November 23, 2021 – Flying, a cloud-scale computing platform for biomedical research and collaboration, announced the successful integration of its platform into Roche and Genentech, a member of the Roche group, for the ingestion, classification, standardization, preservation and analysis of medical imaging data.

The secure and scalable Flywheel platform enables aggregation and management of medical imaging and associated data to accelerate drug discovery. Data is organized and processed with automated pipelines, saving considerable time and minimizing the risk of human error in the drug development process. Cost and time efficiency allows researchers to focus on what matters most: delivering life-changing therapies faster. In addition, Flywheel’s unique approach enabled multi-site collaboration and the development of a customized solution for Roche and Genentech’s needs.

“Manual data retention processes at the terabyte and petabyte level are historically expensive, time consuming and prone to human error. With our platform in place, researchers at Roche and Genentech can access high-quality images for complex analysis and machine learning, thereby accelerating the development of innovative therapies, ”said Jim Olson, CEO of Flywheel. “Before using the platform, this level of collaboration and analysis just wasn’t possible. “

“At Roche, we envision a future where data, analytics and digital technologies will systematically enable more focused and efficient research and development and more integrated and personalized care,” said James Sabry, director of Roche Pharma Partnering. “The Flywheel platform enables rapid access to highly organized imaging data, improving our ability to answer key scientific questions that are critical to improving patient care experiences and outcomes. “

Life science organizations are investing heavily in digital transformations that drive AI technology in hopes of improving R&D processes and getting drugs to market faster. Modern infrastructure is needed to aggregate, organize and analyze a vast assortment of rich biomedical data to support these initiatives and enable machine learning, big data analysis and other data-driven strategic goals.

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