December 22, 2025—The a2 Collective is pleased to announce the funding of 28 new pilots leveraging advancements in artificial intelligence (AI) and related technologies to improve care, health outcomes, and overall quality of life for older adults—including for those living with Alzheimer’s disease and related dementias (AD/ADRD), as well as their caregivers.
These projects comprise the fifth annual cohort funded through the a2 Pilot Awards, a national competition that has allocated more than $40 million over 5 years to support projects developing novel technologies and algorithms for application in the areas of healthy aging and AD/ADRD.
Funded by the National Institute on Aging, a part of the National Institutes of Health, through the Artificial Intelligence and Technology Collaboratories (AITC) for Aging Research program—or a2 Collective—the awards support pilot projects selected by AITCs centered at Johns Hopkins University (JH AITC), the University of Massachusetts Amherst (MassAITC), and the University of Pennsylvania (PennAITech). In addition to awards of up to $200,000 in direct costs provided over a 1-year period, projects also benefit from resources and multidisciplinary mentorship from the funding AITC.
The 28 projects funded in Cohort 5 expand upon the a2 Collective’s investment in user-centered applications of AI and other emerging technologies to enable older adults to age in place, empower them with crucial health information for greater independence and safety, and reduce the burden of frequent in-person visits and physician workload on the healthcare system. Key contributions these projects target include developing novel, noninvasive wearable smart devices to improve independent living and reduce hospital visits; providing resources to support caregivers and improve their mental well-being; utilizing AI to identify novel biomarkers of aging and age-related conditions to support timely interventions that promote independence; and developing AI systems to improve provider communication and inform older adults’ healthcare decisions.
The fifth cohort of pilot studies represents 17 U.S. states and territories, including first-time pilot awardee locations of New Jersey, Maine, and Indiana. The proportion of pilots led by nonacademic institutions (43%) compared to academic ones (57%) remains balanced, an ongoing trend that reflects the a2 Collective’s flexibility in funding modalities to meet the needs of university investigators, healthcare institutions, founder-stage companies, and established startups alike.
Compared to prior cohorts, this class of pilot awards has an increased focus on disease stage–appropriate technology adaptations (43%). The shift toward stage-appropriate adaptations highlights the rising success of AI technologies in detecting and analyzing nuanced patterns in large datasets, which can enhance the precision of diagnostics and treatments for older adults. Other notable focus areas in this cohort include chronic age-related conditions and comorbidities (39%), decision support and education (36%), and availability and accessibility of resources and care (29%).
Many of the Cohort 5 pilots aim to enable stage-appropriate technology adaptations by identifying biomarkers for specific age-related conditions. A pilot led by Anis Davoudi, PhD, at Johns Hopkins University showcases this effort by using AI-powered smart glasses to identify digital markers of mild cognitive impairment in older adults based on eye movement and speech characteristics, enabling timely intervention and personalized dementia care planning.
“Detection of health decline is quicker, earlier, and more precise with the help of AI systems that can detect subtle changes in vitals, movement, speech, and much more,” said Albert Lee, PhD, co-director of the a2 Collective Coordinating Center. “These AI approaches combined with wearable technologies can provide physicians with crucial health information that would otherwise be burdensome to obtain in the clinic. And with this information, physicians have more opportunities to provide timely diagnosis, treatments, education, and support to older adults and their caregivers.”
Studies funded in the fifth a2 Pilot Awards cohort are researching and developing AI technologies that are designed for use by older adults with (54%) and without (64%) cognitive impairment, healthcare professionals and systems (54%), and caregivers and social support network members (50%). This balanced distribution of potential consumers and users demonstrates how the a2 Pilot Awards competition accelerates AI and technology that supports the many individuals involved in the care of older adults, leading to improved health outcomes and enhancing independent living. As seen in prior cohorts, the pilots in the fifth cohort are primarily engaged in initial prototype development and testing (46%), followed by technology concept and discovery (25%), evaluation of prototypes in real-world conditions (21%), and commercial deployment or scaling of technology (7%).
