Overview
ESI helped NCI tackle a major challenge in comparative oncology: fragmented, inconsistent data sets that limited researchers’ ability to draw meaningful insights. Through the development of the Integrated Canine Data Commons (ICDC), we consolidated and standardized access to spontaneously occurring canine cancer data to enable researchers to explore connections between canine and human cancers.
The Challenge
NCI-supported comparative oncology researchers required a centralized location to store and analyze data on spontaneously occurring cancers in dogs. These data sets are not only vital for canine patients suffering from cancer, but also for uncovering connections to human cancers. Dogs and humans share many similarities in their biology including types of cancer. Combining data from canine and human cancer patients could accelerate drug development and treatment.
However, with data sets scattered across various sources, researchers found it challenging to access and use the data effectively. Without a unified platform, researchers were unable to collaborate efficiently, compare findings across studies, or maximize the impact of their work.
The Solution
ESI developed the ICDC, a cloud-based platform designed to aggregate, standardize, and simplify access to canine cancer data for researchers. Built on Amazon Web Services (AWS), the ICDC combines scalable computing, advanced search capabilities, and secure data storage to deliver a powerful, centralized resource for the comparative oncology community.
The platform uses Amazon EC2 and runs Red Hat Enterprise Linux to provide reliable computational resources for data processing and analysis. Amazon Simple Storage Service was employed to securely store large volumes of data while ensuring scalability to accommodate the growing repository of canine cancer datasets. Amazon Elastic Container Registry facilitated the deployment and scaling of bioinformatics tools, enabling researchers to perform complex analyses seamlessly. To address the need for data harmonization, ESI implemented workflows that aggregated information from multiple canine cancer research programs and transformed it into a unified data model.
This standardization ensured consistency and reliability across the repository, providing researchers with a dependable foundation for their studies. Furthermore, we implemented advanced search functionality with Amazon OpenSearch Service, enabling users to intuitively explore data sets and identify relevant information efficiently.
As a cloud-based system, the ICDC also integrated with the NCI’s Cancer Research Data Commons, connecting researchers to resources and tools that supported bioinformatics analysis and human cancer data. This integration enabled researchers to build cohorts and analyze data in ways that bridged canine and human oncology, advancing understanding in both fields.
The Results
By creating a centralized and harmonized platform, ESI eliminated the inefficiencies of fragmented data sources and enabled researchers to focus on discovery and innovation. The ICDC contributed to ongoing comparative oncology efforts and showcased ESI’s ability to build custom, cloud-based tools for scientific work.
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