Philadelphia, PA, July 27, 2024—Today, the a2 Collective announced during the Technology and Dementia preconference to the Alzheimer’s Association International Conference the funding of 30 new pilots using advances in artificial intelligence (AI) and related technologies to enhance care, health outcomes, and quality of life for older adults, including individuals with Alzheimer’s disease and related dementias (AD/ADRD), and their caregivers.
These projects comprise the third annual cohort funded through the a2 Pilot Awards, a national competition that is on track to distribute more than $40 million over 5 years to 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 30 projects funded in Cohort 3 extend the a2 Collective’s investment in patient-centered applications of emerging AI and technology to enable older adults to age in place with greater independence, safety, and well-being. Key contributions include arming clinical teams with powerful new tools to characterize, predict, and monitor disease trajectories and individual needs with greater precision; upskilling caregivers through AI-guided training and support; and empowering older adults with assistive technologies that support activities of daily living across home, social, and virtual environments.
Of the technologies under development, 70% involve user-facing software or platforms. One-fifth of the Cohort 3 pilots leverage virtual assistants or chatbots to help with functions such as engaging in daily personal tasks, monitoring cognitive decline, protecting against phishing attacks, and improving oral health.
More than one-third of the pilots utilize wearable technologies (37%) and nearly half involve either smartphone hardware enhancements (23%), environmental sensors (17%), or smart home utilities (7%). By setting, most pilot technologies are designed for the home or independent living communities (67%), with a substantial number (40%) built for use in residential living or subacute care facilities.
“As public health leaders emphasize healthspan over lifespan and care further transitions from the hospital to the home, practical innovations that enhance day-to-day function are increasingly critical to supporting safe and healthy aging,” said Albert Lee, PhD, co-director of the a2 Collective Coordinating Center. “We’re excited to continue expanding the a2 Collective’s support of novel approaches in this space.”
The vast majority of Cohort 3 pilots incorporate machine learning (83%) to power sophisticated applications across varied users, settings, and technologies, a trend consistent with prior a2 Pilot Awards cohorts. This year’s class also demonstrates key shifts in area of need addressed and types of technology utilized. For example, the proportion of pilots focused on treatment and management of care declined compared to previous cohorts, while the proportion of pilots focused on social and emotional well-being increased (see Figure 1).
![](https://cdn.prod.website-files.com/6180228fb0ed916755543003/66a44afd805fa9e77eea7a7a_66a44ad544cba766a2723a94_FY2022-24%2520a2%2520Pilot%2520Awards%2520by%2520Areas%2520of%2520Need%2520Addressed.png)
This cohort also includes fewer projects focused on household devices and utilities, but more leveraging smartphone hardware enhancements, as well as virtual assistants and chatbots. These trends not only represent enhanced cumulative balance of funded areas across a2 Pilot Awards competitions, but also reflect the fast pace of change in the field as increasingly powerful applications of generative AI and large language models (LLMs) in healthcare emerge.
Several unique developments arose among this cohort. Awardee organizations in this year’s class represent 16 different U.S. states and territories, including first-time pilot awardee locations of Hawaii, Missouri, Puerto Rico, Tennessee, and Utah. The proportion of pilots led by nonacademic institutions (53%) compared to academic ones (47%) remains balanced, underscoring the flexibility of the a2 Collective’s funding model to meet the needs of university investigators, healthcare institutions, founder-stage companies, and established startups alike.
Another noteworthy trend is the funding of novel pilots proposed by prior awardees, particularly in the context of technology transfer and cross-sector collaboration. A Cohort 3 project led by Edward Wang, PhD, focuses on a downloadable oscillometric blood pressure monitor and directly builds on work accomplished through Wang’s Cohort 1 a2 Pilot Awards project and the startup, Billion Labs, that he has since launched.
