Worldwide, MDD affects >300M people, annually causes suicide in 800k people and costs society €1 trillion each year. Many antidepressants are available. Yet, finding the right drug for individual patients remains challenging, as 50% of the patients have not found an effective drug treatment after 1 year. With our assessment tool, we aim to reduce the time to selection of an antidepressant that the patient responds to by 75%. This will have major health and economic benefits.
The goal of this project is to develop DEPREDICT, the first technology that allows very early assessment of antidepressant efficacy in MDD patients based on the patient’s brain MRI signature. This non-invasive assessment will reduce the time to assess treatment efficacy by a factor 4. The main project result will be an innovative MRI analysis software tool for early assessment of antidepressant efficacy based on ‘imaging biomarkers’ discovered using advanced MRI analysis technology (radiomics) and deep learning.
The DEPREDICT a software tool that allows early assessment of response to an antidepressant within 2 weeks after first administration, in patients with major depressive disorder (MDD). The software tool will be developed using artificial intelligence to identify predictive MRI signatures from clinical data and advanced MRI analysis technology. The signatures will be integrated into an assessment tool fully integrated in a cloud-based MRI analysis software environment.
Oslo University Hospital, NordicNeuroLab AS, Vuno Inc.