Similar to the fourth cohort, the most prevalent post-research settings for the fifth cohort of pilots are at-home or independent living communities (46%), residential living communities or subacute care settings (21%), ambulatory care settings (14%), and hospitals (11%). The high percentage of pilot projects focusing on independent and residential living communities reflects technologists’ responsiveness to older adults’ desire to continue living at home—and the potential of AI-driven tools to help them do so while maintaining active, engaged lifestyles. One pilot led by Marie Brodsky, co-founder and CEO of tech startup WISE Connect, is developing an AI-powered platform that provides older adults with tailored recommendations for local support services and social opportunities to improve quality of life, connectedness, and independence while aging in place.
Aligning with older adults’ desire to age in place, the most prevalent types of technology leveraged by this class of pilots are user-facing software and platforms (43%), wearable devices (36%), and virtual assistants and chatbots (29%). Technology solutions delivered through these modes can provide older adults and their caregivers with improved in-home health monitoring systems for specific age-related conditions, guidance on health decisions and facilitating daily activities, and emotional and mental health support.
“AD/ADRD is one of the most prevalent age-related conditions, and many older adults face challenges with memory that can cause mental distress for both them and their caregivers,” said Rose Li, PhD, MBA, co-director of the a2 Collective Coordinating Center. “Leveraging AI technologies can help promote function and routine in the lives of older adults with memory impairments, enabling them to live more independently and enhancing quality of life for them and their caregivers alike.”
Visit our Awardees page for more information about the a2 Collective’s funded pilots. Both Cohort 4 and Cohort 5 pilots will be highlighted at the fourth annual a2 National Symposium in Washington, D.C., on March 19–20, 2026.
NIA is one of 27 Institutes and Centers of the National Institutes of Health at the U.S. Department of Health and Human Services. The a2 Collective is funded through NIA grants U24AG073094 (a2 Collective Coordinating Center), P30AG073104 (JH AITC), P30AG073105 (PennAITech), and P30AG073107 (MassAITC).
a2 Pilot Awards Cohort 5 Projects
Click the descriptive titles below for additional project details or visit our Awardees page to view all five cohorts of projects funded by the a2 Pilot Awards to date.
Training a foundation model to harmonize neural and immune cellular profiles across AD stages in order to identify biomarkers for early AD/ADRD detection and disease tracking
Awardee organization(s): Allen Institute
PI(s): Mariano I. Gabitto, PhD
Developing an AI-driven public health surveillance tool to identify individuals with a high risk of undiagnosed dementia
Awardee organization(s): Apriqot Inc.
PI(s): Ken Shapiro | Kevin Konty, PhD
Identifying novel targets for AD/ADRD treatment by leveraging machine learning to distinguish senescent cell subtypes
Awardee organization(s): AtlasXomics Inc.
PI(s): Timothy S. McConnell, PhD
Developing an innovative, AI-powered mobile tool to enable at-home hearing screening for older adults with mild cognitive impairment
Awardee organization(s): Auspex Medix LLC
PI(s): Wenyao Xu, PhD
Utilizing AI to identify geroprotective effects in regularly prescribed medications that may slow or reverse aspects of aging
Awardee organization(s): Brigham and Women's Hospital
PI(s): Jesse R. Poganik, PhD
Using a contactless, AI-enabled mmWave radar system to enable longitudinal and accurate monitoring of arterial stiffness and overall cardiovascular health among older adults
Awardee organization(s): Carnegie Mellon University
PI(s): Justin Chan, PhD | Swarun Kumar, PhD
Leveraging wearable device data and AI to assist with early detection and continuous tracking of MCI and AD/ADRD
Awardee organization(s): Connected Future Labs
PI(s): Sean Montgomery, PhD
An AI-driven augmented reality platform that increases mobility and autonomy in Parkinson's patients who experience freezing of gait
Awardee organization(s): DexTech Inc.
PI(s): Nipun Chopra, PhD
Leveraging AI to support older adults in appealing health insurance claim denials
Awardee organization(s): Duke University School of Medicine | CareYaya Health Technologies Inc.
