Recardo: using real-world data to derive common data elements for alzheimer's disease and ad-related dementias research through ontological innovation

The National Institute on Aging awarded a Cooperative Agreement totaling $9.8 million to the University of Texas Health Science Center at Houston on September 15, 2025, under the Aging Research program (CFDA 93.866) to develop common data elements and artificial intelligence tools for Alzheimer's disease and related dementias research leveraging real-world data across a ten-institution collaborative network.

The project, titled "ReCARDO: Using Real-World Data to Derive Common Data Elements for Alzheimer's Disease and AD-Related Dementias Research Through Ontological Innovation," creates metadata standards and a collaborative data ecosystem to transform NIA-funded studies through generation of real-world evidence. The work is organized across seven research workstreams: common data element development and knowledge graph construction; data element extraction from real-world data; data, metadata, and resource ecosystems; artificial intelligence, machine learning, and natural language processing for computational phenotyping; research questions, use cases, and pilot study programs; genetics, imaging, biomarkers, and big data analysis; and reproducibility and evaluation. Administrative support includes steering committee and external advisory panel functions. Place of performance is Houston, Texas, with a performance period through August 31, 2030.

UT Health administers the award through its Sponsored Projects Administration Division as the prime recipient. Sub-recipients contributing to ReCARDO include Indiana University Indianapolis (awarded April 1, 2026), the University of Alabama at Birmingham (February 23, 2026), Rush University Medical Center (February 20, 2026), the University of Texas at San Antonio (December 16, 2025), the University of Florida (December 16, 2025), the University of Pennsylvania (December 11, 2025), Vanderbilt University Medical Center (December 10, 2025), the University of Washington (December 6, 2025), and Mayo Clinic (November 10, 2025). The assistance type is a Cooperative Agreement.

Abstract

Common data elements (cdes) are metadata standards serving as a foundation for semantic interoperability, a prerequisite for leveraging disparate real-world data (RWD) sources for secondary analysis. Existing efforts in ad-related metadata development include the national alzheimer's coordinating center's (nacc) uniform data set and ninds cdes. These are parts of an important metadata collection for ad/adrd research, but existing cdes are not designed, developed, and sufficiently validated to transform NIA-funded studies through the generation of real-world evidence (RWE) from RWD with data linkage and longitudinal analyses. In this U24 project, "recardo: using real-world data to derive common data elements for alzheimer's disease and ad-related dementias research through ontological innovation," we propose to create a ten- institution research network for developing an ad/adrd-focused, collaborative data ecosystem incorporating cdes to leverage RWD for empowering NIA-funded studies, and for enhancing the transparency, rigor and reproducibility of ad/adrd research. Our aims cover the development (aim 1), application (aim 2), and dissemination (aim 3) of ad/adrd cdes and AI/ML/NLP tools through this national collaborative recardo research network (RRN). These aims will be achieved through the organization of the RRN in seven work streams: 1. CDE development and CDE knowledge graph; 2. CDE extraction from RWD; 3. Data, metadata, and resource ecosystems; 4. AI/ML/NLP and computational phenotyping; 5. Research questions, use cases, and CDE application, including a pilot study program; 6. Genetics, imaging, biomarkers and big data; and 7. Reproducibility and evaluation. Administrative support (aim 4) will be provided through five key functions: steering committee (SC) and external advisory panel (EAP); management and support for work streams, annual meeting, and the pilot study program; innovation capacity development; governance framework adopting best practices; and dissemination and outreach activities, including a project web portal. This project is significant because IT creates an ecosystem approach to addressing data harmonization and reproducibility challenges in maximizing the value of RWD through partnership among adrcs. This project is innovative because IT builds on the latest data science and ontological advances to ensure sustained impact in a federated data ecosystem incorporating ad-cdes for translating RWD to RWE. Our novel conceptual project framework is designed to bring together teams and ensure the effective operation and impact of the RRN in a milestone-driven, collaborative setting, led by a group of world-class data scientists working side-by-side with some of the most established domain experts in ad/adrd. Success of recardo will revolutionize our approach to translational data-driven discovery in ad/adrd research, for decades to come.