Psychiatric diagnosis still relies on symptom checklists that were never designed to reflect biology. A peer-reviewed invited review published in Brain Medicine now synthesizes recent advances across four converging domains: conceptual frameworks that move beyond categorical labels, molecular and neurobiological biomarkers, digital phenotyping through smartphones and wearable devices, and machine learning approaches capable of integrating these heterogeneous data streams. The review authors, based at the University of Cambridge, argue that combining objective biological measurement with clinical judgment could yield diagnostic subtypes that predict illness trajectory and guide personalized treatment. They also identify formidable barriers, from data scarcity and algorithmic opacity to regulatory fragmentation and the risk of deepening health inequities.