Empowering Africa's Point of Care with Cutting-edge Graphene Biosensing for Rapid Detection and Interconnected Surveillance of Novel Ebola Virus Outbreaks.
- Funded by European Commission
- Total publications:0 publications
Grant number: 101145795
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Key facts
Disease
UnspecifiedStart & end year
20242027Known Financial Commitments (USD)
$3,121,460.57Funder
European CommissionPrincipal Investigator
JARA AntonioResearch Location
SpainLead Research Institution
LIBELIUM LAB SLResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Diagnostics
Special Interest Tags
Data Management and Data SharingInnovation
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
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.