Novel Multimodal Precision Medicine Approaches and the Relevance of Developmental Trajectories in Bipolar Disorder

Olav B Smeland; Cecilie Busch; Ole A Andreassen; Mirko Manchia

doi:10.1016/j.biopsych.2025.03.010

Novel Multimodal Precision Medicine Approaches and the Relevance of Developmental Trajectories in Bipolar Disorder

Biol Psychiatry. 2025 Mar 27:S0006-3223(25)01098-4. doi: 10.1016/j.biopsych.2025.03.010. Online ahead of print.

Authors

Olav B Smeland¹, Cecilie Busch², Ole A Andreassen³, Mirko Manchia⁴

Affiliations

¹ Centre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway. Electronic address: o.b.smeland@medisin.uio.no.
² Centre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
³ Centre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway. Electronic address: ole.andreassen@medisin.uio.no.
⁴ Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, Department of Medicine, University Hospital Agency of Cagliari, Cagliari, Italy; Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada. Electronic address: mirko.manchia@unica.it.

PMID: 40157588
DOI: 10.1016/j.biopsych.2025.03.010

Abstract

There is a pressing need to establish objective measures to improve diagnosis, prediction, prevention, and treatment of bipolar disorder (BD). Multimodal artificial intelligence (AI) tools could provide these means by incorporating various layers of data orthogonally related to BD, including genomics and other omics, environmental exposures, imaging measures, electronic health records, cognition, sensing devices, and clinical variables. These rapidly evolving AI models hold promise to capture the multidimensional complexity of BD and delineate clinically relevant developmental trajectories that could guide clinical care and therapeutic strategies. In this review, we describe the potential of mapping developmental trajectories that underlie BD, outline how novel multimodal models could improve the prediction of BD and related outcomes, and discuss specific clinical use cases and key ethical and practical challenges regarding the development and potential implementation of these multimodal AI solutions to advance precision medicine approaches in BD.

Keywords: Artificial intelligence; Bipolar disorder; Developmental trajectories; Multimodal prediction; Precision medicine.

Publication types

Review