Cognitive Systems Analysis of Alzheimer's Disease Genetic and Phenotypic Data (U01 Clinical Trial Not Allowed) | PAR 19 269

Opportunity Information: Apply for PAR 19 269

The grant opportunity titled "Cognitive Systems Analysis of Alzheimer's Disease Genetic and Phenotypic Data (U01 Clinical Trial Not Allowed)" (Funding Opportunity Number PAR-19-269) is a National Institutes of Health (NIH) cooperative agreement program aimed at pushing Alzheimer's disease (AD) and Alzheimer's disease related dementias (ADRD) research forward using modern artificial intelligence methods. The central idea is to support teams that can build and apply AI, machine learning, and deep learning approaches (grouped under the term "cognitive systems") to analyze existing, community-accessible datasets and, through that analysis, identify gene mutations or genetic variants that either increase risk for AD/ADRD, contribute to disease mechanisms, or potentially protect against developing these conditions. In practical terms, the FOA is looking for computational approaches that can extract meaningful signals from complex, high-dimensional biological data and connect those signals to disease risk, resilience, and underlying biology.

A key emphasis in the announcement is the use of multiple data types that are already available to the broader research community. That includes genetic and genomic data (such as variant data and other genome-scale measurements) as well as biomarker and phenotypic information, which could span molecular biomarkers, clinical traits, and other measurable characteristics tied to AD/ADRD. The expectation is that applicants will not simply apply generic models, but will propose thoughtful analytic strategies capable of handling the scale and complexity of these datasets, finding patterns that traditional analysis might miss, and producing results that are biologically interpretable and useful for the field. The ultimate deliverable implied by the FOA is stronger evidence about which specific variants matter for disease risk or protection and how those variants may relate to measurable biological or clinical features.

The funding mechanism is a U01 cooperative agreement, which typically indicates substantial scientific involvement or coordination with NIH staff compared with a standard investigator-initiated grant. While the exact award ceiling and number of expected awards are not listed in the provided text, the cooperative agreement format generally signals that NIH anticipates active collaboration, shared milestones, and a structured approach to project management. The activity category is Health, and the CFDA number associated with the program is 93.866. The FOA is explicitly labeled "Clinical Trial Not Allowed," meaning the supported work should focus on computational and analytic research rather than prospective interventional studies that meet the NIH definition of a clinical trial.

Eligibility is broad and includes many organization types across government, academia, nonprofit, and industry. Eligible applicants include state, county, city or township governments, and special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments and other tribal organizations; public housing authorities and Indian housing authorities; nonprofits with and without 501(c)(3) status (excluding higher education institutions under those categories); for-profit organizations other than small businesses; small businesses; and other entities. The FOA also highlights additional eligible applicants such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISIs), Hispanic-serving Institutions, Historically Black Colleges and Universities (HBCUs), Tribally Controlled Colleges and Universities (TCCUs), faith-based or community-based organizations, eligible federal agencies, regional organizations, U.S. territories or possessions, and even non-U.S. entities (foreign organizations). This wide eligibility signals an intent to attract multidisciplinary teams with strengths in AI/ML, genomics, and neurodegenerative disease research, including groups that may bring unique populations, computational infrastructure, or methodological expertise.

From a timeline standpoint, the FOA was created on 2019-05-06, and the original closing date listed is 2022-09-07. Even though that specific date may reflect an earlier submission cycle, the description captures the program's core goals: leveraging AI-driven "cognitive systems" to discover and prioritize AD/ADRD-related genetic variants by integrating and analyzing existing genetic, genomic, biomarker, and phenotypic datasets.

• The National Institutes of Health in the health sector is offering a public funding opportunity titled "Cognitive Systems Analysis of Alzheimer's Disease Genetic and Phenotypic Data (U01 Clinical Trial Not Allowed)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.866.
• This funding opportunity was created on 2019-05-06.
• Applicants must submit their applications by 2022-09-07. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.

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