Leveraging Artificial Intelligence for Healthy Aging and Dementia Research

Artificial intelligence (AI) technologies, including machine learning (ML), can help harness large amounts of data to better understand factors related to aging and Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRD). NIA is interested in supporting infrastructure, data resources, and research that leverages artificial intelligence to improve the health and well-being of older adults. AI research is funded and conducted by NIA’s extramural research program, intramural research program, and the Center for Alzheimer’s and Related Dementias (CARD).

NIA’s AI Research Portfolio

NIA has a growing portfolio on artificial intelligence research. As many fields of study are increasingly turning to AI, NIA is taking a multi-faceted approach that taps into entrepreneurship and small business programs as well as funding studies related to aging biology, behavioral and social science, geriatrics and clinical gerontology, neuroscience, and biological sciences. Examples including developing AI and machine learning infrastructure and resources, digital health and AI technologies, and using genetic, genomic, and phenotypic data to garner insights into exceptional longevity.

Select projects are highlighted below, and you can explore all NIA-funded AI projects .

Transformative AI-Based Strategies to Identify Determinants of Exceptional Healthspan and Lifespan: This funding opportunity solicited applications to develop & validate AI/ML strategies to harmonize and integrate genetics and multi-omics data from exceptional longevity studies and identify novel predictive biomarkers of aging, drug targets, and therapeutics to prevent age-related diseases including AD/ADRD. Projects highlighted through this funding opportunity leverage AI to:
- Identify molecular traits associated with exceptional longevity.
- Explore exceptional longevity signaling pathways.
- Address challenges for multi-omics data integration and predictive modeling.
- Analyze multi-omics data from multiple data sources.
Entrepreneurial use of AI/ML: NIA’s Small Business Programs manage the largest source of early-stage funding for aging-related research and development. NIA funds several small business awards that use AI/ML in their innovative products spanning diagnostics, caregiving assistance, digital therapeutics, patient monitoring, telecare, and financial planning. These projects include:
- Digital pet avatar to coach self-care behaviors and assist with care coordination.
- Gamification and AI to accomplish activities of daily living for individuals living with AD/ADRD and their caregivers.
- Machine learning-based online therapy platform to increase engagement between people living with dementia and their care partners.
- Novel algorithm to improve detection and diagnosis of Alzheimer’s disease and related dementias.
- Rapid saliva test for noninvasive diagnostic screening of mild cognitive impairment and dementia.
- AI-assisted screening platform for biomarkers of mild cognitive impairment.

AI Funding Opportunities

Explore current NIA funding opportunities in artificial intelligence.

Artificial Intelligence and Technology Collaboratories (AITC) : Through this program, NIA has earmarked $40M from 2021-2026 to fund promising AI technology pilot projects that seek to improve care and health outcomes for older Americans, including persons living with AD/ADRD.
PAR-24-022: Trailblazer Award for New and Early Stage Investigators : This Trailblazer award is an opportunity for new and early stage investigators to pursue research programs at the interface of the life sciences with engineering and the physical sciences. A Trailblazer project ($400,000 in direct costs over three years) may be exploratory, developmental, proof of concept, or high risk-high impact, and may be technology design-directed, discovery-driven, or hypothesis-driven.
NOT-AG-23-004: Notice of Special Interest (NOSI): Small Business Digital Technologies for Early Detection, Characterization and Monitoring of Senescence-Related Changes : This NOSI is intended to promote small business advances on the use of digital technologies for early detection, characterization, and monitoring of senescence-related changes and diseases outside of clinical settings. Developments are encouraged at all scales, from cells to tissues to whole-body.
PAR-22-127: Focused Technology Research and Development : This funding opportunity supports the development of biomedical technologies with demonstrated proof of concept that have remaining significant technical challenges to full implementation and broad utility.
PAR-22-126: Technology Development Research for Establishing Feasibility and Proof of Concept : This funding opportunity supports the development of innovative technologies for research relevant to NIA’s mission.
PAR-22-123: Bioengineering Partnerships with Industry : This funding opportunity solicits applications from research partnerships formed by academic and industrial investigators to accelerate the development and adoption of promising bioengineering tools and technologies that can address important biomedical problems.

NIA AI Webinar Series

Explore current or past learning opportunities from NIA on artificial intelligence.

Upcoming Webinars:

Jan. 22, 2025 | Leveraging AI, clinical data, and knowledge networks to derive insights into Alzheimer’s Disease . Please register in advance .

Past Webinars:

Nov. 22, 2024 | Leveraging Large Datasets and LLMs to Improve Health Equity
May 24, 2024 | Unsupervised Domain Adaptation for Medical Image Analysis
April 11, 2024 | Leveraging Digital Health Technologies and AI/ML to Optimize Care and Deliver Breakthrough Medicines for Older Adults
Dec. 12, 2022 | Lessons from the regulatory process for medical software for image analysis and AI

Contact Information

To learn more about NIA-funded research on artificial intelligence, please reach out to the NIA contact in your area of research.

Extramural Research Program

Division of Aging Biology

Leonid Tsap : Applications of AI/ML to the study of aging, including image analysis and computer vision, health monitoring technologies, bioengineering, bioinformatics, modeling and “digital twins.”

Division of Behavioral and Social Research

Partha Bhattacharyya : AI infrastructure and resources
Dinesh John : Development of Digital Health and AI technology solutions to improve aging and Alzheimer’s-related outcomes. Areas of interest include mHealth, passive and active sensing, wearables, affective computing, ubiquitous computing, health information technology, telemedicine, and just-in time adaptive behavioral interventions.

Division of Division of Geriatrics and Clinical Gerontology

Nalini Raghavachari : AI/ML approaches to explore exceptional longevity.

Division of Neuroscience

Nandini Arunkumar : Bioinformatics and AI/ML approaches to drug repurposing.
Amanda Dibattista : Computational approaches, including multiscale modeling to study the basic science of normal and pathological brain aging
Erin Gray : AI/ML application to neurodegeneration multi-omics and connectomics, electrophysiological datasets, and multiscale modeling.
Richard Kwok : Environmental epidemiology; exposome assessment and risk for adverse, aging, mild cognitive decline and AD/ADRD in population-based studies; AI/ML approaches in epidemiology
Jennie Larkin : Applying AI/ML approaches to genetic, genomic, and phenotypic data.
Marilyn Miller : Support of fundamental genetic studies for AD/ADRD to reveal the etiological underpinnings of AD/ADRD pathogenesis, including those in diverse minoritized populations in the US and globally. Support infrastructure and harmonization of research resources necessary to support the genetics portfolio. Development and application of study resources and analytic approaches to genetic and associated phenotypic data of AD/ADRD. Integrative Analysis of multiple genetic, genomic, and phenotypic data of AD/ADRD.

Intramural Research Program

RNA Regulation Section

Supriyo De : AI applications in genomic data analysis and in medical imaging informatics.

Center for Alzheimer’s and Related Dementias (CARD)

Faraz Faghri and Mike Nalls: Generative AI to accelerate neurodegenerative disease research. Contact CARD.