How Takeda Pharmaceuticals Accelerates Large-Scale Bioinformatics with AWS HealthOmics

This article discusses how Takeda Pharmaceuticals accelerated large-scale bioinformatics analysis by migrating their Nextflow pipelines from on-premises Slurm clusters to AWS HealthOmics.

Specifically, the article covers:

• The opportunity to scale up analysis of 20,000 RNA sequencing samples for cancer biomarker research, reducing analysis time from 6 weeks to 2 days.
• The solution architecture using HealthOmics workflows, Amazon ECR for containerized tools, and AWS CloudWatch Logs for data provenance.
• Key considerations for tooling/data governance, reproducibility, debugging, testing, and optimizing workflows on HealthOmics.
• The cost savings of over 70% achieved by using HealthOmics and optimizing compute resources.
• Takeda's plans to scale HealthOmics across other therapeutic areas and enhance CI/CD integration.