Skip to main content
NIH
Forecasted

RFA-AG-27-002

Translational Center for Accelerating the Use of Digital Health Technologies Data in AD/ADRD Research

Summary

AI-generated

Translational Center for Digital Health Technologies in Alzheimer's Disease Research

The National Institute on Aging seeks to establish a Translational Center for Accelerating the Use of Digital Health Technologies (DHT) Data in Alzheimer's Disease (AD) and AD-Related Dementias (ADRD) research. The center will build cloud-based infrastructure and methods to host, integrate, and enable reuse of multi-modal digital health data—including legacy datasets and newly generated data—from AD/ADRD studies. A core deliverable is a federated, FAIR (Findable, Accessible, Interoperable, and Reusable) data repository designed for secure storage, processing, and multi-modal integration of DHT data to accelerate translational and clinical research in aging-related cognitive decline. The center will establish best practices for data discovery, access, and dissemination, positioning digital health technologies as a scalable resource for the AD/ADRD research community.

This opportunity spans biomedical informatics, clinical research, and aging science, emphasizing data infrastructure and translational methods rather than single-investigator discovery.

  • Who can apply: Institutions with capacity to develop multi-component research centers; applications not yet solicited—this is advance notice to enable collaboration planning.
  • Funding & project length: Not stated.
  • Award mechanism: U54 (Specialized Center).
  • Key dates: NOFO publication pending; applications not currently solicited.
  • Best fit for: Teams in biomedical informatics, gerontology, and digital health with expertise in data harmonization, cloud infrastructure, and AD/ADRD clinical cohorts.

Insights (5)

Digital health technology expertise and preliminary data critical for competitiveness

strategic fit

This Center requires deep technical expertise in DHT data infrastructure, FAIR principles implementation, and multi-modal data integration—not just AD/ADRD domain knowledge. Applicants with existing experience managing large-scale biomedical data repositories, cloud-based federated systems, or prior work harmonizing legacy datasets will be significantly more competitive. Preliminary data demonstrating proof-of-concept for FAIR-compliant DHT data integration or evidence of successful data repository governance will strengthen applications.

Multi-institutional consortium structure likely essential for U54 Center mechanism

collaboration

U54 mechanisms are designed for multi-component Centers requiring coordinated, distributed expertise. Success will depend on assembling a consortium that spans AD/ADRD clinical research, biomedical informatics, data science, cloud infrastructure, and regulatory/governance expertise. The emphasis on 'legacy and new DHT data' and 'federated' architecture suggests the lead institution cannot operate in isolation—partnerships with existing AD/ADRD cohort studies and data-generating programs will be strategically necessary.

Cloud infrastructure and FAIR compliance requirements limit institutional capacity

eligibility

The requirement to establish a 'cloud-based; federated' FAIR data infrastructure with secure storage and processing capabilities is not trivial—it demands institutional investment in cloud platforms, data governance frameworks, and compliance infrastructure (likely including HIPAA, 21 CFR Part 11, and NIH data sharing policies). Institutions without existing biomedical data repository experience or cloud partnerships may face significant barriers to meeting this infrastructure requirement, effectively narrowing the competitive pool to research-intensive medical centers and data-focused institutions.

Narrow scope and specialized infrastructure requirements suggest limited award number

competition

The highly specific focus on DHT data for AD/ADRD, combined with the infrastructure-intensive U54 mechanism and emphasis on a single 'Center,' suggests this is likely a single or very limited number of awards. The requirement for federated, FAIR-compliant cloud infrastructure further restricts the pool of capable applicants. Competition will be intense among institutions with existing data repository and informatics infrastructure.

Senior leadership with data infrastructure track record essential; limited ESI advantage

career stage

This Center mechanism favors established investigators with demonstrated success managing large-scale data initiatives and multi-institutional collaborations. Early-stage investigators (ESI) are unlikely to be competitive as lead PIs unless embedded within a senior-led consortium. However, ESI with specialized DHT or biomedical informatics expertise could strengthen a team in supporting roles, particularly in technical components focused on data integration or FAIR implementation.

Key Facts

Deadline

Posted

Wed, September 3, 2025

U54
93.866
Grants.gov

Keywords

digital health technologies
Alzheimer's disease
dementia
data repository
FAIR data principles
translational research
multi-modal data integration
clinical research
biomedical informatics
aging research
data interoperability
cloud-based infrastructure
federated data systems

Research Areas

NIH Institute
AgingNIA
OpenAlex
Life SciencesD1Physical SciencesD3Health SciencesD4
Fields
Computer ScienceF17Environmental ScienceF23MedicineF27NeuroscienceF28
Subfields
Artificial IntelligenceS1702Computer Science ApplicationsS1706Information SystemsS1710Health InformaticsS2718NeurologyS2728Public Health & Occupational HealthS2739Cellular & Molecular NeuroscienceS2804Cognitive NeuroscienceS2805
Topics
Cloud Computing and Resource ManagementT10101Privacy-Preserving Technologies in DataT10764Telemedicine and Telehealth ImplementationT10912Cloud Data Security SolutionsT11614Artificial Intelligence in Healthcare and EducationT11636Research Data Management PracticesT11937Explainable Artificial Intelligence (XAI)T12026Health and Medical Research ImpactsT12168+7 more
MeSH
DiseasesC
Nervous System DiseasesC10Pathological Conditions & SymptomsC23
Analytical/Diagnostic/Therapeutic TechniquesE
DiagnosisE01Investigative TechniquesE05
Phenomena & ProcessesG
MetabolismG03Physiological PhenomenaG07
Disciplines & OccupationsH
Health OccupationsH02
Technology/Food/BeveragesJ
Information ScienceL
Information ScienceL01
Health CareN
Health Care ServicesN02Health Care EconomicsN03Health Services AdministrationN04Health Care Quality & EvaluationN05Environment & Public HealthN06
ANZSRC FoR
Biomedical & Clinical Sciences32
Clinical Sciences3202Neurosciences3209
Health Sciences42
Epidemiology4202Public Health4206
Information & Computing46
Applied Computing4601Data Management & Data Science4605Information Systems4609
Mathematical Sciences49
Statistics4905

AI-generated content — verify with the issuing agency’s official FOA/NOFO. Not endorsed by HHS.

© 2026 Biostochastics, Seattle WA · Contact · Terms · About