Scientific Strategy

Making ADRD Data Shareable, Accessible and Analyzable

Strategic Direction Through Thematic Alignment

Guided by an evolving list of priority research questions originally assembled in 2018, the AD Data Initiative is shaping the future of scientific discovery by integrating insights from our Advisory Board, community feedback, and thought leadership engagements. We envision this list of questions as a dynamic blueprint that will drive innovation, inform strategic decisions, and inspire the next generation of collaborative breakthroughs.

Mapping Priority Research Questions to 8 Key Themes

Can we identify biological pathways that might be: 

  • Targets for intervention? 
  • Shared with other neurodegenerative diseases? 
  • Used to stratify patients? 
  • Used to facilitate clinical trials agnostic to existing clinical diagnostic categories?

How can we rapidly, repeatedly, and consistently measure cognitive function?

  • Can we combine existing & new data to track aging and disease progression?
  • Can we identify novels ways to predict and delay the conversion of mild cognitive impairment to Alzheimer’s disease?
  • What factors influence or underpin speed of progression – can that information lead to novel treatment targets for slowing disease and or stratification for clinical trials? 
  • Can we identify a range of non-invasively collected biomarkers for determining Alzheimer's Disease and Related Dementias (ADRD) progression?
  • Can we assess the validity and reliability of proposed novel biomarkers and diagnostics?
  • Can we define multimodal approaches for early detection and risk prediction (including digital and activities of daily living)?
  • Can explainable AI help create models of low-level personalized risk factor interactions to help with early diagnosis of ADRDs?
  • Are there lifestyle or behavioral changes that will pause or delay Alzheimer’s disease symptoms?

Can subtypes of Alzheimer’s disease be further defined based on biomarker data and clinical presentation?

  • How are ADRD risk prediction models similar and different in LMICs compared to high-income countries?
  • Are models for LMICs applicable across LMICs or different between countries?

Can we identify the risk determinants associated with ARIA?

Cross-cutting themes include 

  • Diversity of study participants 
  • Generative AI to accelerate progress

Strategic levers to accelerate progress

Gates Sr AD Fellows

Data Challenges

Research Collaborations & Consortia 

Drivers Projects