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e[cohort]

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02_Exploration_High_v2
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Create and explore customizable virtual cohorts
e[datascientist] biology Request a demo

Scientific challenge

It is challenging to apply a systematic approach to identify the key characteristics that best define a cohort. Life scientists often know they are missing relevant cohort features. 

Teams need a structured environment to appropriately select relevant stratification criteria, perform cohort analyses and generate traceable results.

Comparison between different studies which do not follow the same standard often leads to invalid or incomplete results, owing to the lack of standardized contextual metadata.

e[cohort] generates reliable and reproducible results via unconstrained, data-driven virtual cohorts underpinned by the e[datascientist] valuation engine.

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Key features

  • Create virtual cohorts of subjects based on multiple selection criteria (e.g. genotype, phenotype, indication, biomarker, treatment regime, etc.)
  • Apply and maintain (store, share, reuse) customizable valuation models to rank and prioritize virtual cohorts
  • Perform meta-analysis and downstream cohort analysis, using tools to help with network exploration, statistical models, subgroup comparisons and stratification
  • Generate interactive visualizations of data, and present results in the most compelling, informative way
  • Export comprehensive reports within minutes, ensuring traceability, transparency and collaboration
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Benefits

  • Build unconstrained virtual cohorts driven by a robust valuation framework
  • Define cohorts in a collaborative environment, ensuring informed stakeholder alignment
  • Evidence cohort priorities with justifiable criteria based on true data characteristics
  • Identify indicative correlations and use causal analysis to confirm/refute causal interactions
  • Inform future follow-up experimental and in silico studies to accelerate innovation
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Explore the platform

applications
applications
applications
services
Augment the internal data estate with an industry-defining data universe designed to accelerate collaborative innovation in the microbiome space.
low-code customer apps
Compose robust low-code applications covering a range of business needs. Extend e[datascientist] to deliver custom capabilities and experiences.

Innovating for a better future

Eagle Genomics’ innovative approach in establishing a platform-driven ecosystem for the generation and exchange of scientific data-derived assets is of great potential value to Unilever.
Samantha Tucker-Samaras
Global Vice President Science & Technology, Beauty and Personal Care R&D at Unilever.
Healthy animals, healthy people and a healthy planet are all interconnected. With the advanced knowledge and insights we anticipate generating from our microbiome data, the e[datascientist] will allow us to bring more relevant products to market.
Mike Johnson
Marketing Director at Cargill Health Technologies
As a company driven by innovation, Reckitt collaborates with partners who bring powerful new capabilities to the table so we can deliver disruptive ideas to the market.
Chris Jones
Vice President of R&D Hygiene at Reckitt
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