The Office of Data Science Strategy (ODSS) leads the NIH Strategic Plan for Data Science through scientific, technical, and operational collaboration with the institutes, centers, and offices that comprise NIH.

The rapid increase in the volume of data generated through electronic health records (EHRs) and other biomedical research presents exciting opportunities for developing data science approaches, such as artificial intelligence (AI) and machine learning (ML) methods, to enhance biomedical research and improve health for all Americans. However, several challenges hinder the widespread adoption of AI/ML technologies, including high costs, limited capability for broad application, and inadequate access to necessary infrastructure, resources, and training. Additionally, there is a lack of comprehensive and high-quality AI-ready data, as well as a shortage of a pipeline of talented researchers in both industry and academia to harness the full potential of AI/ML to advance biomedical research and medical practice. Furthermore, tackling the complex drivers of health outcomes requires an innovative and transdisciplinary framework that transcends scientific and organizational silos. Mutually beneficial and trusted partnerships can be established to enhance the adoption of these tools and empower researchers and communities across the United States in AI/ML application and innovation.

Recognizing these challenges and in support of the NIH's data science strategic plans to advance AI initiatives that bridge the gap between AI, clinical, and biomedical research, the NIH launched AIM-AHEAD in July 2021. The AIM-AHEAD program is a large, coordinated network of institutions and organizations with the mission to build AI talented researchers and clinicians across the US, to support multidisciplinary research projects that harness AI/ML to improve the health of Americans and enhance the AI capabilities and infrastructure of limited-resourced communities or hospitals that otherwise would not have had the resources or the capacity to benefit from the advance of AI/ML.

AIM-AHEAD has three major goals.

1. To broaden the participation of researchers and communities across the US in the development and deployment of AI
2. To address health challenges in behavioral/mental, cardiometabolic, and cancer outcomes using AI/ML
3. To improve the capabilities of this emerging technology in communities and institutions across the US

To advance the goals, the AIM-AHEAD Coordinating Center (A-CC) was established to develop and support a consortium of institutions and organizations to build capacity and capability in AI/ML through infrastructure, training, and access to large scale, high-quality, comprehensive data from all Americans (e.g., EHR, genomics, imaging, lifestyle and other non-traditional data). The ACC is led by the University of North Texas Health Science Center in Fort Worth, coordinating with seven regional hubs and three functional cores spanning the entire country. Since July 2021, the A-CC leadership has worked with local communities and stakeholders to identify high-priority areas, known as the AIM-AHEAD North Stars. The A-CC supported research and development awards, training, infrastructure, and public-private awards in these priority areas. In addition, the program developed joint traineeships with NIH-supported programs to democratize data access and build AI talent by leveraging NIH data resources such as All of Us, Bridge2AI datasets, infrastructure, and training components. All funding announcements and review criteria are approved in compliance with all laws and HHS and NIH policies. The program does not use race, ethnicity, or sex as eligibility or selection criteria, nor does it consider these factors when making funding decisions. 

Since its inception in 2021, the program has significantly accomplished the following: 

• Developed a nationwide network, fostering connections and collaborations among researchers, healthcare providers, community organizations, and private sectors, effectively reaching communities and institutions not typically funded by traditional granting mechanisms.
• Generated a wealth of mentorship opportunities and created an ecosystem of professional development through a virtual hub platform called AIM-AHEAD Connect that offers networking, connections, online courses, webinars, and symposiums.
• Developed AI/ML training curricula and trained 380 researchers and clinicians across the US with the skills and knowledge to leverage AI/ML in health research.
• Supported multidisciplinary research projects and facilitated collaboration to harness AI/ML to improve behavioral/mental health, cardiometabolic health, and cancer outcomes for all, which resulted in numerous peer-reviewed publications, and many investigators secured grants from NIH, NSF, NAIRR, and non-federal agencies.
• Built capacity in an AI health lab, federated network, and AI navigation tools in traditionally untapped institutions and healthcare providers, ultimately empowering these institutions to secure further funding and enhance their research capabilities in AI/ML.

On April 5, 2024, the NIH Council of Councils charged an AIM-AHEAD Working Group to assess the AIM-AHEAD’s progress to date and to provide recommendations for the future of this initiative. NIH expects to use these recommendations to guide the future focus of the initiative. Specifically, the charge for the Working Group will be to:

• Review the current scope and goals of AIM-AHEAD as well as progress to date.
• Based on the progress, provide recommendations to enhance the future of the AIM-AHEAD program objectives and goals, with renewed emphasis on addressing chronic diseases through partnerships with a wide range of stakeholders (private sectors, healthcare, and community organizations).  
• Provide recommendations on potential future success measures for the AIM-AHEAD program.