With an increasingly aging global population and no available preventative treatments, Alzheimer’s disease and related dementias are poised to become an even larger public health challenge. The mechanisms underlying Alzheimer’s disease are difficult to study because the disease has a long developmental period during which changes in the brain can occur years before symptoms appear. It also has significant variation across individuals in terms of what causes the disease and how it develops. A promising solution for addressing this complexity is to develop precision medicine approaches that tailor treatments to each person’s specific risk factors, disease mechanisms and treatment responses. To achieve this, scientists need access to extremely large and comprehensive datasets.
In order to tackle this problem, researchers, under the leadership of Sarah A. Biber, PhD, associate professor of neurology at WashU Medicine, are working toward creative and transformative approaches in how we detect, treat and follow Alzheimer’s disease in patients. In an article published in Alzheimer’s & Dementia, Biber and her collaborators deployed a proof-of-concept platform that demonstrates the feasibility of securely linking longitudinal multimodal patient-level data across sources to advance Alzheimer’s disease research and patient care.
With researchers at WashU Medicine’s Knight Alzheimer’s Disease Research Center (ADRC), the Indiana University ADRC and the Columbia University ADRC, a team from the National Alzheimer’s Coordinating Center (NACC) developed a data integration and governance model that has the potential to be scaled broadly across all ADRCs. This multimodal data framework is expected to drive discovery and enable individualized treatment in Alzheimer’s disease and related dementias (AD/ADRD), as well as presenting a standardized implementation model for data consortia across human diseases.
As the era of big data continues, Alzheimer’s disease researchers are looking to incorporate data from outside the ADRC programs into the existing data framework managed by NACC, currently based at the University of Washington in Seattle, Wash. Walter A. Kukull, PhD, now professor of neurology at WashU Medicine, founded NACC in 1999 to manage and streamline the unprecedented scale of data generated by the nearly 40 centers participating in the National Institute on Aging (NIA)-funded ADRC program. Biber co-led the NACC from 2021 to 2025 as executive director.
NACC developed the Uniform Data Set (UDS), which collects robust longitudinal data at the individual patient level in a standardized and comprehensive way and serves as a trusted benchmark for clinical and demographic data for AD/ADRD research. The study’s authors stated that if UDS data was integrated with data from electronic health records (EHR), Medicare claims and genomic information, it could help scientists build predictive models for disease development and progression in individuals, diagnose patients earlier and better match individuals to specific disease-modifying treatments. Moreover, they noted, AD researchers would be able to incorporate data from patient populations and geographic areas that have historically been underrepresented in AD research and drug development.
The authors said a number of obstacles had to be overcome to make the new infrastructure work — the amount of variability and incompleteness in coding and documentation practices in the real-world clinical setting, and legal, ethical and regulatory considerations, such as HIPAA compliance, participant consent and data governance. “It was very much a socio-technical challenge we were solving,” Biber said.
Biber and her team concluded that their pilot successfully demonstrated the feasibility of securely linking gold-standard clinical research data, EHR and claims data and genomic profiles to build holistic, longitudinal participant profiles for over 2,000 individuals across three separate research centers. They also noted that the governance and security components developed for this pilot could serve as the starting point for future centralized frameworks. This type of linked, longitudinal data infrastructure provides a foundation for AI-driven approaches that integrate diverse data to identify patterns in disease risk, progression and treatment responses.
As efforts like this expand across the ADRC program and beyond, the researchers said they will be able to study disease progression at unprecedented levels of detail, linking what is observed in research settings with what happens in real-world clinical care. “What we’re building is a more complete and connected view of each patient’s journey,” Biber said. “That kind of understanding is essential if we want to move toward earlier detection, more personalized treatment and better outcomes for people living with Alzheimer’s disease.”
Biber S, Culhane JE, Prado MG, et al. Integrating real-world data with gold-standard longitudinal clinical and genomic data to advance precision medicine for the Alzheimer’s Disease Research Center Program and beyond: a proof-of-concept data platform. Alzheimer’s Dement. 2026;22:e71207. https://doi.org/10.1002/alz.71207