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Upcoming Webinar (Oct 27 @4p ET) – Separating Geroprotection from Disease Modification to Repurpose Approved Drugs for Human Aging

Registration: https://tinyurl.com/MassAITC-Oct2026-webinar Abstract: Identifying drugs that slow biological aging in humans is a central goal of geroscience, but a key confounder in observational studies is that drugs prescribed for serious conditions may lower biological age scores indirectly by reducing disease burden rather than by exerting a direct geroprotective effect. To address this, we developed an analytical framework that incorporates indication-specific covariates, isolating drug-associated changes in biological age that are independent of disease modification. Applying this approach across large data resources, we systematically evaluate approved medications for geroprotective activity, and further interrogate top candidates using high-dimensional plasma proteomics and metabolomics to gain mechanistic insight into how these drugs alter aging trajectories. This framework provides a scalable strategy for identifying approved, commonly prescribed drugs with geroprotective properties, with broad implications for translating aging biology into actionable clinical…

Continue ReadingUpcoming Webinar (Oct 27 @4p ET) – Separating Geroprotection from Disease Modification to Repurpose Approved Drugs for Human Aging

Upcoming Webinar (Sep 22 @4p ET) – Understanding and Assisting Older Adults with AI: From Emotional States and Functional Capacity to Assistive Technologies

Registration: https://events.zoom.us/ev/AlHlWkhvdvhqx4q5OnjGTSaxHn_an48ZtKwUfSuuVmm_El6aC6LF~AuVtmoJ1Eufnk09HBV0piBoliVpb3u7qriA2tyEOV-2gQctk85QcKLm5jA Abstract: Older adults' needs and abilities are multidimensional and continuously changing, yet much of today’s AI focuses on detecting isolated events or predicting individual outcomes. Our work explores how AI can develop a richer understanding of older adults by integrating behavioral, emotional, functional, clinical, and environmental information. We investigate how subtle changes in emotional state can be inferred from multimodal behavior, how routinely collected clinical data can reveal meaningful patterns of intrinsic capacity, and how AI and robotics can translate this understanding into practical assistance. Across these efforts, we are also developing the data integration and validation infrastructure needed to make AI systems reliable, generalizable, and useful in real-world aging settings. Ultimately, our goal is to move from AI that simply observes older adults to AI that understands their changing needs and abilities…

Continue ReadingUpcoming Webinar (Sep 22 @4p ET) – Understanding and Assisting Older Adults with AI: From Emotional States and Functional Capacity to Assistive Technologies

Past Webinar – Best Practices for Digital Phenotyping Research in Aging Populations

https://www.youtube.com/watch?v=nxRdD0OHu1c Abstract: Digital phenotyping is transforming aging research by enabling high-frequency, real-world measurement of cognition, behavior, symptoms, and context through smartphones, wearables, and passive sensing technologies. This talk will review how digital health tools can complement traditional clinic-based assessments by capturing intraindividual variability, diurnal patterns, environmental influences, and subtle changes in cognitive and functional performance that may signal risk for neurodegenerative disease. Using examples from studies of healthy aging, MCI, Alzheimer’s disease risk, dementia caregiving, and related clinical populations, the talk will highlight best practices for designing digital phenotyping protocols, balancing participant burden with data richness, maximizing adherence, integrating active cognitive assessments with passive data streams and biomarkers, and applying analytic approaches that distinguish within-person change from between-person differences. The session will emphasize opportunities for digital phenotyping to improve early detection, clinical trial endpoints, remote…

Continue ReadingPast Webinar – Best Practices for Digital Phenotyping Research in Aging Populations

Past Webinar – TRIALCHAT: Developing Agentic AI Chatbot Tools with Older Adults and Caregivers to Encourage Participation in ADRD Clinical Trials

https://www.youtube.com/watch?v=L70oKKvsgrA Abstract: Hype around the potential of generative AI tools to transform healthcare is at an all time high, but their design and utility is often not user or patient-centered. This is particularly true for generalized large language models that have limited UI/UX features, may hallucinate or give incorrect medical/healthcare advice, or may lack conversational clarity and specificity. In fact, these tools are rarely designed in partnership with the end-user or patients they intend to serve. As part of a2 Collective Pilot award in partnership with MassAITC, S-3 Research and California State Fullerton have been developing “TRIALCHAT", a multiagentic AI tool with the goal of navigating older adults and their caregivers to resources related to Alzheimer’s Disease and clinical research participation opportunities. Lessons learned from a technology design and development process that involved rapid prototyping,…

