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Pythia BioSciences Multi Omics Analysis Software and Services 

"Every scientist is important because every patient is important"  

An intuitive user interface for biologists and a command line interface for bioinformaticians and data scientists powered by a customizable microservices based architecture

Let Multi-Omics Data Take Your Research to Higher Grounds

Tackle top challenges in Multi-Omics

  • Conduct multi-omics experiments with an Intuitive Graphical Interface

  • Tear down the data silos 

  • Keep up with the latest data types, datasets and knowledge models

  • Integrate with public, third party and private databases and software tools. 

  • Unite scientists with their  colleagues in Bioinformatics, Datascience and Cheminformatics. 

  • Share data, results and entire projects

Integration and customization 

Microservice based cloud architecture enables rapid deployment, integration and customization.

  •  Integration with public, third party and private data sources, pipelines and applications, like R shiny data visualization dashboards.   

Unified Multi-Omics Data management and  Analysis 

Easily explore the various types of omics data as individual datasets and as integrated analysis workflows that can be customized for optimal performance. 

Next Generation pathway and interactome knowledgebase 

Multiple pathway and interactome knowledge sources and workflows,  including Pythia's   Intercellular Signaling Prediction.  

Adjustable Target & Biomarker  workflows

Choose common workflow templates and customize your own.  Additionally,  Tox, MOA and PD biomarker workflows are in development and  coming soon.

Unprecedented Velocity of Development. Impeccable Reliability of Deliverables.

Pythia Biosciences created its CDIAM multi-omics analysis software platform as a microservices architecture with speed of development, adaptability and customization in mind.  CDIAM stands for Carpe DIAM meaning seize the Data, Interactome, Algorithms and Machine Learning.  We live at the most exciting time in history for science when very new and very different Omics technologies, Datasets, Knowledge models and algorithms including Machine learning and AI are being developed at an extremely fast pace.  This pace is not slowing down and with drug development organizations requiring more and more customization the age of platforms that cannot easily adapt to this environment is coming to an end.   

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