drive is simply a convenient illustration; the model does not rely on it, and other sources of weakly structured entropy could be tested. Across simulations, sequence‑dependent responses to both intrinsic and structured perturbations generate testable predictions: changing the structure or timing of these weak perturbations should produce reproducible shifts in mutation spectra. This framework connects cellular ageing and evolution to the flow of cosmic time and suggests experiments to probe DNA's sensitivity to time‑dependent perturbations.
There is no doubt that quantum mechanics has become one of the building blocks of our physical world today. It is one of the most rapidly growing fields of science that can potentially change every aspect of our life. Quantum biology is one of the most essential parts of this era which can be considered as a game-changer in medicine especially in the field of cancer. Despite quantum biology having gained more attention during the last decades, there are still so many unanswered questions concerning cancer biology and so many unpaved roads in this regard. This review paper is an effort to answer the question of how biological phenomena such as cancer can be described through the quantum mechanical framework. In other words, is there a correlation between cancer biology and quantum mechanics, and how? This literature review paper reports on the recently published researches based on the principles of quantum physics with focus on cancer biology and metabolism.