Azure high-performance computing for health and life sciences

Accelerate insights in genomics, precision medicine, and clinical trials with near-infinite high-performance bioinformatics infrastructure.

Gain deeper insights from medical data by deploying analytics and machine learning tools on top of simulation data.

Health and life sciences HPC scenarios

Genomic analysis

Overcome the challenges of scale, collaboration, and compliance —while minimizing cost and complexity— by using Azure for genomic computation. Take advantage of industry-leading privacy, local compliance, and performance capabilities.

Molecular dynamics

Increase the accuracy of mathematical formulas used in simulated atom and particle movement analysis with vast compute resources from Azure —the first public cloud to scale a molecular dynamics code, CP2K, to 20,000 cores.

Proteomics scientists use Azure to do the heavy lifting of sharing peptide data.

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Clinical trial simulation

Improve the efficiency of drug development process with power and scale for computationally intensive stochastic modeling and simulation workloads, such as population pharmacokinetic and pharmacokinetic-pharmacodynamic modeling.

Medical imaging

Gain deeper insights from all of your medical data with big data analytics and machine learning capabilities from Azure.

Powerful infrastructure as a service (IaaS) for health and life sciences

  • Create, manage, and optimize HPC clusters using tools of your choice, such as Platform Load Sharing Facility (LSF), with Azure CycleCloud.
  • Run large-scale, perfectly parallel batch jobs efficiently with Azure Batch.
  • Encapsulate your processes and run containers to elastically provision additional compute capacity for your genomics applications with Azure Kubernetes Service (AKS).
  • Optimize your application workflows to benefit from both on and off premises storage resources without rearchitecting applications requiring file access with Azure HPC CachePREVIEW.
  • Get deeper insights from your simulation data, build intelligent solutions, spin up clusters, and build quickly in a fully managed, global-scale Apache Spark environment with Azure Databricks.
  • Take advantage of scalable, cost-effective, and HDFS-compatible storage that’s optimized for big data workloads with Azure Data Lake Storage.

Learn how life sciences customers are innovating with Azure HPC

"When we wanted to scale up our research and attack those problems with much more sophisticated tools, we were looking for trusted partners and that's where we got in touch with Microsoft, who not only provided the technologies to enable our research but also the level of support that we needed."

Dr. Benjamin Haibe-Kains, Senior Scientist, Princess Margaret Cancer Centre, University Health Network

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University Health Network

"Our project simply would not be possible without the Microsoft partnership, and I think that the cloud computing infrastructure, Microsoft Azure's platform, has allowed us to make progress at a rate that we wouldn't have been able to do otherwise, and so it's been an essential component of our research progress."

Dr. Sohrab Shah, Senior Scientist, BC Cancer

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BC Cancer

"In Azure, we're 15 minutes from wanting new nodes to expanding the cluster to run larger simulations—and then paring them down when we're done."

Andy Lee, Cofounder and Chief Technology Officer, NeuroInitiative

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NeuroInitiative

"When it comes to AI, we don't want to reinvent the wheel. We harness Microsoft Azure AI research and technologies, Microsoft Cognitive Services, and Microsoft Cognitive Toolkit to develop our platform. We don't believe that small-scale startups will be the companies that define AI at the foundational level. It's the big innovators like Microsoft that will clear the AI path for small companies like Eagle Genomics to follow."

Anthony Finbow, Chief Executive Officer, Eagle Genomics

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Eagle Genomics

"I give [the Microsoft Genomics service] the input data that would come from the sequencers. It can uniformly realign everything and let me do the variant calling for the analysis I want."

Dr. Robert Klein, Klein Lab, Icahn School of Medicine at Mount Sinai

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Icahn School of Medicine

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