Request for Pilot Proposals – Fall 2022

1. Program Overview 

The Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease (MassAITC) is a multidisciplinary National Institute of Aging (NIA) P30 Research Collaboratory (1P30AG073107) spanning five sites – the University of Massachusetts Amherst, Brigham and Women’s Hospital, Massachusetts General Hospital, Brandeis University and Northeastern University. The Center aims to foster multidisciplinary research on the development, validation and translation of emerging AI and digital technologies to support healthy aging and the care of patients with Alzheimer’s Disease and Alzheimer’s Disease Related Dementias (AD/ADRD) more effectively in their home environments.  

MassAITC is pleased to issue a call for proposals to support pilot studies on mobile, wearable, and contactless sensors, emerging machine learning approaches, and AI and data-driven visualization technologies that have the potential to improve the health of older adults and individuals with AD/ADRD. MassAITC has a particular focus on supporting successful aging at home through the development of technologies for at-home monitoring and support and to better connect older adults, caregivers, and clinicians. 

2. Funding Opportunity Description 

For key dates, FAQs, and to register for or view an informational webinar, please visit https://www.a2collective.ai/pilotawards

For the upcoming year, the MassAITC will fund up to 15 pilot projects. Projects will typically be funded for a 12-month period with a maximum budget of $100,000 in direct costs, but higher levels of funding (i.e., up to $200,000 in direct costs) will also be considered with appropriate justification.

Applicants who do not have access to facilities and resources needed to carry out the proposed research can request access to the Center’s state-of-art research facilities and diverse cohorts provided by the MassAITC partner institutions (see https://massaitc.org/resources/).

We encourage prospective applicants to reach out to us for feedback about their pilot proposal, assistance in assembling an appropriate investigative team, or use of the Center’s facilities and resources. Please provide your information via: https://airtable.com/shr1Yn7ch0obtHkr8

3. Pilot Research Focus Areas 

Most older Americans want to age at home, yet chronic physical and cognitive conditions or environmental barriers pose challenges for them to do so. Successful aging at home will require effective ways for older adults to utilize and access health care services from their homes, but barriers currently exist including a lack of technologies that have been specifically developed for older adults, cognitively-impaired older adults, caregivers, and their clinicians. Furthermore, there is a lack of decision support tools that consider the unique needs of monitoring older adults in their homes while helping them maintain functional independence.  In addition, successful aging at home, particularly for those with cognitive limitations and those living alone, will require better monitoring and support to ensure safety.

We solicit pilot projects that focus on bridging these gaps by improving accuracy, decreasing algorithmic bias, enhancing usability, decreasing burden, and improving accessibility of AI and digital technologies. MassAITC anticipates that addressing these challenges will require cross-cutting technology solutions proposed by interdisciplinary teams. Pilot projects that involve collaborations with industry are strongly encouraged. Topics of interest include but are not limited to­­­: 

  • Development and validation of AI-enhanced data analytic solutions to distill multi-modal sensor and cognitive performance data into interpretable and actionable information to enhance self-care, support caregivers, and/or improve clinical and caregiving decision making. To enable effective and timely decision making about care, we need to develop data analytics tools that distill actionable knowledge from longitudinal and multi-modal data. Critically, these tools will need to provide explanations and visualizations that can be understood by all stakeholders. For example, a pilot may develop explainable AI algorithms and visualization tools that distill voluminous longitudinal health data to accurately infer medication adherence, side effects, and health status to improve clinical decisions.
  • Develop AI-enhanced devices with lower burden, less algorithmic bias, improved accuracy and enhanced usability for both patients and caregivers. AI and machine learning models may be trained on data that do not adequately represent older adults leading to poor predictive performance and adverse consequences for older adults, caregivers and clinicians who base decisions on the resulting inferences. Pilots in this area will address these issues in the context of a specific health problem, for example, a pilot may address gaps in the performance of wearable monitors for sleep, steps, activity, and gait for older adults with mobility impairments by tailoring methods and models specifically for such individuals.
  • Development and validation of data-driven visualization technologies and systems that distill large volumes of data for patients, caregivers and/or clinicians. There are significant opportunities to develop new clinician-driven, AI-enhanced interventions that leverage health monitoring data to optimize various facets of current treatments such as improving efficacy, reducing the occurrence of side effects, and assessing outcomes. For example, a pilot may develop technologies that help clinicians to understand a patient’s full medication use and side effects as well as other health determinants to reduce unsafe use of multiple medications and develop more effective medication regimens.
  • Development and validation of AI-enhanced technologies that account for social determinants of health relevant to older adults and caregivers. Loneliness, anxiety and depression are common debilitating conditions associated with aging and caregiving.  Technology solutions for interventions in the home could provide continuity of care and address issues not routinely covered in traditional clinic visits.

