Although there is 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 fully benefit from the current therapeutic journey.

OPADE’s objective is to identify key biomarkers that support the decision-making process of the healthcare providers through the development and commercialisation of an AI (artificial intelligence) / ML (machine learning) -predictive tool. The project focuses on the gut–brain-axis which plays a major role in MDD. Through clinical investigations, the consortium partners will study the combination between genetics, epigenetics, microbiome and inflammatory networks to:

• Establish patient profiles to predict & 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,

• 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 blood biomarkers correlate with other specific biomarkers.