FEND for TB

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ABSTRACT In response to RFA-AI-19-030, Feasibility of Novel Diagnostics for TB in Endemic Countries (FEND-TB) the leadership team has brought together a consortium of experienced investigators and clinical sites and developed a research plan to address critical unmet TB diagnostic needs. This program benefits from experience gained during the successful 7-year tenure of the NIH DMID-funded TB-Clinical Diagnostics Research Consortium (TB-CDRC), with overlap in leadership, investigators and sites. This program has been adapted in several ways to further enhance capacity to meet the current challenges in the field -- the successful collaboration with the Foundation for Innovative New Diagnostics (FIND) has been strengthened to now a full partnership that will facilitate access to cutting edge technologies and alignment of FEND-TB work with global stakeholder priorities; clinical study sites in India and Peru have been added to accelerate recruitment and augment capacity to enroll patients with co-morbidities and drug- resistance; inclusion of a mature analytic laboratory and revised technology evaluation strategy that together allow for rational, nimble, step-wise evaluation of early-stage diagnostics; and inclusion of mathematical modeling capacity to inform optimal diagnostic strategies in TB endemic settings. This proposal will test two main hypotheses: A. Novel early stage TB diagnostics, that target bacterial and/or host targets and will be ready for evaluation in the next five years, will have performance characteristics suitable for point of care (POC)/near-care use for TB detection, triage, or drug susceptibility testing. B. Rapid non-sputum diagnostics will provide ancillary support as components of algorithms for the diagnosis of childhood TB as well as paucibacillary pulmonary TB and extrapulmonary TB in adults. Specific Aims are: 1. To evaluate the diagnostic accuracy of early stage diagnostic tests for tuberculosis. 2. To identify new early stage diagnostics for evaluation, and to develop and implement for each a stepwise evaluation plan. 3. To use economic analysis and transmission modelling to design optimal diagnostic algorithms.