Empowering Africa's Point of Care with Cutting-edge Graphene Biosensing for Rapid Detection and Interconnected Surveillance of Novel Ebola Virus Outbreaks.

Grant number: 101145795

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Key facts

  • Disease

    Unspecified
  • Start & end year

    2024
    2027
  • Known Financial Commitments (USD)

    $3,121,460.57
  • Funder

    European Commission
  • Principal Investigator

    JARA Antonio
  • Research Location

    Spain
  • Lead Research Institution

    LIBELIUM LAB SL
  • Research 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.