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First onset of mental illness predominantly occurs before 25-years of age when early intervention is effective and could avert future comorbidity.
Psychiatric predictions for individuals are most needed at this time to identify risk and select treatments in the context of often heterogeneous, diffuse, and dynamically changing presentations.
Progress in building personalised predictive algorithms is encouraging, but it is commonly conducted within discipline boundaries that separate children, adolescents, and young adults. Often, methods are also siloed within specific diagnoses. Such separation results in missed opportunities to capitalise on shared concepts, methods, datasets, and statistical models.
This paper outlines how interdisciplinary and transdiagnostic collaboration could lead to the future of personalised care by introducing the vision, organisation, and aims of the Prediction of Early Mental Disorder and Preventative Treatment Centre of Research Excellence (pre-empt).
Following an introduction of research opportunities, six key components of the Centre will be outlined including: interdisciplinary collaboration, data harmonisation, methods sharing, and development of decision support tools.
Cutting-edge methodological avenues will be addressed including network analysis, joint modelling, and time series analyses. The implementation of research methodology guidelines within the Centre will assist in the production of reproducible, transparent, and open-source techniques and models.
When combined, the paper will provide a roadmap to guide future research towards interdisciplinary approaches that avert, delay, or ameliorate the onset of mental illness across early life.
