Champions Oncology Scales Multi-Omics Analysis with Seqera to Accelerate Cancer Therapy Development

Aim

Streamline cancer therapy development and precision oncology to enable biomarker discovery, drug response profiling, and faster, more rigorous clinical insights.

Challenges

The Data and Bioinformatics team at Champions Oncology faced complex challenges compounded by limited resources. This small team was responsible for supporting numerous assays and cancer types, leaving little capacity for deep optimization or innovation. Many pipelines ran on outdated infrastructure with limited version control and documentation, hindering reproducibility and troubleshooting ability at scale. Efforts to customize workflows often conflicted with the need for standardization and automation. At the same time, high compute costs and noisy, rare datasets added further strain (especially without well-optimized cloud workflows) creating a high-pressure environment where solving one problem often meant delaying another.

Before Nextflow and Seqera, Champions Oncology relied on incremental, issue-specific fixes driven by limited staff, legacy systems, and low automation. Many of these pipelines were outdated, difficult to update, and lacked modularity and version control. Workflows were not optimized for speed or cost, resulting in long runtimes and inefficient scaling. Manual intervention was common, increasing the risk of errors and delaying delivery. With little capacity for strategic development, the team operated reactively: addressing immediate problems while accumulating technical debt. The result was a fragile, high-maintenance system that hindered long-term innovation. Champions Oncology needed a scalable, reproducible solution that would modernize their workflow infrastructure, reduce manual burden, and enable long-term innovation through automation, standardization, and efficient resource use.

Solution

• Nextflow: Enabled modular, containerized pipelines with full reproducibility and scalability, laying the foundation for automation and efficient cloud execution.
• nf-core: Shift from custom to open-source pipelines for better reliability, transparency, and efficiency across WES, RNA-seq, and proteomics.
• Seqera: Unified platform to automate end-to-end processing, manage cloud compute and storage, reduce costs, and deliver reproducible, high-quality data faster.
• Fusion: To minimize I/O overhead and eliminate unnecessary data movement, for breakthrough pipeline performance and cost-efficiency.
• AI/ML tools: Simplify data access and build custom models for drug response and biomarker discovery.

Results

With Seqera, Champions Oncology were able to transform their workflow infrastructure by modernizing legacy pipelines, optimizing compute environments, and automating large-scale data analysis. As a result, they reduced RNA-seq compute costs by 81% and WES costs by 55%, while cutting turnaround time from days to hours. Additionally, centralized run tracking improved reproducibility and traceability, and greater automation freed the team to focus on higher-impact work. The result was a scalable, efficient, and future-ready data platform with sustainable strategies for pipeline updates and long-term data maintenance.