Cambridge, United Kingdom
23 May 2023
Today, Eagle Genomics, the pioneering TechBio business applying network science[*] to biology, announced it had been Highly Commended as ‘Artificial Intelligence (AI) Company of the Year’ at the 2023 Cambridge Independent Science and Technology Awards. The company was shortlisted for this Award alongside several well-recognized Cambridge-based AI companies.
Anthony Finbow, CEO, Eagle Genomics, said: "This recent commendation underscores our use of leading-edge technologies to better understand microbes, microbiome function and host- microbiome interactions and help scientists exploit that understanding. This is part of our efforts to accelerate the Bioeconomy through the digital reinvention of the life sciences. We thank the Cambridge Independent Science & Technology Awards organisers and judges for the recognition.”
The Secretary of State for Science, Innovation and Technology, Chloe Smith, said that the Awards were “a really important contest that illustrates the best of what Cambridge has to offer and the strengths of British science.”
Eagle Genomics’ award-winning artificial intelligence (AI)-augmented knowledge discovery platform, the e[datascientist]™, is powered by network science and multilayer hypergraphs[**], applying machine learning and AI to provide a data-driven insight journey into solving complex problems and delivering impact at scale. It allows scientists to ask and address a novel class of questions enabled by networked data, network analysis, and network thinking.
In January 2022, the company announced scale-up funding from OMRON Ventures following the USD $20 million first close of its scale-up funding round in October 2022.
In their sixth year, the Cambridge Independent Science & Technology Awards are recognized as a celebration of the extraordinary talent in the region across a host of science and technology sectors.
Notes
* Network science is the study of complex networks of physical, biological, and social phenomena, and can also be used to explain and deeply understand these phenomena.
** The e[datascientist]™ is powered by network science and multilayer hypergraphs, applying machine learning and AI to provide a data-driven insight journey into solving complex problems at scale. It integrates active learning at every step of the microbiome innovation journey, from 'descriptive' to 'predictive,' while identifying mechanisms of action, and has been gaining major traction with large household brands as they strive to demonstrate the link between their latest products and microbiome health.
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