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Transforming Alzheimer’s research with real-world data

Picture of Jessica Boten
Jessica BOTEN,
Lead Social Science Analyst,
Division of Behavioral and Social Research (DBSR)
Rebecca Krupenevich
AAAS Science & Technology Policy Fellow ,
Division of Behavioral and Social Research (DBSR)

Editor’s Note: The author is grateful for important contributions to this post from the NIA Real-World Data Planning Committee: Partha Bhattacharyya, Stacy Carrington-Lawrence, Rosaly Correa-de-Araujo, Patricia Jones, Lisa Onken, Nadezda Radoja, Marcel Salive, and Nina Silverberg.

Leveraging the power of real-world data has great potential to advance Alzheimer’s disease and related dementias research in larger, more inclusive, and diverse populations. Today, there is an unprecedented wealth of information available on how people engage with the health care system, their health behaviors, and how the environments in which they live and work affect their health. These real-world data sources include electronic health records, diagnostic test results, medical images, insurance claims, patient-generated data collected in the home, mobile devices and wearables, and many others.

Combining and analyzing real-world data in ways that can’t happen in a research study or clinical trial can help us uncover new insights and patterns that would otherwise remain hidden. Improved access to and use of real-world data can also lower research costs, reduce participant burden, and help researchers rapidly evaluate treatments and interventions across large and more representative groups of people living with dementia and their care partners.

With these goals in mind, we are pleased to announce a Request for Applications to Develop the Real-World Data Platform (RWDP), a new initiative led by NIA in collaboration with the NIH National Institute of Neurological Disorders and Stroke. If this sparks your interest, be sure to register for the informational webinar coming up April 19 at 4 p.m. ET, to learn more.

Leveraging real-world data in aging research

The RWDP will link multiple data sources and research studies to more accurately represent 70% to 90% of the U.S. population, including up to 80% of people living with dementia. The latest in ongoing NIA efforts to identify and link existing datasets, this new initiative and its structure were informed by a related workshop (PDF, 454K) held in spring 2022 and a Request for Information issued last fall.

The RWDP will help a broad range of researchers access and analyze health data in a secure cloud computing environment, and recruit from a more diverse pool of individuals. It will also support collaboration among health care and community health providers to develop and facilitate innovative methods for scalable digital, decentralized, pragmatic, and clinical trials. Another top goal is to prioritize engagement with communities that have been historically marginalized and underrepresented in clinical research and be purposeful in addressing disparities when incorporating secure data sources and studying health outcomes.

Finally, as part of the initiative, the awardees will hold national competitions to fund and facilitate innovative research projects that address gaps and priorities in Alzheimer’s and related dementias research, such as developing patient registries and expanding clinical research networks.

Learn more on April 19 and apply by July 31!

If you are interested in developing the Real-World Data Platform, apply to the notice of funding opportunity by July 31. Be sure to register for the pre-application technical assistance webinar to be held April 19 at 4 p.m. ET., and if you have questions, email


Submitted by Tanvi Bhatt on April 05, 2023

Hello, will this competition only award one application for the development of the RWDP?
Or can there be multiple RWDP’s depending on the data we are interested in? For example falls-risk versus imaging data?
Thanks for any clarification.

Submitted by Jess Boten on April 06, 2023

NIA intends to fund one award for the development of the Real World Data Platform. 

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