Another project represents a collaboration that includes Cohort 1 awardee Ipsit Vahia, MD, and Cohort 2 awardee Joseph Chung, MS. Chung’s Cohort 2 project focused on the integration of sentiment analysis and generative AI into a dementia caregiver support platform developed by healthcare startup Kinto, which recently announced its acquisition by dementia-focused specialty care provider Rippl. The Cohort 3 project, led by Dr. Vahia, Chung, and Rachel Sava, PhD, will leverage an LLM developed by Kinto to create a safe and ethical framework for use of LLMs in dementia caregiver support.
These encouraging developments suggest that in its third year the a2 Pilot Awards competition offers not only discrete resources to accelerate development, but opportunities for longer-term collaboration in a multidisciplinary innovation community.
“A core mission of the a2 Collective is to not only accelerate cutting-edge technologies toward applications in aging and AD/ADRD through pilot funding, but to foster collaborations that will continue to fuel innovation beyond funded project periods,” said Rose Li, PhD, MBA, co-director of the a2 Collective Coordinating Center. “We hope that this synergy will ultimately compound the program’s impact on emerging enterprises at the intersection of AI and aging.”
The fourth annual a2 Pilot Awards competition is underway with finalists to be selected in fall 2024. The fifth annual competition will accept Round 1 applications from Dec. 2, 2024, to Jan. 15, 2025 (5 p.m. ET).
Visit our Awardees page for more information about the a2 Collective’s funded pilots. Cohort 3 pilots will be highlighted at the 2025 a2 National Symposium, which will be hosted by MassAITC in Boston, MA, on April 3-4, 2025.
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 3 Projects
Click the descriptive titles below for additional project details or visit our Awardees page to view all three cohorts of projects funded by the a2 Pilot Awards to date.
AI- and proximity-based speech enhancement and novel hardware to aid older adults in noisy social settings
Awardee organization(s): AudioFocus
PI(s): Shariq Mobin, PhD | Joe Hu, PhD, AuD
AI-based home cognitive assessment to monitor AD/ADRD-related cognitive changes in older adults
Awardee organization(s): Beth Israel Deaconess Medical Center
PI(s): Daniel Press, MD
Utilizing mobile behavioral data with machine learning to monitor, diagnose, and track AD/ADRD progression
Awardee organization(s): Beth Israel Deaconess Medical Center
PI(s): Chun Lim, MD, PhD
Downloadable blood pressure monitoring smartphone app requiring no external devices for hypertension screening using edge computing and software sensing
Awardee organization(s): Billion Labs Inc.
PI(s): Edward Jay Wang, PhD
Smartphone-based fall prevention therapy using computer vision for older adults in the home
Awardee organization(s): Brightway Health | Beth Israel Deaconess Medical Center
PI(s): Yannick Cohen, MS | Dennis Anderson, PhD
AI-enabled personalized training for caregivers of older adults with AD/ADRD
Awardee organization(s): CareYaya Health Technologies Inc.
PI(s): Neal Shah
AI digital twins using multimodal data to predict AD/ADRD and MCI in older adults
Awardee organization(s): DreamFace Technologies LLC
PI(s): Mohammad H. Mahoor, PhD
Detecting cognitive impairment using LLMs from speech
Awardee organization(s): Drexel University
PI(s): Hualou Liang, PhD
AI-powered video app using deep learning to assess motor functions in Parkinson's patients at home
Awardee organization(s): ForesightCares Inc.
