# FEND for TB

> **NIH NIH U01** · RBHS-NEW JERSEY MEDICAL SCHOOL · 2020 · $3,998,028

## Abstract

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.

## Key facts

- **NIH application ID:** 9981978
- **Project number:** 1U01AI152084-01
- **Recipient organization:** RBHS-NEW JERSEY MEDICAL SCHOOL
- **Principal Investigator:** David Alland
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $3,998,028
- **Award type:** 1
- **Project period:** 2020-06-04 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9981978

## Citation

> US National Institutes of Health, RePORTER application 9981978, FEND for TB (1U01AI152084-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9981978. Licensed CC0.

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