Continue ReadingPast Webinar – TRIALCHAT: Developing Agentic AI Chatbot Tools with Older Adults and Caregivers to Encourage Participation in ADRD Clinical Trials

Past Webinar – From AI Validation to Evidence: Proving Readiness for Real-World Aging Care Systems

https://www.youtube.com/watch?v=IIxuaUpqhIM Abstract: Artificial intelligence is increasingly being deployed to support aging populations through applications such as remote monitoring, fall detection, cognitive assessment, and caregiver support. While many AI systems demonstrate strong performance in pilot studies, only a small fraction successfully translate into safe, reliable, and scalable real-world deployments. A key challenge lies in the gap between validation and real-world evidence. Traditional evaluation approaches emphasize model performance, but aging care environments introduce additional complexities—including multimorbidity, heterogeneous living conditions, and safety-critical decision contexts—that are often not adequately captured during pilot validation. This webinar presents a structured approach to moving from AI validation to evidence-driven deployment readiness for aging care systems. The session will explore lifecycle-based evaluation methods spanning data, model development, pilot testing, real-world deployment, and continuous monitoring. It will highlight approaches for assessing fairness across aging…

Continue ReadingPast Webinar – From AI Validation to Evidence: Proving Readiness for Real-World Aging Care Systems

Past Webinar – Old School Meets New School: Voice-Based, AI-Enabled Cognitive Rehabilitation for Dementia Care

https://youtu.be/tY05wZMGYg8 Abstract: Cognitive rehabilitation therapy supports individuals living with mild cognitive impairment and early-stage dementia in maintaining and improving function in daily life. However, access remains limited due to constraints in the availability and scalability of trained therapists. Recent advances in artificial intelligence, combined with evolving reimbursement pathways for remote care in the United States, now make virtual delivery models increasingly viable, creating new opportunities to expand access to high-quality cognitive care. Moneta Health has developed a telephone-based cognitive rehabilitation platform that enables structured, personalized therapy sessions delivered remotely and overseen by licensed speech-language pathologists. The platform leverages AI-driven speech analysis and automated session orchestration to support consistent therapy delivery while preserving clinician oversight, enabling older adults to engage in care from their homes through a familiar and intuitive interface. This approach is designed to…

Continue ReadingPast Webinar – Old School Meets New School: Voice-Based, AI-Enabled Cognitive Rehabilitation for Dementia Care

Past Webinar – How to Develop and Test Mechanism-Driven, Technology-Enabled Interventions in Response to the Scientific Foci of ASU Roybal Center for Older Living Alone with Cognitive Decline

http://youtube.com/watch?v=6n6meYGI_Ug Abstract: Purpose: 1) Explain the scientific foci of ASU Roybal Center for Older Adults Living Alone with Cognitive Decline to delay the onset and progression of Alzheimer’s disease and related dementia (AD/ADRD), and 2) Guide investigators to develop strong research proposals, focusing on the significance of a proposed solution, mechanism-driven and technology-enabled interventions, and health disparity factors.  Rationale: Poor lifestyle behaviors such as physical inactivity, unhealthy diet, and stress contribute to up to 40-50% of AD/ADRD cases; however, few intervention successes have been translated into real-world impacts. Most interventions are not mechanism-driven, precise, accessible, cost-effective, and/or scalable, which could potentially be addressed by technology through integrating Artificial Intelligence, real-time analytics and feedback, enhancing user autonomy and person-centeredness, and personalizing intervention prescription and delivery. In addition, the population of older adults living alone with cognitive…

Continue ReadingPast Webinar – How to Develop and Test Mechanism-Driven, Technology-Enabled Interventions in Response to the Scientific Foci of ASU Roybal Center for Older Living Alone with Cognitive Decline