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Improve AI model performance with life sciences data networks

Apheris securely connects proprietary life sciences data while preserving confidentiality and IP.

We power federated data networks

Proprietary life sciences data is stored in private data repositories due to IP and privacy concerns.

But data from the public domain lacks diversity to build ML models that achieve the required accuracy and generalizability.

We address this challenge: collaboratively train higher-quality models on data of multiple parties - while keeping data IP and confidentiality protected.

Powering the AISB Consortium to Revolutionize AI Drug Discovery

Apheris provides the tech layer for the Artificial Intelligence Structural Biology (AISB) Consortium, an unprecedented collaboration among AbbVie, Boehringer Ingelheim, Johnson & Johnson, Sanofi and Takeda aimed at transforming AI drug discovery. State-of-the-art AI models will be trained and evaluated on unique data from multiple biopharma companies without exposing proprietary information.

Visit the AISB page

A Gateway to better models in life sciences

Gain access to higher-quality and more generalizable models. Join secure, federated, privacy-first data networks or build your own. The Apheris Gateway provides granular data privacy controls, model IP protection, and integrates with your existing tooling.

Maintain complete control over users, models and their access to your data. Adapt to new research protocols swiftly with full governance and minimal hassle.

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Trusted by our customers and partners

What our customers and partners say about us

Public data lacks both quantity and chemical diversity, limiting ADMET models' predictive power and applicability domain. By joining a federation-powered ADMET Consortium, pharma companies and biotech can address this challenge and gain access to better models. Apheris has the expertise and product to enable secure, federated collaborations that protect everyone's IP and data privacy.

Darren Green, PhD
Formerly Director of Cheminformatics at GSK; Honorary Professor of Chemistry at University College London

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