Unleash Science
What is a Sciborg? Human prodigies living at the intersection of science and data who remove friction by aligning your IT, data, and science departments. Sciborgs optimize and accelerate the transformation of your scientific data by driving high-impact use cases for scientific data workflows and unlocking the massive latent value in your scientific data. Their expertise spans between science and data and their deep knowledge and skill with TetraScience’s powerful tools.
Why is a paradigm shift happening in scientific data management and analysis?
A traditional scientific data management system (SDMS) merely stores your data, keeping it stagnant and locked up in just another data silo. This impedes its use for predictive analytics and AI. Pharmaceutical companies are realizing they have mishandled this goldmine of data, which holds the key to improving and accelerating scientific outcomes.
Derive value at every step in the scientific data and AI journey
Focus on scientific outcomes
Take a holistic approach with end-to-end data workflows that encompass collection, contextualization, and harmonization—all aimed at driving scientific outcomes.
Seamlessly access your data for analytics and AI
Construct dashboards, perform advanced analytics, and apply AI algorithms with the tools of your choice for data-driven scientific insights and decision making.
Free your scientific data from silos
See how the Tetra Scientific Data and AI Cloud automatically assembles and centralizes data from disconnected sources for easy access, sharing, collaboration, and management.
Tap into the largest library of integrations
Leverage the world’s largest, fastest-growing, purpose-built library of industrialized integrations and data schemas that covers 100% of the highest-priority instruments in top biopharmas.
The 8 Trends Redefining Scientific Data Management in Biopharma
Discover how the Tetra Scientific Data and AI Cloud provides the world’s largest, fastest-growing, purpose-built library of data integrations and data models that drive scientific outcomes.
The 15 scientific use cases illustrating the promise of AI
Scientific data is expected to exceed 30 million petabytes in 2030. Virtually every stage in the pharmaceutical value chain, from discovery to commercialization, has the potential to be transformed by AI.
How to free your scientific data from silos
See how the Tetra Scientific Data and AI Cloud automatically assembles, contextualizes, and harmonizes data, while providing essential functionality for data management.
Collect
Centralize
Contextualize
Comply
View the largest library of scientific data integrations
TetraScience hosts the world’s largest, fastest-growing, purpose-built library of industrialized integrations and data schemas. It covers 100% of the highest-priority instruments in top biopharma organizations.
SIMPLO empowers chromatography analysts to quickly and easily analyze data
See six SIMPLO dashboards, how they are used, and their benefits. See:
Advanced in silico model predicts cell line formulations faster
See how this in silico model helps reduce wet lab experiments by 88% with media formulation optimization. See how to radically accelerate high throughput screening.
An AI model significantly streamlines and improves the accuracy of in vitro testing
See how AI helped for Charles River Laboratories Hungary (SOLVO) after replatforming and engineering scientific data with an in silico model optimizing sampling and improving calculations.
Streamline batch release workflows between Signals Notebook, LabX, and Tiamo
See the seamless transfer of data through integrations and advanced data engineering while simultaneously preparing data for downstream use in analytics and AI applications.
Expect:
- 40% increase in lab productivity
- 4x reduction in error rate
- Reduction in FTEs required for QC review
- AI-native data for prediction and troubleshooting