The National Institutes of Health invites applications for its Transformative Artificial Intelligence and Machine Learning Based Strategies to Identify Determinants of Exceptional Health and Life Span.
Donor Name: National Institutes of Health
State: All States
County: All Counties
Type of Grant: Grant
Deadline: 10/21/2022
Size of the Grant: $350,000
Grant Duration: 5 years
Details:
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 study must be conducted using a two-phase approach in which the first phase, the R21 phase, will be the pilot/innovative phase during which awardees will develop and evaluate novel AI/ML strategies to analyze multi-omics data across human and non-human species with data harmonization tools applicable for AI-based integrative data analyses. This will be followed by a second phase, the R33 phase, during which there will be full-scale implementation focused on applying the AI/ML tools developed during the R21 phase in order to compare and validate findings from human and non-human multi-omic data sets generated by EL studies that can be accessed through the ELITE portal. Both the R21 and R33 phases must be described in the application, each with proposed milestones. The transition from the R21 to the R33 phase will be based on completion of established milestones for the R21 phase. Applications that propose only R21 or R33 activities will not be accepted under this FOA.
R21 Activities
- Priority activities of the R21 phase include, but are not limited to, the following:
- Assess and curate publicly available multi-omic data from longevity studies on human and non-human species.
- Perform data quality control and develop methods for harmonization/normalization by statistical and machine learning tools for merging different sources of data with non-uniform population stratification, scaling, and dimensionality.
- Evaluate and refine, if necessary, existing AI/ML strategies or develop novel methods such as (1) representation learning for unsupervised and supervised dimensionality reduction, feature selection, and feature engineering for compressing high-dimensional omics data;(2) data integration applying hierarchical, stepwise, and concatenation-based integrative analysis of multiple omics data sets to, for example, identify causal pathways from SNPs via cellular pathways to longevity outcomes; (3) transfer learning methods to train/apply ML models across species and domains; and/or (4) improve the explainability and automate the interpretation of models and results across domains.
- Develop implementation strategies using AI/ML tools on EL multi-omic data sets.
R33 Activities
- Activities of the R33 phase include, but are not limited to, the following:
- Harmonize data from multiple EL projects, the Accelerating Medicines Partnership Program® for Alzheimer’s Disease (AMP-AD), the Alzheimer’s Disease Sequencing Project (ADSP), and other publicly available data from longevity studies. Grantees are strongly encouraged to leverage activities similar to those in the ADSP project that are in the process of developing harmonization tools across different AD studies. Applicants may refer to FOA PAR-20-099 for more information.
- Perform AI/ML-based integrative analysis of multi-omic data (human and non-human) to identify causal pathways that mediate protection (e.g., from SNPs via cellular pathways) to longevity outcomes.
- Determine familial relationships from family-based studies, population stratification, and cross-species differences in EL.
- Perform integrated analysis of multi-omic data from non-human species to identify factors that slow the aging process and identify human orthologs.
- Identify novel predictive biomarkers of aging and drug targets.
- Identify pharmacological interventions by exploring publicly available drug discovery databases to prevent age-related diseases, including AD/ADRD, and promote healthy aging.
Transition from the R21 to the R33 phase:
- An initial award for up to two years will be made for the R21 pilot phase. Completion of established milestones proposed within the application will be used to assess potential transition from the R21 to the R33 phase.
- Prior to the end of the R21 phase, grantees will be expected to submit a package requesting transition to the R33 phase. This transition package must include a progress report describing the achievements of the R21 phase, completion of the established milestones, and plans for the R33 phase considering the activities successfully completed during the R21 phase.
- Transition packages will be reviewed by NIA program staff. If approved, the R33 will be awarded without the need to submit a new grant application.
Funding Information
- Award Ceiling: $350,000
- The maximum project period is 5 years in total. The R21 phase may take up to 2 years and the R33 phase may take up to 3 years.
Eligibility Criteria
- Higher Education Institutions
- Public/State Controlled Institutions of Higher Education
- Private Institutions of Higher Education
- The following types of Higher Education Institutions are always encouraged to apply for NIH support as Public or Private Institutions of Higher Education:
- Nonprofits Other Than Institutions of Higher Education
- Nonprofits with 501(c)(3) IRS Status (Other than Institutions of Higher Education)
- Nonprofits without 501(c)(3) IRS Status (Other than Institutions of Higher Education)
- For-Profit Organizations
- Small Businesses
- For-Profit Organizations (Other than Small Businesses)
- Local Governments
- State Governments
- County Governments
- City or Township Governments
- Special District Governments
- Indian/Native American Tribal Governments (Federally Recognized)
- Indian/Native American Tribal Governments (Other than Federally Recognized)
- Federal Government
- Eligible Agencies of the Federal Government
- U.S. Territory or Possession
- Other
- Independent School Districts
- Public Housing Authorities/Indian Housing Authorities
- Native American Tribal Organizations (other than Federally recognized tribal governments)
- Faith-based or Community-based Organizations
- Regional Organizations.
For more information, visit Grants.gov.
