Build · AWS
Ran an 80,000+ vCPU job, finishing a workload 33% ahead of schedule
Ran an 80,000+ vCPU job, finishing a workload 33% ahead of schedule
AWS is Amazon's cloud platform, used across pharma for genomics compute, SageMaker/Bedrock model training, and healthcare-and-life-sciences-specific services like Amazon HealthOmics.
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.
Source
Published by AWS on its own site — read the original case study on aws.amazon.com ↗
Note: 404 not found — the URL no longer serves a 23andMe case study; it redirects/resolves to AWS's generic Customer Success Stories hub page with no 23andMe-specific content.
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- 01Sanofi Accelerates Drug Discovery with AI on AWS
- 02Key Takeaways from Gilead's Innovation Talk at re:Invent 2023
- 03AWS Life Sciences Symposium 2025 | Development Assistants at AstraZeneca
- 04Cloud-based genomics-sequencing data processing at scale
- 05Roche Accelerates Personalized Healthcare R&D While Reducing Costs Using AWS HealthOmics
- 06AWS re:Invent 2023 - Customer Keynote Pfizer