Securing contracts with three-quarters of the world’s largest pharma companies, SciBite topped the chart having delivered compound annualised growth of 76% over the past two years, and now boasts a workforce of 50+ scientific experts servicing more than 50 clients worldwide.
SciBite’s software technology combines the latest developments in machine learning with its ontology-led approach, providing an infrastructure that understands the complexities of scientific data. It gives customers the ability to build their data foundation with standardisation, harmonisation and acceleration.
“This is a great accolade for us to receive and it’s as a result of our amazing team and amazing customer base that achievements like this one are possible.” says CEO and President Rob Greenwood.
“When SciBite’s journey began we could see that there was a real change in the market with pharma realising the value of their data and recognising that they needed help to understand and analyse it. We’ve grown rapidly since bringing our cutting-edge technology to the market and built a continually growing team who share a common passion for helping our customers make their data better.”
In their upcoming webinar Head of Ontologies Jane Lomax will explain how SciBite is working with customers to embrace FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. They believe this need for FAIR is never more acutely felt than with the increasing investment in areas such as training deep learning models, as well as in search and big data integration.
Read more about SciBite’s Pharma Fast 50 win.
SciBite provides an enterprise-ready semantic software infrastructure to standardise and transform scientific information silos into clean, interoperable data. Supporting the top 20 pharma with use cases across life sciences, SciBite is headquartered in the UK with additional sites in the US and Japan.
SciBite today announced being named as a winner of the Queen’s Award for Enterprise in International Trade – the highest official UK awards for businesses.Read
In this blog post hear from GSK's Scientific Lead within the Data and Computational Sciences Solutions team, Samiul Hasan on how semantic integration can be made to ultimately become part of an integrated learning framework for more informed scientific decision making.Read
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