Apheris for Pharma

Collaborate with partners on data and AI. Innovate and evolve the practice of life sciences​.

Trusted by our customers & partners

What customers are saying about Apheris

«Apheris' technology empowered granular access to European Union data for our real-world evidence study exploring treatment and outcomes in oncology. The potential to impact the understanding, creation, and adoption of therapies that cater for more diverse populations is remarkable.»

Kevin Pollock Ph.D., MPH
Director RWE Strategy, International Markets at Bristol Myers Squibb

Billions are spent on licensing limited datasets – ​still 97% of all healthcare data remains inaccessible

The Apheris Compute Gateway enables access to the world’s best data for compliant, private and secure research

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 founded by AbbVie and Johnson & Johnson 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.

3 modes of collaboration for pharmaceutical companies

Build your own site network

Build a federated data network with your existing site relationships. Execute any new study at accelerated pace.

Partner with other Pharma

Partner with your peers in a consortium – gain valuable research insights while protecting your data IP.

Get deeper access to healthcare software & data vendors​

Enable trusted users to view metadata of your datasets. Upload synthetic discovery data helping your users to understand structure and value without compromising on privacy.

Support use cases across the whole Pharma value chain

Compliance is a top priority for us

Want to collaborate on distributed data?

Learn how to foster collaboration in a secure, private and compliant way. Talk to us about governed data access for analytics and ML.