Welcome to Phaedra 2.0

Phaedra 2.0 is the next-generation open source platform for High Content Analysis, Evaluation and QC. Use it to:

  • Import huge data volumes from local, network or cloud storage
  • Define plate layout definitions in Phaedra, or integrate with your own plate definition system to retrieve them automatically
  • Define protocols to compute features, normalizations, and other types of calculation
  • Configure those features for automatic fitting of dose-response curves
  • Visualize data, both raw and calculated, using various tables, charts, image viewers, etc.
  • Perform data validation using a controlled, secure and auditable approval flow
  • Retrieve data into downstream processing apps or environments using one of Phaedra’s public APIs
  • Future updates will bring many additional functionalities, such as automated report generation, Python scripting, and much more.

As the successor to version 1.x, Phaedra 2.0 is built up from scratch using extremely scalable, modern, cloud-friendly technology, all of it open source:

  • Containerized using Docker and Kubernetes
  • Event-driven, decentralized architecture with a RESTful API, a GraphQL API, and extensive support for event streaming
  • Customizable and extensible through various programming languages such as R and JavaScript
  • Secured by OAuth2 technology, and bundled with a Keycloak server that can interface with virtually all enterprise identity and access providers
  • High performance OpenJPEG image codec, for efficient compression and real-time rendering of images of any resolution


Phaedra 2.0 is freely available and released under the terms of the Apache License 2.0.

All Phaedra 2.0 source code can be found on GitHub.


Community Support

Don’t find the information you need in our documentation? Reach out on our Q&A website under the “Phaedra” category.

Commercial Support

Open Analytics has been involved with Phaedra’s design and development since day one. They offer support contracts for organizations and companies that want to rely on their expertise for in-house deployments, maintenance and user support. Typically this entails:

  • Development of custom features or protocols for particular assays
  • Integration with other software in the screening workflow
  • Development of statistical or machine learning methodology for a particular problem
  • L1/L2/L3 support on customer deployments and user training