SciBite, a semantic AI company headquartered in Cambridge UK, has been acquired for an undisclosed sum by global research publishing and information analytics provider Elsevier.
A recent Queen’s Award winner, SciBite is based in the Wellcome Trust Sanger Institute Morgan Building and provides an enterprise-ready semantic software infrastructure to standardise and transform scientific information silos into clean, interoperable data.
Globally influential, the technology business supports the top 20 pharma companies with use cases across life sciences.
Elsevier, part of UK power player RELX, has acquired the Cambridge innovator to help customers make faster, more effective R & D decisions through advanced text and data intelligence solutions.
SciBite’s solutions identify and extract scientific insights from both structured and unstructured text and content, to identify key concepts such as drugs, proteins, companies, targets, and outcomes.
This semantically-enriched, machine-readable data, helps SciBite’s customers around the world make streamlined, more efficient decisions. SciBite was founded in 2011 by Dr Lee Harland, who currently serves as chief scientific officer.
SciBite’s major products include: TERMite, an AI and ontology driven text analysis engine; DOCstore, which transforms search through semantic indexing; and CENtree, a next-generation collaborative ontology management platform; they are complemented by a suite of apps that support its core technology and allow customers to automate data-curation and manage terminology standards.
Dr Harland said: “I am incredibly proud of everyone at SciBite; we believe that our continued investment in innovative technology enables our customers to address the huge challenges they face in creating, connecting and analysing disparate content and data.
“Our track record in driving new insights and efficiencies within drug discovery and the wider life sciences is something we will continue to build upon in this next phase of our journey.”
Rob Greenwood, CEO and President of SciBite, added: “This is an exciting next step for our business. The combined offering of Elsevier’s high-quality content and data and the innovative technology from SciBite will deliver amazing value for any data led strategy across the scientific community.
“As part of the Elsevier organisation, SciBite will have the ability to deliver enterprise technology, and new advances in scientific insight and discovery across its broad reaching global customer base.”
Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. To support this, Elsevier’s Life Sciences Solutions division is transforming from a provider of reference solutions into a creator of data and information analytics capable of supporting multiple scientific domain-specific use cases, ranging from search and discovery through to machine learning and AI.
SciBite’s proven and award-winning solutions will enable Elsevier to develop its Life Sciences Solutions services, such as: Reaxys, which powers chemistry research and development; Embase, the world’s most comprehensive international database of biomedical information; and Entellect, its FAIR data compliant platform that integrates, stores, and enriches client data with Elsevier and third-party content into a common analytical environment.
Cameron Ross, managing director Life Sciences Solutions at Elsevier, said: “The life sciences and corporate R & D communities face complex challenges, with an ever-expanding sea of data and content to extract knowledge from.
“We aim to combine Elsevier’s expertise and content from existing products, with SciBite’s impressive capabilities and suite of ontology-led products, to support more customers around the world make data led decisions in the drug development process.”
Leading life science and technology law firm Taylor Wessing advised on the acquisition; its team included Ross McNaughton, Adrian Toutoungi and Charlie Adams – all based in Cambridge.
from Business Weekly https://ift.tt/3aXTNyw