NIH funding

 

1. Bridge to Artificial Intelligence (Bridge2AI) Program

   • Description: This NIH Common Fund program aims to propel biomedical research by generating new data sets and best practices for AI and machine learning analysis. The initiative is designed to address complex biomedical challenges beyond human intuition.
   • More Information: Visit the Bridge2AI program page for detailed information and updates​ (NIH Common Fund)​.

2. Smart Health and Biomedical Research in the Era of Artificial Intelligence (AI) and Advanced Data Science (NSF 23-614)

   • Collaborators: National Science Foundation (NSF) and NIH.
   • Objective: Supports projects that integrate AI and advanced data science to enhance biomedical research, focusing on innovative health solutions.
   • Submission Deadline: November 13, 2024.
   • More Information: Details can be found on the NIAID funding news page​ (NIAID)​.

3. Transformative Artificial Intelligence and Machine Learning Based Strategies (R21/R33 Clinical Trial Not Allowed)

   • Objective: Develop strategies to identify determinants of exceptional health and lifespan using AI and machine learning.
   • Status: No current funding opportunities, but it represents the kind of initiatives NIH has supported in the past.
   • More Information: Visit the NIH Common Fund page for archived initiatives and future updates​ (NIH Common Fund)​.

For updated deadlines, detailed descriptions, and additional opportunities, regularly check the NIH Grants & Funding page.

der to understand human health and disease etiology. This includes multi-omic data acquisition undertaken by ongoing exceptional longevity (EL) studies supported by the National Institute on Aging (NIA) that aim to identify and translate protective molecular factors and biological processes that promote exceptional health and life span. Such NIA-supported studies include the Long Life Family Study (LLFS), Longevity Consortium (LC), and Integrative Longevity Omics (ILO). While these human cohorts, with extensive physiologic, clinical, and pharmacologic data, provide advantages to unravel exceptional aging processes, the limited signal strength caused by modest variance in life span across humans and other stochastic factors, such as environmental exposures, could hinder the detection of protective biological factors that drive EL. In an effort to overcom