EPOCA
Empowering Africa’s Point of Care with Cutting-edge Graphene Biosensing for Rapid Detection and Interconnected Surveillance of Novel Ebola Virus Outbreaks.
This project proposes developing, preclinical and clinical validation of a Point of Care (PoC) biosensing platform based on multiplexed field-effect sensor technology based on graphene monolayers functionalized with specific and oriented recognizing biomolecules (BioGFET). This technology will be used for the rapid and remote diagnosis of Ebola infection by titrating specific biomarkers in peripheral blood samples. To strengthen the diagnostic ability and offer a robust differential triage of patients, serological biomarkers specific for the virus and biomarkers specific for infection severity will be analyzed and compared simultaneously (Figure). Therefore, the final correlation between the achieved parameters will offer a robust and rapid triage of patients, thus, permitting to identify rapidly at the point-of-care potential Ebola outbreaks and offering to physicians a more precise overview of the patient status before knowing the confirming laboratory results. Besides the proposed technology, another key point of this device is represented by its IA-based cloud networking. In fact, once processed and retrieved, the locally achieved diagnostic results will be transmitted to a central server (for example, located in a General Hospital), processed by a custom-made IA software, and, in case of necessity, a health warning will be sent to all the interconnected platforms, independently to their location.
EPOCA project pursues the following objectives:
To design and manufacture a user-friendly cartridge based on multiplexed graphene sensors, enabling efficient confinement and multiparametric analysis of biological samples
Integration of the graphene-based cartridge into an IoT device according to defined standard and data models
Development of a trustable artificial intelligence system for detection of infections episodes and pandemic surveillance
Implementation of an IoT-Ege-Cloud architecture for real time disease monitoring
Validate the diagnostic ability of the proposed biosensor in a real clinical scenario
Partners
HOP UBIQUITOUS SL
UNIVERSIDAD COMPLUTENSE DE MADRID
UNIVERSIDAD DE GRANADA
UNIVERSITA CAMPUS BIO MEDICO DI ROMA
ARINIMI ON BRIDG OU
UNIVERSITY OF GHANA
Medtronic Portugal, Lda
INSTITUT NATIONAL DE RECHERCHE BIOMEDICALE DU ZAIRE
UCBM team is responsible for WP on regulatory aspects, tasks on AI and HTA.