Personalised medicine aims to predict therapeutic response according to a personal profile that includes clinical, biological, and genetic data. This project focuses on depression. It aims to establish an artificial intelligence platform that brings together data from clinical research on the components of these profiles with the purpose of identifying predictors for response to depression treatment. The results will be combined into a single data platform that enables the use of large multimodal datasets to develop predictive models of symptoms and outcome data, thus enhancing the impact of these data. Artificial intelligence approaches will be investigated to identify novel biomarkers that can predict response to treatment. This will help to develop of a decision support system for personalised therapy while identifying the specific ethical and legal requirements that need to be fulfilled.