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Title: Multiplex point-of-care detection of human and avian influenza viruses using an antibody microarray technology
Author: d'Episcopo, Lorenzo
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2013
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Over the last two decades concern about influenza has increased worldwide due to the rising number of human infections caused by an avian virus, H5N1, and the 2009-pandemic of swine-origin H1N1 virus. Counter-measures, for example the selective administration of antivirals to infected individuals, their hospitalization, and the culling of large numbers of infected animals require a prompt and reliable diagnosis, that ideally identifies the type and subtype of the virus and can be carried out at the Point-of-Care (POC). Nowadays instead diagnosis is still largely laboratory-bound, as the available POC-suitable tests are hampered by poor and very variable clinical sensitivity. This PhD was developed in the frame of a European joint effort (Fluarray) that aimed at constructing an automated diagnostic system for the rapid influenza diagnosis. Key technology of the system is an antibody microarray technology that permits the simultaneous analysis of hundreds of antigen-antibody interactions. This research investigated ways to detect the influenza virus using a panel of monoclonal antibodies that were purified, characterized and integrated into the microarray platform. The optimised immunoassay detects and differentiates the influenza nucleoproteins of type A and B at concentrations in the order of few nanograms/ml. A panel of influenza viruses were detected and their type identified within 1 hour hands-on time. The developed microarray platform will soon be integrated into an Automated Diagnostic Analyser for Microarrays (ADAM) developed by the collaborating partner Microtest Matrices. It is envisaged that the system will be a consistent aid in the influenza diagnosis and sensibly facilitate and speed up diagnostic procedures.
Supervisor: Crisanti, Andrea Sponsor: Microtest Matrices
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available