FL-CHEMSAFE
The Future of
Chemical Safety Assessment
Enabling secure, collaborative QSAR modelling through federated learning.
About
Join a global network redefining predictive toxicology —
share knowledge, not data.
FL-CHEMSAFE empowers organisations to advance
chemical safety assessment with cutting-edge federated learning,
ensuring privacy, performance, and regulatory confidence.
Problem vs Solution
Rethinking
In Silico Predictions
Current QSARs Workflow
Today’s QSAR models are trained in isolation, using limited datasets. This leads to:
• Conflicting predictions between models
• Narrow chemical space coverage
• High uncertainty in decision-making.
FL-CHEMSAFE Approach
Imagine combining unseen proprietary data across organisations without sharing raw data. Federated learning enables:
• Access to broader chemical space
• More balanced predictions across adverse events
• Preservation of your confidential data.
New to Federated Learning?
Get a hands-on introduction with our free 7-day newsletter challenge.
Easy daily lessons
Real-world examples
Learn at your own pace
Benefits
Benefits
Unlock the Advantages of Federated QSARs
Experience how collaborative, privacy-first innovation can advance chemical safety assessment, and discover why now is the perfect time to participate in our proof-of-value initiative.
Zero Direct Data Sharing
Share model updates, not sensitive data — safeguard your IP and proprietary research.
Zero Direct Data Sharing
Share model updates, not sensitive data — safeguard your IP and proprietary research.
Broadened Chemical Space
Leverage unique proprietary knowledge across the consortium for more robust, generalisable QSAR models.
Broadened Chemical Space
Leverage unique proprietary knowledge across the consortium for more robust, generalisable QSAR models.
Improved Confidence
Reduce conflicting predictions and uncertainty, especially in low-data or novel chemical scenarios.
Improved Confidence
Reduce conflicting predictions and uncertainty, especially in low-data or novel chemical scenarios.
Scalable Security
Built-in compliance with the highest security standards, including ISO 27001 certification.
Scalable Security
Built-in compliance with the highest security standards, including ISO 27001 certification.
Lower Carbon Footprint
Train models where the data resides, minimising data transfers and reducing environmental impact.
Lower Carbon Footprint
Train models where the data resides, minimising data transfers and reducing environmental impact.
Recognition & Milestones
Recognition & Milestones
Our Journey So Far
Oral Presentation QSAR2025 Award
Oral Presentation QSAR2025 Award
One of the five
start-ups selected for
One of the five
start-ups selected for
FAQ
Frequently Asked Questions
Get answers about participating in the first secure, collaborative
consortium for chemical safety assessment.
Who should join the FL-CHEMSAFE proof-of-value consortium?
How is sensitive or proprietary data protected?
Can FL-CHEMSAFE accommodate different data formats or endpoints?
How does FL-CHEMSAFE handle imbalanced datasets?
How is data privacy ensured?
Get in Touch
Ready to explore the benefits of collaboration?
Connect for a no-pressure conversation and discover how joining FL-CHEMSAFE could accelerate your chemical safety assessment goals.
© 2025. All rights reserved.
An initiative by AI4Cosmetics
FL-CHEMSAFE
FL-CHEMSAFE
The Future of
Chemical Safety Assessment
Enabling secure, collaborative QSAR modelling through federated learning.
Join a global network redefining predictive toxicology — share knowledge, not data.
FL-CHEMSAFE empowers organisations to advance
chemical safety assessment with cutting-edge federated learning,
ensuring privacy, performance, and regulatory confidence.
About
About
Problem vs Solution
Problem vs Solution
Rethinking
In Silico Predictions
Current QSARs Workflow
Today’s QSAR models are trained in isolation, using limited datasets.
This leads to:
• Conflicting predictions between models
• Narrow chemical space coverage
• High uncertainty in decision-making.
FL-CHEMSAFE Approach
Imagine combining unseen proprietary data across organisations without sharing raw data. Federated learning enables:
• Access to broader chemical space
• More balanced predictions across adverse events
• Preservation of your confidential data.
New to Federated Learning?
Get a hands-on introduction with our free 7-day newsletter challenge.
Easy daily lessons
Real-world examples
Learn at your own pace
Who should join the FL-CHEMSAFE proof-of-value consortium?
How is sensitive or proprietary data protected?
Can FL-CHEMSAFE accommodate different data formats or endpoints?
How does FL-CHEMSAFE handle imbalanced datasets?
How is data privacy ensured?
Who should join the FL-CHEMSAFE proof-of-value consortium?
How is sensitive or proprietary data protected?
Can FL-CHEMSAFE accommodate different data formats or endpoints?
How does FL-CHEMSAFE handle imbalanced datasets?
How is data privacy ensured?
Connect for a
no-pressure conversation and discover how joining FL-CHEMSAFE could accelerate your chemical safety assessment goals.
Ready to explore the benefits of collaboration?
Get in Touch
Get in Touch
© 2025. All rights reserved.
An initiative by AI4Cosmetics
FAQ
FAQ
Frequently Asked Questions
Get answers about participating in the first secure, collaborative consortium for
chemical safety assessment.