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GE Healthcare and SOPHiA Genetics on Tuesday announced collaboration plans aimed at better targeting and matching cancer treatments to each patient's genomic profile and disease type so that they can receive the "most effective and personalised" care. The tie-up involves combining data from GE Healthcare's Edison platform and SOPHiA's DDM cloud-based platform in order to create artificial intelligence (AI)-based analytics and workflow solutions for the clinical and biopharma markets.
Jan Makela, who heads imaging at GE Healthcare, suggested that integrating genomics-based AI into oncology workflow solutions would be "a major breakthrough" for integrated cancer medicine and future clinical research. Meanwhile, Jurgi Camblong, chief executive at SOPHiA, predicts the partnership will help patients with cancer "receive equal access to better diagnoses and treatments through secure data-pooling and knowledge-sharing, unlocking the promise of data-driven medicine at scale."
Specifically, the companies said they will deploy GE Healthcare's medical imaging and monitoring capabilities, and Edison platform-enabled data aggregation, with SOPHiA's DDM "software-as-a-service" analytics genomic insights platform and related solutions, which are available in more than 750 hospitals, laboratories and biopharma companies.
SOPHiA's platform uses AI and machine learning to generate actionable insights from complex multimodal datasets, while GE Healthcare is utilising Edison to integrate data from diverse sources, such as electronic health records and radiology information systems, imaging and other medical device data. Bringing them together will "break down the data silos…that so often delay or even prevent patients from getting the most appropriate treatment," the companies said, adding that the AI tools they want to develop will help "simplify oncology patient workflows, better understand increasingly complicated clinical patient data, and compare data from patient to patient."
In March, SOPHiA entered into a partnership with Hitachi to use multimodal health data in order to advance data-driven precision medicine.
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