Unlock Discovery with Harmonized Data in the Cloud
Scientific innovation in today’s biopharmaceutical companies relies heavily on their ability to effectively manage big data across their organization, globally. The trend towards outsourcing vast amounts of work to contract research organizations (CRO’s) has become an integral part of the drug discovery and development cycle. While outsourcing can significantly reduce the R&D lifecycle of a new therapeutic, the reach of data management now must also extend to third parties, adding complexity to an already arduous task.
Upcoming Webcast with TetraScience:
“Overcoming Lab Data Inertia: Learnings from a Decade at the Bench”
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- Date: July 22nd 1:00 EST
- Presenter: Joel Melby, Life Sciences Data Analyst, TetraScience
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The challenges surrounding big data management are common across the biopharmaceutical industry: siloed data preventing the flow of information, manual processes limiting productivity, error-prone data transcription, and heterogeneous data formats, all rendering valuable R&D data inaccessible and not re-usable. Due to the varied scope of work being conducted and the breadth of laboratory instrumentation and systems throughout their digital landscape, it is not surprising that a siloed and fragmented ecosystem exists in most biopharma organizations, creating an enormous roadblock to scientific innovation.
Solving the Big Data Challenge
The digital lab is powered by free-flowing, harmonized data across the global reach of biopharma organizations. Data-centric enabling technologies such as artificial intelligence (AI) and machine learning (ML) require accessible, clean, and harmonized data to provide accurate predictive models to accelerate R&D.
Point to point integrations, which are the current standard for lab connectivity, do not facilitate a fully digitized lab environment. They create islands of disconnected data lakes, are highly customized and/or difficult to maintain, and prevent the free flow of R&D data necessary for advanced analytics. Many commercially available out of the box ‘solutions’ only focus on automated and centralized data collection, which does not address the critical issue of data harmonization.
TetraScience’s cloud platform provides the central hub that enables the free flow of harmonized digital data across all systems and workflows surrounding your R&D lifecycle. The Tetra R&D Data Cloud combines the industry’s only cloud-native data platform built for global biopharma companies with a diverse array of connections to common R&D data systems and informatics. Lab connectivity is achieved through an open, configurable, API-driven and vendor-agnostic data cloud which allows you to connect to existing heterogeneous and best-of-breed data solutions while re-platforming to the cloud.
TetraScience Platform Integrations with Data Targets
Leveraging the power of AWS, the Tetra R&D Data Cloud engages with a wide array of laboratory systems via the TetraScience connector library to move source data over to the cloud and into the Tetra data lake, where it becomes centralized but not yet harmonized. The data pipeline is then converted into a standardized data format by the Intermediate Data Schema (IDS) and prepared for transfer to your laboratory’s ecosystem of downstream applications. This approach solves all of the big data challeges faced by biopharma organizations to provide automated, centralized and harmonized data essential for advanced analytics.
Summary
TetraScience provides biopharma companies with the flexibility, scalability, and data-centric capabilities to easily access centralized, standardized, and actionable scientific data. As an open platform, TetraScience has built the largest integration network of lab instruments, informatics applications, CRO/CDMOs, analytics, visualization, and data science partners, creating seamless interoperability and an innovation feedback loop that will accelerate discovery by empowering digital transformation to drive the future of biopharma R&D.
Why it Matters for You
The digital lab landscape of today’s global biopharma organizations is largely comprised of siloed and fragmented data that hinders gaining actionable insights quickly and efficiently. These common challenges with big data can be solved in the following ways to achieve operational excellence across all scientific laboratories operating across your R&D lifecycle:
- Harmonizing data across the global reach of your biopharma organization will allow for the free flow of data that powers the digital laboratory and drives AI/ML technologies to accelerate R&D.
- Deploying a data management platform with a scalable cloud infrastructure and resilient universal connectivity provides automated, centralized and harmonized data essential for advanced analytics.
- Implementing the Tetra R&D Data Cloud allow you to manage R&D data as your core asset, enabling advanced data-centric capabilities to automate the full life cycle of R&D data. TetraScience’s open, API-driven, vendor-agnostic platform provides the freedom of choice to connect existing heterogeneous systems and best-of-breed data solutions, while re-platforming to the cloud.
About Astrix
Astrix partners with many of the industry leaders in the informatics space to offer state of the art solutions for all of your laboratory informatics needs. With over 25 years of industry proven experience, Astrix has the informatics specialists and business process analysis tools required to develop and implement the solution that works best for your enterprise. Our domain experts have helped hundreds of companies globally effectively navigate their digital transformation journey, connecting people, processes and systems to accelerate the advancement of science and medicine.
