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Largest AI-Powered Medical Research Network Launched

By HospiMedica International staff writers
Posted on 27 Dec 2018
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The newly launched OWKIN (New York, NY, USA) Loop Network, which includes over 30 leading international hospitals and research institutions across the United States and Europe, has been designed to help researchers train predictive models on real-world data at scale, and transfer the accrued knowledge to a collective intelligence. Members include Cleveland Clinic (OH, USA), Mount Sinai (New York, NY, USA), and Groupe AP-HP, a cluster of 39 hospitals in France, among others.

The Loop Network thus creates an ecosystem that shares the collective knowledge, benefitting research organizations, partner hospitals, and pharmaceutical companies in advancing research and development in oncology, cardiovascular, neurodegenerative, and autoimmune diseases. Projects undertaken by the network include the training of a predictive model identifying new quantitative biomarkers associated with prognosis in a rare cancer, the prediction of brain age from magnetic resonance imaging (MRI), and prediction of gene expression profiles from slide images as a marker of response to immunotherapy.

“Access to patient data is critical for improving medical research, but the current patient data brokerage system hinders knowledge-sharing and risks patient data privacy, resulting in knowledge silos at individual hospitals,” said Thomas Clozel, MD, co-founder and CEO of OWKIN. “If we can transform the world’s clinical data into broadly accessible research knowledge, we believe we can fundamentally advance medical research and have an incredibly powerful impact on solving the most important medical challenges.”

“We are excited to be working with OWKIN to apply AI algorithms to clinical data for mesothelioma research,” said Françoise Galateau-Sallé, MD, principal investigator at Centre Léon Bérard (Lyon, France). “AI models identified a new subgroup of patients that are poor responders to the standard of care and potential good candidates for immunotherapy.”

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