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| Funder | European Commission |
|---|---|
| Recipient Organization | Fondazione Ebris |
| Country | Italy |
| Start Date | Dec 01, 2022 |
| End Date | May 31, 2027 |
| Duration | 1,642 days |
| Number of Grantees | 14 |
| Roles | Participant; Coordinator |
| Data Source | European Commission |
| Grant ID | 101095436 |
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 biomarkers350 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.
Fundacion Universitaria Sanitas; Biokeralty Research Institute Aie; Cephalgo; Universita Degli Studi Di Siena; Artificial Intelligence Expert Srl; Fundacio Institut D'Investigacio Biomedica de Girona Doctor Josep Trueta; Perseus Biomics; Istanbul Medipol Universitesi; Ceinge Biotecnologie Avanzate Franco Salvatore Scarl; Mama Health Technologies Gmbh; Stichting Universitaire En Algemene Kinder - En Jeugdpsychiatrie Noord-Nederland; Fondazione Ebris; Fundacio Eurecat; Protobios Ou
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