An intuitive platform for the food and beverage industry

E[datascientist] - Feeding the innovation funnel in large-scale organisations

Time to create robust scientific product claims through a data driven process. Whether it’s the innovation of plant-based products, analysis of animal gut health for better food, or the creation of functional foods and ingredients, the e[datascientist] is the answer. 

Organisations already on board the Eagle Genomics’ train



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The world is facing new challenges like never before

  • Make scientific plant-based product claims
  • Delve into animal biology and create nutrition rich food and feed through in-depth analysis of intestinal microbiota present in animal hosts 
  • Develop healthy packaged products with the right balance of micronutrients and probiotics
  • Understand the role of the gut microbiome present in humans in order to address immunity issues, diabetes, obesity and more
  • Analyse the relationship between health and mental wellness in humans 







"Not only our science has to evolve — also our way of doing microbiome research and understanding multi-omics. Without Eagle Genomics’ data pipelines, we would learn something from each scientific study, but it wouldn’t go anywhere beyond that." 
Samantha Tucker-Samaras, Global Vice President Science & Technology, Beauty and Personal Care R&D at Unilever.


The e[exploration] collection

The e[datascientist]’s exploration collection applies a data driven approach that encompases network science and graph theory to:

  • Provide a curated and catalogued data repository generated from multiple databases such as KEGG, Human Metabolite Database, FooDB etc. 


  • Enable scientists to infer key relationships, and the strength of those relationships, between different entities via an intuitive scoring system. 
  • Equip teams to normalise, standardise and correct data for further statistical analysis and graph exploration.
  • Provide scientists with the ability to improve hypothesis formulation through an interactive and exploratory data analysis approach, and apply the formulated hypotheses on a broad range of datasets.

Interested in learning more? Have a look at Eagle Genomics' e[datascientist].