Rates of Disease Progression — Disease Progression Tracking
Modeling rates of disease progression across existing trial and cohort data to uncover the factors driving decline — and to guide better-targeted treatments and interventions.
The Challenge
What are the key factors driving differential rates of disease progression?
Our Approach
Combining multimodal data across neurodegenerative diseases to uncover insights no single study could reach.
Disease progression varies widely from one person to the next, yet the reasons remain poorly understood. Today's research is fragmented across siloed datasets and inconsistent definitions, leaving studies underpowered to detect the patterns that matter. This project brings the data together to identify, quantify and interpret the biological, clinical and methodological drivers of progression across neurodegenerative diseases — including Alzheimer's, Parkinson's, frontotemporal dementia and ALS.
This project harmonizes and analyzes clinical-trial and longitudinal-cohort datasets at scale, convening a global, interdisciplinary consortium of academic, industry and nonprofit partners.
Bringing these datasets into a common environment makes it possible to compare findings across studies and surface signals no single dataset could reveal on its own.
Key Research Questions
This project's work is organized around a set of priority questions on what drives differential progression.
Drivers of Progression
Predictive Features
Progression Subtypes
Cross-Disease Patterns
Representative questions, not a comprehensive list.
This project and its partners continue to be defined; additional investigators will be added as they are confirmed.