TetraScience announces 5-year, $500 million investment in the ongoing development and delivery of the world’s only cloud-native, open, and purpose-built scientific data cloud as it lays the foundation for revolutionary AI- and ML-based discovery
In response to overwhelming customer demand, TetraScience announced the evolution of its industry leading data cloud to include manufacturing and quality control (QC) data as it seeks to relentlessly replatform and reengineer the world’s scientific data in its cloud to radically accelerate and improve scientific outcomes. The Tetra Scientific Data Cloud™, already deployed in 10 of the top 20 pharma companies, helps customers solve previously intractable scientific data problems at scale.
BioPharma organizations have attempted to unlock the full value of their scientific data for decades in order to decrease time-to-market, glean scientific insights, and gain operational efficiencies. However, legacy systems, manual processes, incomplete cloud solutions, proprietary data formats, have contributed to inflexible point-to-point integrations to thousands of primary sources and millions of data silos. Having both upstream Research and Development (R&D) and downstream manufacturing and QC data available in the Scientific Data Cloud will yield long sought-after breakthroughs including new process development efficiencies, analytical control strategy, technology transfer acceleration, and reduction of manufacturing risk.
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The Tetra Scientific Data Cloud systematically solves these problems across the BioPharma ecosystem, accelerating drug delivery while improving quality controls and data integrity. It comprises productized API-based integrations from the Tetra Partner Network, the open, cloud-native Tetra Data Platform which re-engineers raw or primary data into FAIR, harmonized “Tetra Data (™),” and use case-based Scientific Applications enriched by Tetra Data and the Tetra Partner Network. The Tetra Data Platform runs natively on Amazon Web Services (AWS) and is available as a SaaS solution in AWS Marketplace.
These new classes of scientific applications, built on the Tetra Data Platform in conjunction with Tetra Partners, reduce time-to-value by addressing the challenges of specific scientific lab operations and workflows. Examples include data flow automation in high throughput screening and batch release and stability testing. In addition, for customer use cases in manufacturing and quality control , Tetra GxP ensures the capture of data provenance through a comprehensive audit trail, disaster recovery, control matrices, and software hazard analysis.
In addition to its unparalleled cloud capabilities and deep scientific data knowledge, TetraScience’s market position as the “Switzerland of Scientific Data” – namely, not seeking to compete with our instrument manufacturer, ELN, and informatics partners – uniquely engenders trust among all industry and adds value to their core offerings. With the world’s scientific data trapped in millions of data silos, it’s essential that TetraScience remains open and agnostic to data sources and endpoints and focused on one goal – maximizing the value of the data for all relevant stakeholders.
“By engineering and automating data flow in late stage biopharma labs, Tetrascience and our Tetra Network Partners have already transformed how safer, better products can be manufactured more efficiently. In fact, meaningful decisions are already being made using Tetra Data-powered data science in QA/QC labs across the globe. Increasingly, Tetra Data (™) is now being requested for reactors, bioanalyzers and other manufacturing equipment for the game-changing therapies of tomorrow,” said Spin Wang, TetraScience CTO.
“As CRISPR advances our mission to develop transformative gene-based medicines for serious human diseases, it’s critical that our advanced analytics are able to leverage as much scientific data as possible coming from a wide range of instruments and informatics systems.,” said Julian Fowler, VP, Head of Information Technology at CRISPR Therapeutics. “TetraScience has brought us value in this area already, and we’re very pleased to see the company further evolve their capabilities to better support an expanded set of use cases in QA and manufacturing via the Scientific Data Cloud.”
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“The Tetra Scientific Data Cloud is a one-of-a-kind, purpose-built industry data cloud optimized to accelerate and improve scientific outcomes. We’re closely collaborating with the world’s most innovative BioPharma companies, scientific vendors, leading technology companies – such as AWS, and top global systems integrators – such as Deloitte, to fundamentally transform customer outcomes,” said Patrick Grady, TetraScience Chairman and CEO.
“TetraScience’s cloud-native platform, built on AWS, coupled with its partner network and deep scientific knowledge, allows it to securely and compliantly assemble and engineer some of the world’s largest scientific data sets,” said Lita Sands, Worldwide Life Sciences Strategic Solutions Leader at Amazon Web Services (AWS). TetraScience’s data engineering and harmonization at enterprise scale delivers the underlying data that enables advanced analytics and new artificial intelligence-based capabilities. This leads to accelerated and improved outcomes including increased business agility, reduced costs, improved productivity, and faster time-to-market.”
“We’ve seen first-hand the pains and challenges biopharmas experience around fragmented, siloed scientific data trapped in legacy systems,” said Laks Pernenkil, Principal, Life Sciences at Deloitte. “Digital innovation in the life sciences space is at an inflection point, and what TetraScience is doing to help organizations leverage the full value of scientific data will play an important role in transforming the value stream across drug discovery and development, QA, manufacturing, and supply chain.”
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