SB1AG087924
Project Grant
Overview
Grant Description
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.
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.
Awardee
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Atlanta,
Georgia
303081019
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 207% from $1,246,208 to $3,821,254.
Maphabit was awarded
Enhancing Alzheimer's Assistive Technology Platform with AI Gamification
Project Grant SB1AG087924
worth $3,821,254
from National Institute on Aging in May 2024 with work to be completed primarily in Atlanta Georgia United States.
The grant
has a duration of 3 years and
was awarded through assistance program 93.866 Aging Research.
The Project Grant was awarded through grant opportunity SBIR/STTR Commercialization Readiness Pilot (CRP) Program Technical Assistance and Late Stage Development (SB1, Clinical Trial Not Allowed).
SBIR Details
Research Type
SBIR Phase II
Title
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
Abstract
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.
Topic Code
NIA
Solicitation Number
PAR23-219
Status
(Ongoing)
Last Modified 6/5/26
Period of Performance
5/15/24
Start Date
4/30/27
End Date
Funding Split
$3.8M
Federal Obligation
$0.0
Non-Federal Obligation
$3.8M
Total Obligated
Activity Timeline
Transaction History
Modifications to SB1AG087924
Additional Detail
Award ID FAIN
SB1AG087924
SAI Number
SB1AG087924-4206168175
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Small Business
Awarding Office
75NN00 NIH National Insitute on Aging
Funding Office
75NN00 NIH National Insitute on Aging
Awardee UEI
T87GHUJ1TXG7
Awardee CAGE
861L0
Performance District
GA-05
Senators
Jon Ossoff
Raphael Warnock
Raphael Warnock
Modified: 6/5/26