Simpler Grants.gov #RFA-DK-27-112

NIH Forecasted Single Source for EDIC Study Research Center Continuation

This opportunity is a forecasted single source procurement by the National Institutes of Health (NIH) to continue support for the EDIC Study Research Center, focusing on long-term research into type 1 diabetes complications. - Government Buyer: - National Institutes of Health (NIH), Division of Diabetes, Endocrinology and Metabolic Diseases - Program Scope: - Continuation of the Epidemiology of Diabetes Interventions and Complications (EDIC) Study Research Center - Long-term follow-up of the EDIC cohort to study development and progression of type 1 diabetes (T1D) complications - Research areas include severe microvascular disease, cardiovascular and liver disease, sleep disorders, mortality, and other comorbidities - Emphasis on age-related morbidities, quality of life, self-management, and caregiver burden - Evaluation of emerging therapies such as SGLT2 inhibitors and GLP-1 receptor agonists - Technical and Research Requirements: - Use of advanced statistical methods, including machine learning and artificial intelligence - Application of modern technologies: continuous glucose monitoring, coronary calcification imaging, vascular tonometry - Support for multi-omic approaches and leveraging external databases for cost-effectiveness and quality-of-life analysis - Funding and Eligibility: - Estimated program funding: $6,300,000 - One expected award - Eligible applicants: public and private institutions of higher education - No specific OEMs, vendors, products, or part numbers are mentioned in the solicitation - Place of performance and contracting office: National Institutes of Health

Description

This funding opportunity announcement (FOA) supports the EDIC Research Center to continue long-term follow-up of the EDIC cohort to study the development and progression of complications in type 1 diabetes. Research will focus on severe microvascular disease, cardiovascular and liver disease, sleep disorders, mortality, and other comorbidities, with emphasis on age-related morbidities and the impact of emerging therapies. Advanced statistical methods and modern technologies will be applied to identify phenotypes and biochemical signatures associated with complications. The program also encourages leveraging external databases to examine cost-effectiveness and quality-of-life impacts of intensive therapy.

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