The leading AI platform for collaborative disease and drug research
We enable (pre)clinical researchers to take a translational systems biology approach to disease and drug research. Powered by the largest AI integrated knowledge base researchers get access to a suite of applications including Search optimised for disease and drug biology, Analytics for multi-omics & systems biological insights and a Knowledge Graph for exploring biomolecular interaction networks.
Search - Optimised for disease and drug biology
- Target Assessment
- Gene-Disease Analysis
- Set Creation.
Analytics - Systems biological multi-omics insights
Gene Set Enrichment
Gene Set Ranking
Transcription Network Analysis
Knowledge Graph - Biomolecular interaction analysis
Workflows - Target discovery & assessment (and more)
Target Discovery in Oncology
Target Discovery for Bispecific Antibodies.
We enable collaborative disease and drug research at multiple levels. Academic and corporate users can work together using the same core functionality. Sets, Analytics projects and Knowledge Graphs can be shared directly within the same organisation. We publish selected curated datasets or machine learning results with all our users.
"In this project we evaluated you against our internal investigations and the results of one other external provider. What really sets you apart is how you combine a fundamentally biological and data driven approach. The breadth of the indications you assess and the depth of your analysis sets you apart and is a clear value add to our internal capabilities."
"We have been working with Euretos for many years now. They provide us with unique tools that we use as an integral part of our target discovery and validation. Using the Euretos AI Platform is a mandatory input to our target evaluation meetings"
"We are fascinated by the suggested hypothesis. It was great that even very small expressional changes were captured and a hypothesis was generated. The interpretation was also convincing and consistent. Also the team is well engaged, and had a very good understanding in the background of the project and our research question"