SBIR-STTR Award

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
Award last edited on: 3/18/2025

Sponsored Program
SBIR
Awarding Agency
NIH : NIA
Total Award Amount
$1,246,209
Award Phase
2
Solicitation Topic Code
866
Principal Investigator
Matthew Golden

Company Information

MapHabit Inc

75 5th Street Nw Suite 2000
Atlanta, GA 30308
   (404) 282-2474
   info@maphabit.com
   www.maphabit.com
Location: Single
Congr. District: 05
County: DeKalb

Phase I

Contract Number: 2024
Start Date: ----    Completed: 5/15/2024
Phase I year
2024
Phase I Amount
$1
Direct to Phase II

Phase II

Contract Number: N/A
Start Date: 4/30/2027    Completed: 5/15/2024
Phase II year
2024
(last award dollars: 1742285620)
Phase II Amount
$1,246,208

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.

Public Health Relevance Statement:
The MapHabit System (MHS), our neuroscience-based, innovative assistive technology and interactive care management platform is focused on people living with Alzheimer's disease and Alzheimer's disease related dementias and helps organize an individual's habits and routines into visual maps i.e., step-by- step pictures/videos to successfully carry out activities of daily living (ADLs) and other activities. This CRP will boost commercialization and marketability of the MHS by implementing the goals of three interconnected Specific Aims (SAs) that will (SA1) strengthen our platform infrastructure and security to enable new predictive analytics components, (SA2) enhance user appeal and user "stickiness" by upgrading our innovative gamification programs and improvements related to the front-end user interface, and (SA3) enhance customer care processes utilizing social determinants of health (SDOH) Z codes. Taken together, these goals provide particularly important developments for successful commercialization because value-based care models to address health equity disparities are increasingly being linked to SDOH, and SDOH codes, and because these goals reflect the nation's public health goal of further reducing the burden of AD/ADRD on individuals, their families and caregivers, and society at large. Terms: