On AWS you can build and run data applications that are retrospective, real-time or predictive to accelerate the journey from genomic data to genomic insight. Reduce data processing times from week to hours and obtain early insights into diseases such as cancer, cystic fibrosis, and Alzheimer’s. Learn how AWS customers like AstraZeneca and Fred Hutchinson are lowering time-to-results, and running their genomics workloads at scale on AWS.

Whether you are running compute-intensive, FPGA, or GPU-accelerate based applications, you can find the right compute platform with Amazon EC2. If you are running compute intensive applications, read this blog to learn how you can significantly lower costs with AWS Graviton2. You can also use AWS Batch to orchestrate batch workloads and work with the any workflow language such as Nextflow, DRAGEN, Cromwell, and NVIDIA Clara Parabricks to run your analysis. AWS Open Data Program houses openly available datasets, with 40+ open life sciences and genomics datasets to enable frictionless collaboration, providing research and clinical communities with a single documented source of truth.

AWS brings the broadest and deepest set of instance types, scalable storage solutions, and advanced machine learning and data integration services to meet imaging workload requirements. On AWS you can elevate image analysis and facilitate long-term data retention. HPC on AWS enables workloads including basic research, data transfer, instrument integration, diagnostic medical imaging, high content screening, digital pathology, MRI, PET, X-Ray, and CT scans. Learn how AMBRA Health expanded its medical imaging platform on AWS, and how UC San Diego leveraged AWS’ HIPAA secure environment to deploy machine learning based algorithms to X-Ray images.

Take advantage of graphics-optimized G4 Amazon EC2 instances, to facilitate medical image rendering in real-time. With AWS DataSync you can quickly transfer data for storage or processing between on-premises or cloud storage solutions or remotely stream from your on-premises workstation using the Amazon DCV remote streaming protocol. You can improve identification and pattern classification in medical images with the machine-learning capabilities of AWS SageMaker.