The era of precision psychiatry: toward a new paradigm in diagnosis and care

Mental disorders affect nearly one billion persons worldwide, having a substantial burden on individuals, families, and healthcare systems. Current diagnostic and therapeutic approaches could fail to reach optimal outcomes, highlighting the need for more effective and personalized interventions. Precision psychiatry aims to address this challenge by integrating multidimensional data, ranging from genomomics and epigenomics to neuroimaging and psychometric assessments, through advanced computational tools such as machine learning and artificial intelligence. This transdisciplinary approach could allow the study of biologically informed endophenotypes, improve diagnostic accuracy, and support individualized treatment strategies. Emerging technologies, including pharmaco-neuroimaging, virtual histology, and large-scale consortia, are advancing the field by elucidating the molecular and circuit-level correlates of mental disorders. Although significant progress has been made, the translational gap between research and clinical practice remains a critical issue. Effective implementation will require the systematic integration of bioinformatic tools, big data analytics, and clinician-guided interpretation, in a context in which the evolving landscape of precision psychiatry continues to prioritize therapeutic alliance and individualized patient care.