课题基金 / 基金详情

RADIATION/NUCLEAR MEDICAL COUNTERMEASURE (MCM) PRODUCT DEVELOPMENT SUPPORT

RADIATION/NUCLEAR MEDICAL COUNTERMEASURE (MCM) PRODUCT DEVELOPMENT SUPPORT
辐射/核医疗对策 (MCM) 产品开发支持
批准号:
9570101
负责人:
POLLY CHANG
金额:
$53.09万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-02-06 至 2020-02-05

项目摘要

项目成果

POLLY CHANG的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The Department of Health and Human Services has assigned the NIH the responsibility to identify, characterize, and develop new medical countermeasures (MCM) against radiological or nuclear threats. As part of the “NIH Strategic Plan and Research Agenda for Medical Countermeasures against Radiological and Nuclear Threats”, the NIAID awarded the Medical Countermeasures against Radiological Threats: Product Development Support Services contract to provide support services for products that may have the potential to become radiation or nuclear medical countermeasures. This contract is tasked with bringing these potential countermeasures to a point at which they can 1) be approved or licensed by the U.S. Food and Drug Administration (FDA) or 2) transition to the Biomedical Advanced Research and Development Authority (BARDA). When approved, these MCMs could be acquired by the Strategic National Stockpile.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
ANIMAL MODEL DEVELOPMENT AND EFFICACY TESTING OF CANDIDATE MCMS
  • 批准号:
    10935874
  • 项目类别:
  • 资助金额:
    $775.16万
  • 财政年份:
    2023
  • 负责人:
    POLLY CHANG
  • 依托单位:
ANIMAL MODEL DEVELOPMENT AND EFFICACY TESTING
  • 批准号:
    10721323
  • 项目类别:
  • 资助金额:
    $865.18万
  • 财政年份:
    2022
  • 负责人:
    POLLY CHANG
  • 依托单位:
NON-CLINICAL STUDIES IN SUPPORT OF IND/NDA/BLA SUBMISSIONS
  • 批准号:
    10706913
  • 项目类别:
  • 资助金额:
    $211.73万
  • 财政年份:
    2022
  • 负责人:
    POLLY CHANG
  • 依托单位:
ANIMAL MODEL DEVELOPMENT AND EFFICACY TESTING
  • 批准号:
    10916149
  • 项目类别:
  • 资助金额:
    $343.36万
  • 财政年份:
    2022
  • 负责人:
    POLLY CHANG
  • 依托单位:
国内基金
海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data