{"@context":"https://schema.org","@type":"ScholarlyArticle","headline":"Quantum medicine: A quantum-mechanical framework for redox biology, disease and precision medicine.","author":[{"@type":"Person","name":"Ji-Yong Sung"},{"@type":"Person","name":"Jae-Ho Cheong"}],"datePublished":"2026","isPartOf":{"@type":"Periodical","name":"Clinical and translational medicine"},"identifier":"https://doi.org/10.1002/ctm2.70598","description":"Abstract\n \n Background\n 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.\n \n \n Rationale\n 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.\n \n \n Content\n 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.\n \n \n Conclusion\n 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.\n \n \n Key points\n \n \n \n Quantum biomedicine redefines life as a dynamic equilibrium sustained by quantum coherence, tunnelling and redox resonance.\n \n \n Hybrid quantum–classical algorithms, such as VQE and QPE, enable first‐principles modelling of redox and spin‐dependent reactions with near‐experimental accuracy.\n \n \n NISQ‐era hardware supports proof‐of‐concept simulations of electron tunnelling and radical‐pair dynamics, bridging computation with measurable biophysics.\n \n \n Integration of quantum simulations with spectroscopy and cryo‐EM establishes a quantum–experimental–clinical (QEC) pipeline linking theory, experiment and medicine.\n \n \n Ethical, educational and governance frameworks are essential for equitable, transparent and sustainable implementation of quantum health technologies.\n \n \n \n ","url":"https://innscience.ca/es/community/literature/doi_10_1002_ctm2_70598"}