All pilot applications must describe why the problem that they are addressing is a critical barrier to achieving successful aging and/or AD/ADRD care at home, and how the proposed AI methods and digital technologies are well-suited to address the problem.

4. Eligibility 

4.1 Institution 

  • Eligible institutions include for-profit corporations within the United States including startups and established companies, as well as colleges, universities, medical or nursing schools, health care systems or settings, and other fiscally responsible organizations. No research may be performed outside of the United States.  

4.2 Principal Investigator 

  • Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research is invited to work with their organization to develop an application. 
  • Applicants must hold an appropriate position at an eligible organization by the start date of the award or be otherwise eligible to serve as a Principal Investigator as determined by their organization. 
  • Applicants from under-represented racial and ethnic groups as well as individuals with disabilities are strongly encouraged to apply. 

5. How to Apply 

Interested applicants should submit a Letter of Intent at https://www.a2collective.ai/pilotawards by August 15th, 2022.

LOIs will be reviewed and applicants who have submitted highly rated proposals will be invited to submit a full application, including specific aims, a 2–3-page research strategy, a detailed budget and justification, and biographical sketches for all key personnel. Applicants may be invited for a presentation and Q&A if reviewers have additional questions. Final selections will be made thereafter. 

Proposals that have been selected for funding will be required to submit additional documentation to NIH including a project management plan, human subjects protections information and recruitment criteria, and other information.

6. Pilot Selection Criteria 

The review process will consider the following criteria and weigh them as appropriate for each application to assign an overall score. Note that an application does not need to be strong in all categories to be judged likely to have significant impact and be a strong fit for this pilot program. 

6.1 Scientific Merit  

  • Does the project have the potential to make a significant impact on the lives of older adults and/or AD/ADRD patients and their caregivers?
  • Does the project explore development, validation, or translation of innovative AI and/or digital technologies and propose forward-looking solutions? 
  • Are the proposed analytic methods, technological approaches and/or study design technically feasible and deployed appropriately? 
  • Are health equity considerations integrated into the design elements of research plan? 
  • Can the study be feasibly completed within the proposed timeline? 

6.2 Strengths of the Investigators  

  • Do the investigator(s) have a track record of innovative and high-impact research? 
  • Does the team’s prior work and expertise support the likelihood that they can accomplish the proposed project? 
  • Does the team include both technology and clinically oriented collaborators? 

6.3 Impact and Translation 

  • If successful, does the pilot project have the potential to lead to high-impact publications, future grants and/or translation opportunities? 
  • Does the project strengthen a connection with industry, foster a new start-up venture, or enable a Small Business Innovation Research (SBIR) grant submission? 

6.4 Human Subjects  

  • Investigators will need to present a clear plan for how human subjects and data privacy risks will be managed. 

6.5 Resources Sharing  

  • Will the project produce datasets that are properly anonymized and curated with high quality ground truth that can be used by future MassAITC researchers or the research community at large? 

7. Pilot Grant Recipient Expectations 

The pilot project PI will meet with an assigned mentor from the MassAITC at quarterly intervals during the lifecycle of the pilot project. The assigned mentor will be available to help strategize, identify resources that are available, assist with navigating pitfalls, etc. Pilot investigators will be required to engage with the MassAITC by:  

  • Participating and offering new content in their area of expertise to enhance the training activities of the Center (e.g., tutorial on relevant topic, developing a “best practices” document). 
  • Attending and presenting at the in-person MassAITC Annual Meeting
  • Presenting webinars in the Center’s seminar series. 
  • Exploring methods for sharing datasets, software and hardware platforms, and other artifacts across center investigators to enhance future pilot studies.