A quick introduction
We enable toxicology teams to generate robust in silico predictions — without sharing sensitive data — using privacy-enhancing technologies such as federated learning.
Why it matters
Run QSAR models on distributed datasets without the proprietary data leaving your infrastructure.
Get toxicity predictions for your molecules without exposing them to external systems.
Collaborate across organisations for stronger safety evidence, such as Adverse Outcome Pathways.
Designed for chemical hazard screening and prioritisation supporting the transition to non-animal approaches.
A quick introduction
Outreach
Are you organising an event or leading a team or a community that would benefit from an introduction to federated learning for chemical safety assessment?
Invite us to speakPast engagements
New to the topic?
This series of blog posts will guide you through the essentials of Federated Learning: what it is, why it matters, and how it's already transforming life sciences.
Milestones
