Adaptive Biotechnologies Transforms Data Stream Into New Immune Medicine Platform with Azure

Adaptive Biotechnologies had built a massive clinical immunomics database containing more than 47 billion immune receptors but lacked the computational infrastructure to fully analyze it and unlock its diagnostic potential. The company adopted Azure Virtual Machines, Machine Learning, Kubernetes Service, and Blob Storage to build a scalable immune medicine platform mapping T-cell receptors (TCRs) to disease-specific antigens. Within weeks the platform processed 500 million TCR sequences using 29 compute-years to identify COVID-19 immune signatures, identified shared T-cell signatures for Lyme disease and launched a clinical validation study within months, cut hours off lab-result pipeline processing time, and enabled simultaneous rather than sequential dataset processing. As stated in the case study: "With Azure Machine Learning, we can take a ton of data and train models to help us sort through that data in an efficient and effective way."

Microsoft Azure is Microsoft's cloud AI platform, combining Azure Machine Learning and Azure OpenAI Service — the delivery channel for a large share of pharma's enterprise GPT deployments.

This sits in the Build stage of the AI use-case lifecycle: Named examples from the foundation-model labs and platforms pharma teams use to actually construct, train and generate the model or application.