Dan is the CEO of Distributive, a Kingston-based software company reimagining how the world computes. He holds a PhD in Physics from Queen’s University and previously served as a military pilot and a Physics professor at the Royal Military College of Canada.
Day 1: Dec 5, 2023
Day 2: Dec 6, 2023
4:15 pm
CASE STUDY: MULTI-HOSPITAL FEDERATED LEARNING WITH REVENUE SHARING
From Siloed Data to Precision Insights: How a Multi-Omic Federated AI Platform Is Advancing Psoriatic Arthritis Care
Psoriatic Arthritis affects nearly 300,000 Canadians, yet treatment selection remains a trial-and-error process due to fragmented datasets, strict privacy constraints, and limited computational infrastructure. To address this, our team built a federated, multi-omic learning platform that brings models to the data—spanning genomics, proteomics, metabolomics, and clinical records across multiple hospitals. The approach preserves patient privacy, accelerates precision-medicine research, and introduces a revenue-sharing model that lets institutions participate directly in the value they help create.
Leave with a practical strategy to:
- Deploy federated learning across hospitals while keeping all patient data on-premise
- Combine multi-omic data streams to improve treatment-response prediction for complex diseases
- Leverage validated genomic markers (HLA-B27, HLA-C06, TNFAIP3, IL23R, TYK2) within scalable ML pipelines
- Achieve strong predictive performance using ensemble approaches, with retrospective AUCs up to 0.96
- Align hospitals, researchers, and industry partners using an equitable, revenue-sharing commercialization model
Fuel more efficient clinical research, stronger predictive models, and scalable precision-medicine programs through federated multi-omic AI.
