Treating the individual: moving towards personalised eating disorder care

Eating disorders (EDs) are complex and heterogeneous conditions, which are often not resolved with conventional, manualised treatments. Arguments for the development of holistic, person-centred treatments accounting for individual variability have been mounting amongst researchers, clinicians and people with lived experience alike. This review explores the transformative potential of personalised medicine in ED care, emphasising the integration of precision diagnostics and tailored interventions based on individual genetic, biological, psychological and environmental profiles. Building on advancements in genomics, neurobiology, and computational technologies, it advocates for a shift from categorical diagnostic frameworks to symptom-based and dimensional approaches. The paper summarises emerging evidence supporting precision psychiatry, including the development of biomarkers, patient-reported outcomes, predictive modelling, and staging models, and discusses their application in ED research and clinical care. It highlights the utility of machine learning and idiographic statistical methods in optimising therapeutic outcomes and identifies key challenges, such as ethical considerations, scalability and implementation.