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FEND for TB

FEND for TB
FEND 防治结核病
批准号:
9981978
负责人:
David Alland
金额:
$399.8万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-06-04 至 2025-05-31

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中文摘要
翻译
摘要 响应RFA-AI-19-030,新的结核病诊断方法在流行国家的可行性 (fend-TB)领导团队召集了一个由经验丰富的调查人员组成的财团 并制定了一项研究计划,以满足关键的未得到满足的结核病诊断需求。 这项计划得益于在美国国立卫生研究院7年的成功任职期间获得的经验。 DMID资助的结核病临床诊断研究联盟(TB-CDRC),在 领导层、调查人员和现场。该计划已在几个方面进行了调整,以进一步 提高能力以应对目前的外地挑战--与 创新新诊断(FIND)的基础已经得到加强,现在已经完全 将促进获得尖端技术和协调防控结核病工作的伙伴关系 具有全球利益相关者优先事项;印度和秘鲁的临床研究地点已增加到 加快招募和扩大能力,以招募合并疾病和药物的患者- 抵抗力;纳入成熟的分析实验室和修订的技术评估战略 它们共同允许对早期诊断进行合理、灵活和循序渐进的评估;以及 纳入数学建模能力,为结核病流行的最佳诊断策略提供信息 设置。这项提议将检验两个主要假设:a.新的早期结核病诊断,即 目标细菌和/或宿主目标,并将在未来五年内准备好进行评估,将具有 适合用于结核病检测的护理点(POC)/近护理使用的性能特征, 分诊,或药物敏感性测试。B.快速非痰诊断将提供辅助 作为诊断儿童结核病和少菌症算法的组成部分的支持 成人的肺结核病和肺外结核病。具体目标是:1.评估诊断 结核病早期诊断试验的准确性。2.识别新的早期阶段 诊断以供评估,并为每一项制定和实施逐步评估计划。3. 利用经济分析和传输模型设计最优诊断算法。
英文摘要
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.
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Resources, Workforce Development, and Animal Models for the Rutgers RBL
Supplement to G20AI67347 to complete critical upgrades to the Rutgers RBL
  • 批准号:
    10631469
  • 项目类别:
  • 资助金额:
    $191.33万
  • 财政年份:
    2022
  • 负责人:
    David Alland
  • 依托单位:
Key Facility Upgrades for the Rutgers University RBL.
  • 批准号:
    10393791
  • 项目类别:
  • 资助金额:
    $332.84万
  • 财政年份:
    2021
  • 负责人:
    David Alland
  • 依托单位:
Bacterial and Host Heterogeneity in TB latency, persistence and progression
  • 批准号:
    10493254
  • 项目类别:
  • 资助金额:
    $265.83万
  • 财政年份:
    2021
  • 负责人:
    David Alland
  • 依托单位:
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