TetraScience, a cloud-native and open R&D Data Cloud for scientific discovery, announced that its flagship product, the Tetra R&D Data Cloud, is now available as a SaaS solution in AWS Marketplace in the Lifesciences category. TetraScience is an AWS Independent Software Vendor (ISV) Partner and the R&D Data Cloud solution is certified as reviewed by Amazon Web Services, Inc. (AWS).
“By making an industry data cloud available as a SaaS solution via AWS Marketplace, TetraScience is removing the complexity that’s inherently part of a DIY approach while enabling our customers to accelerate data science and discovery,” noted Chad Garrett, TetraScience CRO. “The global scale of AWS coupled with the life sciences domain expertise of TetraScience is a potent combination that enables enterprise pharma and biotech organizations to gain the benefits of the cloud while enjoying the competitive advantages of a data platform that’s tuned to their specific R&D workflows” Garrett continued.
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The Tetra Data Platform (TDP) runs natively on AWS and is available as a multi-tenant SaaS solution or deployed in a private AWS account. With its cloud-native architecture, TDP delivers enterprise management, scalability, and performance by leveraging AWS services including Amazon Elastic Kubernetes Service (EKS), Amazon Elasticsearch Service, AWS Lambda, and Amazon Athena.
“To meet the unique demands of the world’s research labs, TetraScience has developed three integrated capabilities – the Tetra Data Platform, Tetra Partner Network, and Tetra Solutions Team – to deliver an open R&D data cloud that’s capable of harmonizing experimental data from virtually any lab source in any location,” stated Patrick Grady, TetraScience CEO and Chairman. “The emergence of a vertical industry data cloud with its three supporting pillars – product, network, and services – signals the next wave of innovation moving beyond the horizontal data cloud technology of the past,” continued Grady.
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Global pharmas are challenged by inefficient manual transcription and siloed experimental data, and struggle to maintain rigid, costly point-to-point integrations to move data in their R&D workflows. As a result, their pace of discovery suffers from an inability to apply data science using enhanced data analytics applications and AI/ML. Many organizations attempt a “DIY” approach to building a custom data cloud based on horizontal technology. This approach is difficult to deploy in a configuration that considers requirements in cloud-native architecture, data science, and R&D experimental data.
Unlike horizontal platforms and DIY data clouds, the Tetra R&D Data Cloud is built and optimized for life sciences experimental data. Leveraging cloud-native infrastructure, it provides enterprises cloud benefits such as elasticity, scale, performance, and reliability. With data that’s harmonized and centralized in the cloud, R&D organizations can break down silos and unlock data science insights.
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