Description:
BACKGROUND:
The involvement of small businesses in translational aging research could hasten the pace at which scientific advances are transformed into commercial products to improve or maintain the health and functional independence of older adults. Therefore, this funding opportunity announcement (FOA) is intended to support innovative research conducted by small businesses to advance the availability of novel devices, products, health care practices and programs with the potential for commercial success and the likelihood to benefit the lives of older adults.
For the purposes of this FOA, T2 translational research on aging involves the development or evaluation of methods for disseminating (1) results from clinical studies into everyday clinical practice and health decision-making in geriatric medicine (e.g., adapting an efficacious intervention for application in clinical practice and in the community), (2) results from large scale behavioral and community interventions into practice in community organizations, workplaces, and public institutions, and (3) development of new technologies for enhancing research productivity in aging research. Research activities related to T2 translational research could include data-mining for developing new educational materials, or to inform new health care practices in geriatric medicine and community programs for older adults.
Applicants interested in proposing translational research projects related to the development of new strategies for prevention and treatment of age-related pathologies should refer to the companion FOA for T1 research (RFA-AG-12-009). Additional information on NIA funding considerations for RFA-AG-12-009 and RFA-AG-12-010 is available at: http://www.nia.nih.gov/GrantsAndTraining/FundingOpportunities/TranslationalResearch.htm
RESEARCH OBJECTIVES:
Eligible small businesses are invited to submit grant applications (Phase I, Phase II and Fast Track SBIR applications) proposing to develop and deliver technologies or products appropriate to the needs of older adults and to clinicians responsible for their care. Responsive applications will include a description of the specific healthcare requirement or need of the older population being addressed. Applicants should also include a timeline and milestones for projects submitted in response to this FOA. The timeline should delineate a series of project stages, identify criteria for completion of work stages and provide contingency plans for each work stage. It is important that the applicant includes the criteria and contingency plans that will be used to determine milestone completion before proceeding to the next phase of the project.
T2 translational research topics include but are not limited to:
Clinical tools applied to the prevention of falls in older persons.
Clinical tools applied to pain management for older adults affected by chronic pain.
New approaches for the assessment and management of persons with multiple chronic conditions.
Strategies to improve appropriate medication prescribing and/or administration in older adult patients; e.g., minimization of toxicity through appropriate dosing that consider appropriate pharmacokinetic alterations in elderly populations; improvement of strategies to minimize interactions among prescription drugs and /or between prescription drugs and over-the-counter drugs or nutriceuticals.
Utilization of novel technologies to monitor, assist or maintain daily functioning of older individuals with cognitive impairment.
Validation of brief cognitive screening measures for clinical practice.
Development and/or testing of management strategies in clinical practice.
The development of evidence based risk-reduction programs (also referred to as health promotion, health management, demand management, and disease-prevention programs) that are applicable to older U.S. workers.
The development of software to improve financial decision making including projected retirement earnings, Medigap supplemental insurance decisions, expenditures on long-term care, and out-of-pocket medical expenditures. Such software should be capable of being updated as state and federal policies change, retiree health benefits change, or to follow market variation.
The development of practical applications using innovative technologies (e.g., hand-held, internet, telemedicine, GPS, robotics, social networking, and communications technologies) to support and improve quality of life, well-being, and the ability to older adults to live independently and safely at home.
The development of interventions or programs for issues impacting caregivers of the elderly and older individuals needing long-term care such as: (1) strategies for care providers (both professional and families) to deal with burdens associated with chronic disabling illness or disease (including Alzheimer’s disease) using evidence-based findings; and (2) programs or interventions that address/decrease the trauma and difficulty of elders, their families, and care providers faced with end of life decisions and events surrounding end of life.
Develop forecasting models to: (1) improve national, state, and county level estimates of the demand for aging-related services, (2) improve the prediction of the costs and effects of public health interventions, (3) determine changes in health-care financing and insurance, social security, pension coverage, or changes in retirement age.
Develop or test novel devices or methods to identify at-risk older drivers and devices to avoid problems such as “pedal misapplication.”
Develop software or applications for zoning boards and other local officials to use to assess the elder-friendliness of neighborhoods and highlight specific changes needed to enhance safety, livability, and well-being.
Develop online genetic counseling so that users have a way to interface with professionals regarding issues that may have arisen after learning about genetic risk for disease, or about any new ancestry information that might be at odds with their self-identified race.
Develop a more targeted understanding of who will engage in DTC genetic testing and who will not, based on personality and other characteristics. This could be accomplished through comparisons with other large-scale surveys.
