280M of people worldwide suffers from major depressive disorders (MDD). Although a well-populated therapeutic landscape of anti-depre280M of people worldwide suffers from major depressive disorders (MDD). Although a well-populated therapeutic landscape of anti-depressants, the number of patients in remission is particularly low with not more than 6% of the patients who benefit from the current therapeutic journey. OPADE objective is to identify key biomarkers that support the decision-making process of the healthcare providers. The project focuses on the microbiota – brain -axis which plays a major role in mental health and in particular MDD. Through clinical investigations, the consortium partners will study the combination between genetics, epigenetics, microbiome and inflammatory networks to: - Establish patient profiles to predict and optimise the efficacy of the antidepressants prescribed with an increase in the remission rate and reduction of impairment of real-life functioning, - Establish the possible correlation between neuroinflammatory indices, target indicators of the microbiome, metabolomics, immune-profile linked, epigenomic, enzymatic algorithms, - Evaluate molecular and non-molecular biomarkers that may represent predictive indices of recurrence - Discover new molecular targets for a personalised approach, - Improve the diagnostic accuracy for primary prevention, - Evaluate retrospectively, using accurate anamnesis, the onset of depressive symptoms in adolescence. - Establish how much and to what extent do blood biomarkers correlate with other specific biomarkers 350 patients between 14 and 50 years will be recruited in 6 EU and international countries for 24 months. Real-time EEG and patient cognitive assessment will be collected with blood, stool and saliva samples. Results and analysis will be used to train the AI / ML predictive tool, the main outcome of the project. A patient empowerment tool will be deployed over the project duration.

150M people suffer from mental disorders in Europe & this number is sharply increasing. There are not enough psychiatrists to cope with the situation: a psychiatrist sees 1,000 patients in sessions separated every 3-4 months. Psychiatrists have no way to know if a patient's treatment is working and if there is any risk of relapse/suicide between sessions. A patient's emotional status gives insights into treatment effectiveness and diagnosis of major depressive disorder, but there are no accurate tools to monitor emotions remotely and continuously. Cephalgo has solved this challenge & developed the first accurate, remote & continuous emotion tracker to monitor treatment effectiveness, and predict the best course of treatment for a given patient profile. Combining speech analysis & an AI-driven emotion recognition algorithm, our AI detects emotions with high accuracy & predicts the best treatment to reduce the trial & error approach currently employed in psychiatry.