SOURCE-LINKED INTELLIGENCE
Detection of the different phases of Mycobacterium tuberculosis infection and prediction of the development of tuberculosis disease progression by application of novel interferon gamma release assay
perience of the applicant in a LTBI diagnostics, medical microbiology and molecular biology will be combined with hands on training in a field of bioinformatics, and in silico approaches supported by artificial intelligence computational and experimental methods applied for structural analysis of proteins supporting strategic decisions in detection system development. As part of the World Health Organization's (WHO) End TB Strategy to reduce the mortality and incidence rates of TB by 90% and 80%, respectively, in 2025 and further reduction by 95% and 90% in 2035, reverse efforts to focus on TB infection management as one of the TB preventive care approaches for the long-term situation of TB prevention and treatment are highly needed. The main goal of this proposal is to better understand molecular basic of the TB infection and progression aiming identification of the new antigens which later can provide a new avenue for designing of novel interferon gamma release assays (IGRA) test for detection of different phases of TB infection and predict active TB disease progression. We hypo
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 155793.6
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.