Enhancing CBTN digital pathology processing pipeline through the use AWS cloud-based services to enable automation, parallel processing, and rapid use of AI/ML analytics

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PROJECT SUMMARY The Gabriella Miller Kids First pediatric research program is a collaborative initiative with the goal of understanding the etiology and drivers of pediatric diseases. Related efforts include (1) developing data-driven platforms, workflows and tools; (2) accelerating discovery of generic causes and shared biologic pathways within and across conditions; and (3) enabling rapid translation of scientific discoveries to personalized treatments. Through this program, some of the largest, multi-modal pediatric datasets have been generated, harmonized, and released for use by the research community. In parallel, developed software platforms have enabled streamlined, user-friendly workflows in cloud environments to empower data exploration to analysis. While this work has significantly advanced the use of integrated datasets, particularly for genomics and clinical data, related advancements for medical imaging data have been slower. In the present project, we focus on digital pathology data in research contexts and aim to enable the use of modern cloud infrastructure and processes for Kids First digital pathology slides. Specifically, we will explore, implement, optimize, and assess cloud platforms and services to reduce current challenges in data ingest and release, and preparation of digital slide images for downstream analytics. The selected cloud solutions are expected to enable workflow automation, scaling of computing resources, and full support of the entire data lifecycle. This should drastically reduce the operational and computational costs of utilizing Kids First digital pathology data across research contexts. Together, this project will bridge digital pathology data and tools with high-performance cloud workspaces to accelerate their use with advanced analytics and multi-modal integration for all Kids First pediatric data.