Coma induced by Out of Hospital Cardiac Arrest (OHCA) is a major global health problem. An early and accurate prognostication is the cornerstone for the clinical management of these patients, mainly because the vast majority of the related mortality observed in this setting comes from withdraw life-sustaining treatment (WLST) decisions following prognostication of a poor neurological outcome. However, currently recommended predictors, based on a multimodal assessment encompassing the use of one fluid-derived biomarker in isolation (NSE, Neuron Specific Enolase) are only informative in a minority of patients, leaving up to 50-77% of anoxo-ischemic coma patients in a ‘gray zone’ of prognostication. Moreover, a further important gap in the existing anoxic coma literature concerns the limited treatment strategies to enhance neurological recovery after OHCA. The current proposal aims to develop and validate over the course of 4 years a new mechanistically coherent battery of fluid-derived biomarkers for the early neuroprognostication and individually-tailored treatment for anoxic coma patients. As a significant paradigm shift in the field, we seek to identify the best combination of fluid-derived biomarkers related to key neuroinflammatory, neurodegenerative and neuroprotective (3N) processes known to be triggered by cardiac arrest. To this end, we will use for the first time in this setting ground-breaking and highly synergic deep 3N multiomics profiling methods that will be empowered by innovative artificial intelligence methods. Following a step-wise approach, first we will capitalize on already existing data to identify among a panel of candidate biomarkers from peripheral blood samples. Second, to increase the robustness and explainability of the predictive models, we will cross-validate the fluid biomarkers and characterize them in relation to well-established 3N hallmarks using multi-dimensional data from an additional independent prospective patient cohort. Finally, a third cohort will be gathered to ensure the prospective and external validation of the identified fluid biomarkers at a European level, aiming to guarantee the predictive model’s generazability and inform the feasibility and design of future clinical trials. The final deliverable will consist of a potential game-changer AI-based predictive classifier for anoxic coma patients based on easily accessible and inexpensive peripheral blood-derived biomarkers. The whole dataset will be made FAIR to facilitate data sharing with the broader research community.