PI(s): Hamed Tabkhi, PhD
Using AI/ML and continuous gait data from environmental sensors to analyze mobility changes associated with AD/ADRD in older adults
Awardee organization(s): Foresite Healthcare
PI(s): Nicholas Kalaitzandonakes, PhD
NLP-driven smart automation for patient portal messages for dementia care partners
Awardee organization(s): Johns Hopkins University
PI(s): Kelly Gleason, PhD, RN
AI-developed multimodal digital biomarkers using portable integrated equipment to characterize individuals with AD/ADRD
Awardee organization(s): Johns Hopkins University
PI(s): Laureano Moro-Velazquez, PhD
Using cognitive and speech AI to characterize and stratify cognitive impairment in older adults
Awardee organization(s): McLean Hospital
PI(s): Shifali Singh, PhD
Creating a framework for LLMs to enhance caregiver support in dementia
Awardee organization(s): McLean Hospital | Rippl
PI(s): Ipsit Vahia, MD | Rachel Sava, PhD | Joseph Chung, MS
AI-powered digital therapy assistant to monitor and treat cognitive impairment in older adults over the phone
Awardee organization(s): Moneta Health
PI(s): Jennifer Flexman, PhD, MBA | Michael Busa, PhD
AI models of physiological signals to mitigate health risks in older adults receiving healthcare at home
Awardee organization(s): Mountain Biometrics
PI(s): Matthias Christenson, PhD
Machine learning-enhanced therapeutic music platform for rural-residing older adults at risk for AD/ADRD
Awardee organization(s): Musical Health Technologies
PI(s): Jennifer Rae Myers, PhD | Chelsea S. Brown, MT-BC
Machine learning-powered wearables for adaptive electrical vestibular stimulation balance therapy for older adults at home
Awardee organization(s): Neursantys Inc.
PI(s): John Ralston, PhD, MBA | VP Nguyen, PhD
Smartphone app using heuristic AI to help caregivers prioritize and manage neuropsychiatric symptoms of AD/ADRD
Awardee organization(s): New York University Rory Meyers College of Nursing
PI(s): Ab Brody, PhD, RN
Multimodal conversational AI to assist older adults with daily tasks at home
Awardee organization(s): Pennsylvania State University
PI(s): Rui Zhang, PhD | Marie Boltz, PhD, GNP-BC
AI-enhanced wearable for continuous blood pressure monitoring to improve cardiovascular health in older adults
Awardee organization(s): PyrAmes Inc.
PI(s): Xina Quan, PhD
AI-based cloud care platform to improve AD/ADRD outcomes for caregiver-patient dyads
Awardee organization(s): REOFTech
PI(s): G. Antonio Sosa-Pascual, MBA, MPP | Michael Busa, PhD
Objective assessment app utilizing computer vision to evaluate cognitive and motor functioning in older adults at risk for AD/ADRD
Awardee organization(s): Stanford University
PI(s): Ehsan Adeli, PhD
AI-powered web app using computer vision to analyze knee joint space in older adults using only plain radiographs
Awardee organization(s): University of Georgia
PI(s): Soheyla Amirian, PhD
AI-enabled voice agents using machine learning to prevent phishing attacks for older adults at home
Awardee organization(s): University of Illinois Urbana-Champaign | OSF HealthCare
PI(s): Gang Wang, PhD | Roopa Foulger | Jonathan A. Handler, MD
Interpretable transformer for AI-based sensing and assessment of chronic pain in long-term care residents with AD/ADRD
Awardee organization(s): University of Massachusetts Amherst
PI(s): Xian Du, PhD | Joohyun Chung, PhD, MStat, RN | Shishir Prasad, PhD
AI-powered digital dyadic coach using reinforcement learning to promote oral health in older adults
Awardee organization(s): University of Michigan | UCLA | Harvard University
PI(s): Inbal Billie Nahum-Shani, PhD | Vivek Shetty, DDS | Guy Shani, PhD, MBA | Susan A. Murphy, PhD
AI-powered point-of-care system for motor function assessment to determine MCI, frailty, and fall risk
Awardee organization(s): University of Missouri
PI(s): Trent M. Guess, PhD
AI-enhanced virtual reality music intervention for AD/ADRD care
Awardee organization(s): University of Tennessee, Knoxville
PI(s): Xiaopeng Zhao, PhD
AI-enhanced scheduling for a neighborhood model of affordable quality home care
Awardee organization(s): Vivia Cares Inc.
PI(s): Dew-Anne Langcaon | Kimia Ghobadi, PhD
The a2 Collective thanks Naveen Rao, MHS, Patchwise Labs, for contributions to this piece.