quantum computing

Psychiatric disorders represent some of the most biologically complex challenges in medicine, arising from intricate interactions among genetic, epigenetic, environmental, developmental, and social factors. Advances in artificial intelligence (AI) have improved our ability to analyze large-scale biological datasets, identify biomarkers, and support precision medicine initiatives. However, the growing volume and complexity of genomic and multi-omic information increasingly challenge the capabilities of even the most advanced conventional supercomputers. Quantum computing offers a potential next step in biomedical discovery by enabling rapid analysis of multidimensional datasets, molecular simulations, and optimization problems relevant to genetic medicine and gene therapy. Extending these findings conceptually, we propose the forward-looking hypothesis that continued advances in quantum computing may eventually complement artificial intelligence and human expertise to facilitate increasingly sophisticated analyses relevant to psychiatric genetics and precision medicine. At present, no direct evidence of which we are aware demonstrates clinical implementation of quantum computing in psychiatric genomics. Accordingly, the concepts discussed in this Opinion should be viewed as a forward-looking scientific perspective that builds upon current advances in computational science and biomedicine while awaiting future experimental and clinical validation. Importantly, these advances should complement rather than replace human expertise. Human-in-the-loop systems remain essential for ensuring scientific rigor, ethical oversight, clinical judgment, and patient-centered care. The convergence of quantum computing, AI, genetic medicine, and human expertise may ultimately establish a transformative framework for future precision psychiatry and mental health therapeutics.