Adding technology that will enhance commercialization of our neuroscience-based innovative assistive technology platform for living with Alzheimer's disease and Alzheimer's disease related dementia

Individuals living with Alzheimer’s disease and Alzheimer’s related dementias (AD/ADRD) have the same quality of life needs as individuals without dementia, however, in the setting of progressively diminishing memory and worsening abilities for self-care, individuals living with AD/ADRD experience progressive losses in independent decision-making

capacity and quality of life. The MapHabitTM system (MHS), (NIH/NIA 1st place Eureka Award; 2 SBIR awards; 2 non- provisional patents approved), is a neuroscience-based assistive technology app that leverages the science of visual mapping, together with the neuroscience of habit formation, to help memory-impaired individuals accomplish activities

of daily living, maintain their independence, and improve overall quality of life for users, including caregivers. In this CRP application, MapHabit will further enhance its commercialization and marketing potential by implementing three

Specific Aims (SAs): In SA1, our goal is to strengthen our platform infrastructure and security to enable new predictive

analytics components. In the Phase I/II aims (AG065081) we built out capabilities of gamification, predictive analytics, artificial intelligence, and Alexa Voice. We now seek new technical assistance to enhance our technology stack with

SOC2 certification, optimize the backend infrastructure, and to apply artificial intelligence (AI) methods to mine usage

patterns. As examples, we will build, train, and deploy generative AI models to intervene ahead of a participant churn, (a

decrease in user activity after an initial period of heavy use (as in SA2) and behavioral changes that could signal onset of cognitive change. Effective management of these by AI or machine learning models (MLs) will be a key commercialization metric to engage upstream business partners (payors) and position the platform to address ADRD

population health. In SA2, our goal is to enhance user appeal. Gamification enhancement of the platform began in our Phase II. Games will be accessed by approaches proven to enhance engagement, e.g., cumulating points for using visual maps to complete ADLs and that reflect independent functioning (e.g., attending meals with others). New AI/ML models

will gamify the experience and upgrade our serious games with reward systems. We will tailor ML models from SA1 with an emphasis on applicability to sociodemographically diverse communities, including data from social determinants of health in SA3. These will be packaged into programs that can be upsold to B2B clients. We will consult with experts at

the Mayo Clinic to advise on strategic initiatives for virtual care consultations and for hard-to-treat domains, like Lewy Body Dementia. In SA3, the goal will be to enhance customer care processes utilizing social determinants of health (SDOH) Z codes. We will use technical assistance to apply standards endorsed by the CDC National Center for Health

Statistics to update our intake process to include variables of SDOH, engaging JGS Consulting for value-based care market strategy and coding expertise. This is an important prerequisite for successful commercialization as value-based care models to address health equity disparities are linked to SDOH, and SDOH codes. As described in several examples

in the sections above, and throughout the CRP, the three SAs are highly interconnected, and the developments in each SA connect and contribute meaningfully to the overall success of the marketability and commercialization of the MHS.