Development of a low-cost point-of-care test for T.. (Pocket)
Development of a low-cost point-of-care test for Tuberculosis detection
Date du début: 1 nov. 2013,
Date de fin: 31 oct. 2016
Pocket will develop a novel point-of-care (PoC) urine test for the detection of tuberculosis (TB), achieving at the same time a low cost (5 to 10 euro end-user cost per test, including depreciation cost of the instrument) and a high accuracy (>80% capture of TB-positive patients, which is much better than the present solutions which reach 60%). The test positions itself between current low-end immunological urine tests with limited accuracy and between high-end expensive nucleic-acid-based tests, which are not truly point-of-care. Throughout this project, special attention will be paid to both end-user requirements (performance, cost, ease-of-use, ...) and to manufacturability. Pocket will go well beyond the development of a mere laboratory prototype, as in the final year of the project, the instrument will be field-tested in Africa and India.The combination of low cost and high accuracy will be achieved through a unique integration of several state-of-the-art concepts, which the partners have separately developed and of which the maturity has already been shown:-a nanophotonic transducer with integrated spectrum analyser developed by UGent (Vernier ring resonator cascade with arrayed waveguide grating spectrometer). This will enable us to eliminate the cost associated with the inclusion of a high-end tunable laser (20k euro) that typically plagues the competing approaches using resonant optical nanophotonic sensors.-a high-confinement silicon nitride (SiN) platform running in a mature small-volume CMOS fab (imec). The use of SiN as opposed to the more traditional Silicon-on-Insulator material system will enable us to move the operating wavelength from 1550 nm to 900 nm, where both the sources and the detectors are significantly less expensive.-a novel TB detection system, based on a unique combination of high-quality antibodies for two different biomarkers.
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