Covering Scientific & Technical AI | Thursday, January 16, 2025

TetraScience Collaborates with Microsoft to Advance Scientific AI at Scale 

BOSTON, Jan. 16, 2025 -- TetraScience announced a key new collaboration with Microsoft that aims to accelerate the adoption of scientific AI to radically improve workflows across the entire biopharmaceutical value chain: drug discovery, development, manufacturing, and quality control. This collaboration combines the power of Microsoft’s secure Azure platform with the Tetra Scientific Data and AI Cloud to empower scientific organizations with the ability to extract scientific insights from complex experimental data at an enterprise scale.

The collaboration arrives at a critical moment when pharmaceutical companies are racing to adopt AI but wrestle with unprecedented volumes of complex scientific data, much of it locked in proprietary formats and scattered across disconnected systems. Given the scope and urgency of the data challenge, the path forward for life sciences organizations is to migrate their scientific data into an open and modern technology stack purpose-built for scientific AI.

Microsoft and TetraScience deliver the four essential components of that scientific AI stack: massive computational power, advanced models, sophisticated scientific data ontologies, and deep scientific use case expertise. TetraScience is the only industry cloud purpose-built to re-platform and engineer the world’s scientific data into powerful data models and domain-specific use cases. The Microsoft Azure platform provides enterprise-grade infrastructure and serves as the computational backbone for even the most demanding scientific workloads, from real-time analytics to large-scale AI use cases.

The combined capabilities deliver immediate practical benefits to scientific organizations, seamlessly harmonizing data from hundreds of scientific instruments and vendor formats while maintaining the experimental context needed for multimodal analytics and AI model training. The best part? Scientists can focus more time and resources on science rather than dealing with data.

"The world's scientific data is trapped in millions of silos and locked in proprietary and incompatible languages," says Patrick Grady, TetraScience Chairman and CEO. "By joining forces with Microsoft, we're breaking down these silos and unlocking the full potential of scientific data to proliferate AI-driven use cases that will define the next century of scientific discovery."

"It’s not enough to have data, you have to have AI-ready data," says Elena Bonfiglioli, General Manager, Pharma, and Life Sciences, Microsoft. “Combining TetraScience’s expertise in scientific data and use cases with Microsoft’s leading AI and cloud capabilities, our joint customers will benefit from cutting-edge solutions that will empower researchers with insights for faster discovery and development cycles.”

The collaboration aims to improve processes across the biopharma value chain. In drug safety assessment, for example, scientific AI models trained on well-engineered data sets predicted IC50 values with fewer data points required, accelerating early-stage discovery by shortening screening times. At another pharma organization, scientific AI models classified cellular features and drug responses in high-throughput images far faster than humans can, accelerating the phenotype screening step critical in oncology and neurology. At a third firm, AI co-pilots automatically flagged anomalies in system audit trails, which can streamline review processes in manufacturing, quality control, and GxP environments.

The companies will engage with leading pharmaceutical organizations to demonstrate the real-world impact of liberated data with AI for scientific discovery. The combination of TetraScience solutions with Microsoft data platform capabilities has the potential to accelerate scientific workflows and make data collaboration accessible to research organizations of all sizes.

About TetraScience

TetraScience is the Scientific Data and AI Cloud with a mission to improve and extend human life radically. It is accelerating the Scientific AI revolution by designing and industrializing AI-native scientific datasets, which it brings to life in a growing suite of next-generation scientific data and lab data automation products and AI-enabled scientific use cases. For more information, visit tetrascience.com.


Source: TetraScience

AIwire