Accelerating Pediatric Cancer Research with a Cloud-Based Data Platform

Background

A leading non-profit organization dedicated to advancing pediatric cancer research sought to accelerate discoveries that could improve early detection and treatment for children worldwide. Founded in honor of a young cancer patient’s legacy, the organization has grown into a global movement that funds groundbreaking research, raises awareness, and supports families affected by childhood cancer. Its mission is guided by one unshakable belief: every child deserves a healthy, hopeful future.

Challenge

Over time, the organization accumulated vast amounts of research and clinical data across multiple systems. However, these datasets were fragmented, siloed, and lacked the unified structure necessary for advanced analysis. Researchers struggled to correlate critical indicators across studies—such as early symptom patterns and genetic risk factors—due to disconnected data sources and slow reporting processes. Without a centralized, scalable data environment, the organization faced limitations in collaboration, slowed time to insight, and an inability to fully harness the potential of its data for predictive modeling and early cancer detection research.

Approach

Keyrus partnered with the organization to modernize its data environment using the AWS cloud. We began with a Rapid Landing Zone (RLZ) engagement to establish a secure, scalable, and compliant AWS foundation designed to support data science and research workloads. This was followed by a full data migration initiative, where Keyrus centralized core datasets, standardized ingestion pipelines, and optimized data storage for performance and security. Once the environment was live, research teams were able to build, test, and refine data models that revealed new correlations in pediatric cancer data—such as symptom progression patterns, susceptibility indicators, and potential treatment pathways. Keyrus worked closely with researchers to ensure data accuracy, compliance with privacy standards, and adoption of modern best practices that would sustain future AI-driven research initiatives.

Key results

Benefits

The project transformed the organization’s ability to turn data into actionable insight. It established a modern, scalable AWS infrastructure that reduced manual workloads, improved reporting accuracy, and empowered data-driven decision-making across research teams. Most importantly, it gave scientists the tools and agility to accelerate life-saving discoveries in pediatric cancer research, making a tangible impact in the fight against childhood cancer.

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