PI(s): Kathyrn Pollak, PhD | Neal Shah
Using a multi-agent generative AI system to support AD/ADRD patients and caregivers in understanding lab results and asking relevant follow-up questions Awardee organization(s): Florida State University
PI(s): Zhe He, PhD
Using AI/ML models to identify mitochondrial genetic and epigenetic markers and to develop a mitochondrial aging clock
Awardee organization(s): Fox Chase Cancer Center
PI(s): Hayan T. Lee, PhD
Developing and validating a multimodal machine learning model for early detection of MCI among older adults
Awardee organization(s): Johns Hopkins University
PI(s): Anis Davoudi, PhD
Machine learning–driven real-world gait analysis integrated in shoes to support healthy aging in older adults
Awardee organization(s): Johns Hopkins University
PI(s): Nitish Thakor, PhD
Integrating a voice-controlled AI assistant to support symptom tracking in a miniaturized in-ear wearable that monitors cerebral blood flow in adults with AD/ADRD
Awardee organization(s): Lumia Health Inc. | Spaulding Rehabilitation Hospital Boston
PI(s): Selina Zhu, ScD | Paolo Bonato, PhD
Utilizing image-based AI technology to monitor AD/ADRD patients' nutrition and provide personalized dietary recommendations to inform care decision-making for staff at adult day centers
Awardee organization(s): New York University Rory Meyers College of Nursing
PI(s): Tina R. Sadarangani, PhD, RN
Leveraging a pre-trained foundational AI model to integrate prior knowledge to identify genetic risk factors for AD/ADRD
Awardee organization(s): Old Dominion University | Admera Health
PI(s): Hong Qin, PhD, MS |Yaping Feng, PhD| Shunian Xiang, PhD
Leveraging an LLM-based facilitation bot to enhance peer-to-peer support among informal caregivers of people with AD/ADRD
Awardee organization(s): Socratic Sciences Inc. | University of Massachusetts Amherst
PI(s): Gregory Stock, PhD, MBA | Hamed Zamani, PhD
Leveraging AI to develop a sleep-promoting device that improves slow-wave sleep in patients with AD
Awardee organization(s): Synaptic Health LLC
PI(s): Brian Krohn, PhD
Identifying barriers to adoption and refining an AI-powered speech recognition system to support individuals with severe dysarthria
Awardee organization(s): The Babel Group
PI(s): Katie Seaver MS, CCC-SLP
Developing and validating machine learning models to detect early-stage neurological and psychiatric disorder biomarkers and improve diagnostic accuracy
Awardee organization(s): University of Denver
PI(s): Reza Mahmoodi, PhD
Leveraging multimodal LLMs to develop an inclusive and accessible tool that aids older adults when making over-the-counter medication choices
Awardee organization(s): University of Maryland
PI(s): Eun Kyoung Choe, PhD
Developing an AI-based conversational agent to support the mental well-being of AD/ADRD informal caregivers
Awardee organization(s): University of Massachusetts Amherst
PI(s): Ravi Karkar, PhD
Using an adaptable perceptual AI system to provide personalized task assistance for AD/ADRD patients and reduce caregiver burden
Awardee organization(s): University of Michigan
PI(s): Joyce Chai, PhD | Anson Kairys, PhD
Developing a machine learning–driven decision support algorithm using passive, wearable sensor data to identify heart failure exacerbations and response to treatment
Awardee organization(s): University of Pennsylvania
PI(s): Pamela Cacchione, PhD, CRNP, RN
Implementing trustworthy generative AI in the development of clinical chatbots to answer AD/ADRD patient questions and reduce genetic counselor time when conducting APOE genetic testing
Awardee organization(s): University of Pennsylvania
PI(s): Angela R. Bradbury, MD
Using NLP and LLMs to scale an evidence-based cognitive behavioral intervention for AD/ADRD family caregivers
Awardee organization(s): Washington University in St. Louis
PI(s): Karla T. Washington, PhD
Developing an AI tool that recommends appropriate local resources to support older adults aging in place
Awardee organization(s): WISE Connect
PI(s): Marie Brodsky
Using an AI-powered humanoid social robot and multimodal sensor technology to provide personalized and context-aware assistance to AD/ADRD patients
Awardee organization(s): Worcester Polytechnic Institute
PI(s): Fiona Yuan, PhD
