Using molecular and clinical data to predict outcomes to treatments for depression

Project Code

MRCNMH24Ex Caramaschi

Research Theme

Neuroscience and Mental Health

Full Project Description

Please download the below document for a full project description and to see the full supervisory team.


Up to 50% of people with depression do not benefit from the pharmacological and psychosocial treatments initially prescribed. This often results in the need to switch treatments several times before finding the optimal therapy. In this project you will develop and compare markers for antidepressant treatment efficacy focussing on integrating clinical, demographic, genetic and epigenetic characteristics using machine learning across studies and outcomes.

Lead Supervisor

Dr Doretta Caramaschi

Lead Supervisor Email

University Affiliation