Programs

To tackle the human health challenges that face the world today, the FNIH develops collaborations with top experts from government, industry, academia and the not-for-profit sector and provides a neutral environment where we can work productively toward a common goal.

NINDS Healthcare Disparities in Tribal Communities Summer Internship Program

The NINDS Healthcare Disparities in Tribal Communities (HDTC) Summer Internship Program (SIP) is a student research training program in brain and nervous system research. The program focuses on neurological disorders and healthcare disparities and seeks to provide research experiences and career development opportunities for Native American students, along with students from other underrepresented communities.

Biomarkers Consortium - Inflammatory Markers for Early Detection and Subtyping of Neurodegenerative and Mood Disorders

This project will aim to standardize and validate measurement methods for inflammatory markers associated with Alzheimer’s Disease and/or Major Depressive Disorder to ultimately identify a unique biosignature of disease. The identified biosignature would greatly assist with medication development, patient diagnosing, and patient selection for clinical trials.

Biomarkers Consortium - Carotid MRI Development and Validation via an AIMHIGH Sub-Study

The goal of this project was to conduct a 75-patient study at a total of 15 centers to determine the reproducibility of the non-invasive technique of carotid magnetic resonance imaging (CMRI). Results established a standardized carotid MRI protocol and determined, for the first time, that kinetic parameters of carotid atherosclerotic plaque are reproducible and can be used for multi-center studies.

Biomarkers Consortium - In Silico Modeling of Biomarkers of Atherosclerosis: Estimating Risk Reduction and Residual Risk from Statin Therapy

The Biomarkers Consortium’s In Silico Modeling of Biomarkers of Atherosclerosis: Estimating Risk Reduction and Residual Risk From Statin Therapy’s goal was to identify a time-dependent, dynamically-responsive panel of extant markers that change in response to Phase II intervention and predict Phase III clinical cardiovascular outcomes to build the model. This model would support cardiovascular drug development decision-making and assessment of atherosclerotic risk in the development of drugs for other indications.