Transformative Artificial Intelligence and Machine Learning Based Strategies to Identify Determinants of Exceptional Health and Life Span (R21/R33 Clinical Trial Not Allowed)

Funding Agency:
National Institutes of Health

This Funding Opportunity Announcement (FOA) invites applications seeking to develop novel, transformative artificial intelligence/machine learning (AI/ML) strategies and computer automation to integrate, extract, and interpret multi-omic (i.e., genome, epigenome, transcriptome, proteome, metabolome, microbiome, phenome) data sets from human exceptional longevity (EL) cohorts and multiple non-human species that display a wide variation in life span, and to decipher the relationships between DNA, RNA, proteins, metabolites, and other cell variables, as well as links to disease risks and exceptionally healthy aging. The investigative team(s) for this FOA is/are expected to be multi-disciplinary, encompassing expertise in AI/ML and a variety of disciplines, including, but not limited to, aging biology, comparative biology, and bio/chemo informatics. This FOA utilizes the National Institutes of Health's (NIH) Phased Innovation Award (R21/R33) activity code. During the R21 phase, investigative teams will design and develop intelligent and innovative algorithms and novel AI/ML based computational strategies. During the R33 phase, teams will apply the developed AI/ML tools to complex, heterogenous multi-omic data sets from exceptional healthy aging human cohorts and non-human species to discover novel protective molecular factors that influence EL, and to develop translational strategies on omic-based therapeutic target(s) to prevent or delay age-related diseases, including Alzheimer’s disease (AD) and AD-related dementias (ADRD), and enhance human health span.

EL, as illustrated by the lower incidence and delayed onset of age-related disabilities/diseases (e.g., cardiovascular disease, AD, and cancer), represents an extreme phenotype, and the ability to achieve such an exceptional health span is likely to be influenced by differing domain-specific factors that affect preservation of performance in individual physiologic systems (e.g., respiratory, cardiovascular, immune) or functional domains (e.g., mobility, cognition), as well as biological processes that span those systems. EL is believed to be influenced by inherent protective molecular factors in exceptionally long-lived individuals, biological process(es), and interlayer regulatory mechanism(s) that govern the exceptional aging process. This FOA strongly encourages collaboration, coordination, and data and resource exchange among researchers studying EL (including between public-private partnerships), as well as with related NIH-supported omics activities being pursued in different cohorts, such as Trans-Omics for Precision Medicine (TOPMED), Accelerating Medicines Partnership-AD (AMP-AD), and the AD Sequencing Project (ADSP). Prospective applicants are strongly encouraged to contact the agency contacts of the National Institute on Aging (NIA) listed in Section VII to discuss their proposed projects to ensure their responsiveness to this FOA.


  • Letter of Intent Due Date(s): September 21, 2022

  • Application: October 21, 2022

RFA-AG-23-033 Expiration Date October 22, 2022

Agency Website

Amount Description

Application budgets are not to exceed $150,000 in direct costs per year in the R21 phase and $350,000 in direct costs per year in the R33 phase.

Funding Type





Engineering and Physical Sciences
Medical - Basic Science
Medical - Clinical Science
Medical - Translational

External Deadline

October 21, 2022