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Adaptive Biotechnologies Leverages Azure for Immune Medicine Platform
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Education
- Equipment & Machinery
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Automated Disease Diagnosis
- Predictive Maintenance
Services
- Data Science Services
- Training
The Challenge
Adaptive Biotechnologies, a commercial-stage biotechnology company, has been working on harnessing the biology of the adaptive immune system to transform disease diagnosis and treatment. The company has built a proprietary immune medicine platform that decodes the genetic language of the adaptive immune system. However, the challenge was to synthesize this vast system of biology and tap into the full value of the massive clinical immunomics database generated. The company needed high-scale compute resources and machine learning capabilities to unlock the full potential of the research data. The immune system's complexity and the sheer volume of data generated by Adaptive’s dynamic clinical immunomics database, which includes more than 47 billion immune receptors, posed significant challenges.
About The Customer
Founded in 2009, Adaptive Biotechnologies is a commercial-stage biotechnology company based in Seattle, Washington. The company is focused on harnessing the inherent biology of the adaptive immune system to transform the diagnosis and treatment of disease. Adaptive Biotechnologies has built a proprietary immune medicine platform that is capable of decoding the genetic language of the adaptive immune system at scale. The company's innovative approach involves sequencing the genomes of immune cells to read the immune systems of individuals and across the population. Adaptive Biotechnologies has a dynamic clinical immunomics database that includes more than 47 billion immune receptors.
The Solution
Adaptive Biotechnologies turned to Microsoft Azure for compute, storage, and machine learning capabilities. The company adopted Azure to apply machine learning to exponentially accelerate its ability to gain novel insights from its clinical immunomics database. The platform was used for end-to-end support, from sample intake to processing, to generate the sequencing data targeted to the immune response of a particular genome. The data was then processed through an automated in-house bioinformatics pipeline running on virtual machines created using Azure Virtual Machines. Adaptive researchers used Azure Machine Learning and Azure Kubernetes Service (AKS) to train and evaluate models. The company stored its many terabytes of source and experimental data in Azure Blob storage and used virtual machines and Azure Application Gateway to provide web-based access to data and interactive research environments.
Operational Impact
Quantitative Benefit
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