Neurology diseases biomarker discovery and therapeutic monitoring

Using secure, standardized health data and AI to uncover biological signals that can improve how brain diseases are studied and monitored

Neurodegenerative diseases such as Alzheimer’s disease are complex and difficult to study because biological signals linked to disease progression are scattered across many datasets and measured in different ways. This project brings together biological data from human brain–derived tissue models and public datasets, and uses modern data standards and artificial intelligence (AI) methods to make these data easier to combine, analyze, and reuse.

Many promising discoveries in precision medicine fail to translate because data are fragmented, poorly standardized, or inaccessible. This project addresses that gap by organizing biological data in a secure, privacy-preserving way so researchers can better identify biomarkers that may be useful for disease monitoring or therapeutic development. Improving how these data are structured and shared can accelerate research while reducing duplication of effort.

By the end of the project, the team will have:

Integrated metabolomics and biomolecular datasets into a standardized, FAIR-aligned format
Demonstrated how these datasets can be analyzed using AI-based approaches
Contributed reusable data pipelines, documentation, and metadata to the DHDP ecosystem

“Neurodegenerative diseases remain an area of high unmet need, and better data integration is essential for advancing both research and therapeutic development.”

“Participating in this initiative reflects a shared commitment to responsible AI, collaborative science, and building sustainable digital health infrastructure in Canada.”