Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action

[EN] Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substan- tial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identification of the underlying pathophysiology for BD is fundamental to realize major health benefits through better treat- ment and preventive regimens. However, to achieve these goals requires coordinated action and innovative approaches to boost the discovery of the neurobiological underpinnings of BD, and rapid translation of research findings into development and testing of better and more spe- cific treatments. To this end, we here propose that only a large-scale coordinated action can be successful in integrating international big-data approaches with real-world clinical inter- ventions. This could be achieved through the creation of a Global Bipolar Disorder Foundation, which could bring government, industry and philanthropy together in common cause. A global initiative for BD research would come at a highly opportune time given the seminal advances promised for our understanding of the genetic and brain basis of the disease and the obvious areas of unmet clinical need. Such an endeavour would embrace the principles of open science and see the strong involvement of user groups and integration of dissemination and public involvement with the research programs. We believe the time is right for a step change in our approach to understanding, treating and even preventing BD effectively.We thank Chris Chang for input on the description of the ENIGMA project. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health in the UK. Ole A. Andreassen is together with Paolo Fusar-Poli co-chairing the Prevention of Severe Mental Disorders (PSMD) cluster, which is supported by the European Brain Research Area project. EBRA has re- ceived funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825348