What if AI could shorten lead clone selection from five months to just one? Or cut wet lab experiments for cell culture media formulation by up to 88%? Imagine spotting out-of-spec events before they happen using real-time chromatography dashboards.
These outcomes are within reach, but today’s fragmented data management practices stand in the way. Scientists often spend more time locating and transferring data than actually analyzing it. Laboratory ecosystems, with their diverse and siloed data sources, make it difficult to generate the engineered data needed for analytics and AI.
Let’s examine the status quo and see how the Tetra Data and AI Workspace offers scientists a far better data analysis experience.
Current Challenges
Scientific data management in biopharma is currently plagued by major inefficiencies:
- Data management complexity: Manual-heavy data workflows increase the risk of errors and losing scientific context.
- Slower insights: Scientists spend roughly half their time gathering and preparing data for analysis, delaying downstream steps.
- Data silos: Moving data between instruments, file stores, and analytical platforms creates silos, obscuring data lineage and complicating traceability.
- Limited collaboration: New experimental data is often inaccessible to collaborators until analysis is complete. This limits parallel workflows and slows down collaboration.
- Inaccessible AI: Scientists lack the time, tools, and expertise to compile the large engineered datasets required for advanced analytics and AI applications.
Introducing the Tetra Data and AI Workspace
The Tetra Data and AI Workspace transforms how scientists manage and analyze their data. It co-locates automatically centralized and engineered data from the Tetra Scientific Data and AI CloudTM with cloud-based analytics and AI applications, including commercial and TetraScience-developed apps.
This solution enables scientists to easily access data, perform analyses, and automatically link results back to the original data—all within a single cloud-based environment. The results can also be sent to an electronic lab notebook (ELN) or laboratory information management system (LIMS) in just a few clicks.
Benefits
- Streamlined analytics: Data is analyzed where it’s stored, resulting in consistent data formats, clear lineage, and faster insights.
- Centralized access: A single, browser-based location for your data and tools simplifies access across your organization.
- Sessions: The workspace uses sessions to manage individual workflows, allowing users to resume, share, or search previous sessions.
- Enhanced data management: A unified framework simplifies data governance and regulatory compliance.
- Scalability and flexibility: Cloud-based resources scale to meet demand, unlike the limitations of on-premises workstations.
- Accessible AI: Scientists can leverage advanced analytics and AI through user-friendly applications—without the need for specialized training or data management skills.
Types of Applications
- Partner Apps: Modern laboratories use a variety of commercial applications, often limited to on-premises hardware. The Tetra Data and AI Workspace brings these applications to the cloud, enabling users to launch them in an ephemeral cloud environment using a bring-your-own-license model. This approach lets scientists analyze data directly on the platform, free from hardware constraints. A prime example is FlowJo in the Tetra Data and AI Workspace.
- Tetra Data Analytics Apps: TetraScience, guided by industry feedback, has developed custom analytics applications that deliver insights beyond the capabilities of off-the-shelf software. For instance, the Chromatography Insights app allows you to track column, method, and system performance across all your chromatography systems, independently of the vendor.
- Tetra Scientific AI Apps: TetraScience empowers biopharma with AI-powered custom solutions designed to accelerate scientific outcomes. For example, our Lead Clone Selection Assistant can predict the most promising lead clones in silico, enabling faster and better candidate selection.
- Build Your Own: If you have unique analytical needs, you or your team can use standard tools like Streamlit to build, deploy, and manage custom data apps directly within the Tetra Data and AI Workspace.
In Summary
The Tetra Scientific Data and AI Cloud centralizes and engineers scientific data, optimizing it for advanced analytics and AI. The Data and AI Workspace takes this a step further. Now, scientists can use both familiar and custom software in the cloud to analyze co-located data—all from a single, browser-accessible interface. The solution unlocks new scientific use cases, enabling faster and deeper insights for better scientific outcomes.
Ready to see how the Tetra Data and AI Workspace can improve your workflows? Contact us for a demo.