Case Study: PAIGE advances cancer diagnosis with Igneous

PAIGE Advances Computational Pathology for Cancer Diagnosis, Treatment, and Prevention with Igneous

The research organization PAIGE faced the challenge of managing over 8PB of high-resolution medical scan data required to train its cancer-detecting AI algorithms. Storing and protecting this massive unstructured dataset was only part of the problem; the team also needed to efficiently organize, find, and move specific data subsets for high-performance computing while meeting stringent medical privacy and security requirements. They turned to vendor Igneous and its DataProtect and DataFlow services to provide a modern data management solution.

The solution implemented by Igneous provided scalable data protection and a powerful API-based data movement engine, which integrated seamlessly with PAIGE's Pure FlashBlade and NVIDIA processing systems. This allowed researchers to quickly query for and move only the specific data subsets they needed, drastically accelerating their machine learning workflows. As a fully managed, as-a-service platform, Igneous eliminated the need for PAIGE to hire dedicated IT staff, enabling its small team of engineers and pathologists to focus entirely on their research.

Paige

Ran Godrich

Research Engineer