Suppliers United States TetraScience
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TetraScience

United States
Boston
2014
Private
< $10m
11 - 50
Open website
TetraScience develops hardware and software solutions to monitor and manage research experiments and log the data in the cloud. It offers sensors to monitor temperature, humidity, acceleration, etc.; camera to view experiment or tools; electric switches; adapters to connect hardware tools that comprise syringe pumps and wave generators; and timers. TetraScience serves scientists, engineers, managers, and safety officers. It has a strategic partnership with Dotmatics. Alok Tayi, Salvatore Savo, and Siping Wang founded TetraScience on October 21, 2014. It has its headquarters in Boston in Massachusetts.
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Automated bioprocess data management
Standard data models
TetraScience produces standardized JSON files containing both metadata and results. Our data model helps automate analytics, process reporting, and develop process optimization.

Metadata tagging
Different instruments produce different data therefore, we provide metadata tagging. Tagging allows users to segment and find data quickly via query and search.

Search and consumption
Indexed JSONs are available via Elasticsearch and dedicated API. Automation into reporting and other systems is configured using specific API calls with JSON returns.
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TetraScience is a provider of Industrial IoT application infrastructure and middleware technologies.
Technologies
Application Infrastructure & Middleware
Data Exchange & Integration
Services
System Integration
TetraScience’s Technology Stack maps TetraScience’s participation in the application infrastructure and middleware IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies2
Improving Protein Purification through Data Science: A Case Study on Alexion Pharmaceuticals
Alexion Pharmaceuticals, a biopharmaceutical company, was facing several challenges in its downstream process development operations. The company was struggling with data silos as instrument vendors did not integrate with one another, leading to manual data movement. The proprietary data formats of vendors required their specific tools, which hampered third-party data standardization. Additionally, informatics leads had to manually move, update, and curate files from multiple locations. Scientists were also required to enter peak information into analytical software themselves. Furthermore, existing dashboarding tools had steep learning curves and could not manage metadata. Scientists were constantly needing to test their hypotheses and derive useful insights from heterogeneous data sources.
Driving Cost-Effective CRO Collaboration through IoT
Pharmaceutical and biotech organizations frequently collaborate with Contract Research Organizations (CROs) for absorption, distribution, metabolism, and excretion (ADME) testing of pharmacokinetics (PK) properties of drug candidates. However, most CROs use their own data formats for standard assays, which can pose data aggregation challenges to biopharma companies. The ability to harmonize data from different CRO reports is critical to scale up ADME/PK processes. The manual data workflows for pharmacokinetics and pharmacodynamics (PK/PD) studies are laborious. Scientists have to manually check the reports from CROs, which is time-consuming and prone to errors.
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