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Collaborative Research: Balancing the Portfolio: Efficiency and Productivity of Federal Biomedical R&D Funding

Collaborative Research: Balancing the Portfolio: Efficiency and Productivity of Federal Biomedical R&D Funding
合作研究:平衡投资组合:联邦生物医学研究的效率和生产力
批准号:
1158699
负责人:
Padhraic Smyth
金额:
$29.73万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-15 至 2016-07-31

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中文摘要
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英文摘要
This cross-disciplinary, cross-institution collaborative research project combines economic analysis with state-of-the-art methods from statistical machine learning, to assess the relative efficiency and efficacy of research and development expenditures across the U.S. National Institutes of Health (NIH) portfolio of extramural projects. The novel combination of econometrics, topic modeling, and document classification permits analysis of massive collections of grant abstracts and scientific publications, identification of latent research topics present in NIH-funded research, assessment of possible spillover effects across research topics, and evaluation of causal linkages between changes in NIH funding by research topic and scientific advances. Two specific research outcomes are considered: scientific publications, classified by topic; and pharmaceutical innovation, measured by drugs entering into clinical development to treat specific diseases. Planned research also includes refinement of existing economic theory to produce normative evaluations of the allocation of public research spending.Broader Impacts: This research will inform key policy questions related to federal funding of biomedical research. First, fiscal austerity requires careful attention to the nation's research portfolio and investments. This project will describe and evaluate the productivity of those investments, as a first step towards policy recommendations for rebalancing the portfolio, to maximize society's expected return on investment. Second, if NIH funding for basic research spurs increased pharmaceutical innovation, NIH possesses an important policy tool to promote pharmaceutical R&D in areas of high therapeutic importance or significant health disparity.
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RI: Medium: Assessment of Machine Learning Algorithms in the Wild
  • 批准号:
    1900644
  • 项目类别:
    Standard Grant
  • 资助金额:
    $119.99万
  • 财政年份:
    2019
  • 负责人:
    Padhraic Smyth
  • 依托单位:
NRT-DESE: Team Science for Integrative Graduate Training in Data Science and Physical Science
  • 批准号:
    1633631
  • 项目类别:
    Standard Grant
  • 资助金额:
    $296.72万
  • 财政年份:
    2016
  • 负责人:
    Padhraic Smyth
  • 依托单位:
III: Small: Statistical Learning Algorithms for Micro-Event Time Series Data
  • 批准号:
    1320527
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.99万
  • 财政年份:
    2013
  • 负责人:
    Padhraic Smyth
  • 依托单位:
CRI: Collaborative Research: Improving Experimental Computer Science with a Searchable Web Portal for Datasets
  • 批准号:
    0551510
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $19.99万
  • 财政年份:
    2006
  • 负责人:
    Padhraic Smyth
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)