Multi-Scale Models Bridging Levels of Analysis in Aging and Alzheimer's Disease (AD) and AD-Related Dementias (ADRD) (R01 Clinical Trial Not Allowed)
ID: 352211Type: Posted
Overview

Buyer

National Institutes of Health (HHS-NIH11)

Award Range

$0 - $500K

Eligible Applicants

Others

Funding Category

Health

Funding Instrument

Grant

Opportunity Category

Discretionary

Cost Sharing or Matching Requirement

Yes
Timeline
    Description

    The National Institutes of Health (NIH) is inviting applications for a federal grant titled "Multi-Scale Models Bridging Levels of Analysis in Aging and Alzheimer's Disease (AD) and AD-Related Dementias (ADRD)." This funding opportunity aims to develop multi-scale computational models that capture dynamic changes associated with aging and AD/ADRD, utilizing methodologies such as artificial intelligence and machine learning to analyze data across various biological levels. The initiative is critical for enhancing the understanding of aging processes and their impact on AD/ADRD, ultimately informing future research and interventions in public health. Interested applicants can apply for up to $500,000 per year, with a total funding pool of $4 million available for 5-7 grants, and must submit their applications by May 13, 2024. For further inquiries, applicants can contact NIH Grants Information at grantsinfo@nih.gov.

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    Title
    Posted
    The National Institutes of Health (NIH) is inviting applications for a funding opportunity aimed at developing multi-scale computational models related to aging, Alzheimer’s disease (AD), and AD-related dementias (ADRD). This initiative seeks to establish models that encapsulate changes across various biological scales—molecular, cellular, tissue, and behavioral—using methods like artificial intelligence and machine learning. The goal is to harness existing public datasets to understand vulnerabilities and resilience in aging processes affecting AD/ADRD. Key dates include a posted date of February 6, 2024, with a submission deadline of May 13, 2024. Up to $4 million is allocated for funding 5-7 grants, with a maximum budget of $500,000 per year for each application. Eligible applicants include higher education institutions, non-profits, for-profits, governments, and foreign entities. Successful applications will undergo scientific merit reviews based on criteria such as significance, investigator qualifications, innovation, and approach. The overarching aim is not only to bridge computational levels but also to contribute substantially to the understanding of aging and its influence on AD/ADRD, ultimately informing future research and interventions in this critical area of public health.
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