Open-source group to aid ILD care through digital imaging, ML

A group of experts conducting research in an aspect of lung disease associated with respiratory diseases such as emphysema is forming an Open Source Imaging Consortium to aid diagnosis through digital imaging and machine learning.


A group of experts conducting research in an aspect of lung disease associated with respiratory diseases such as emphysema is forming an Open Source Imaging Consortium to aid diagnosis through digital imaging and machine learning.

The international group—comprising researchers, experts and advocates in the fight against idiopathic pulmonary fibrosis, fibrosing interstitial lung diseases (ILD) and other respiratory diseases—say the organization will function as a cooperative and open-source effort between academia, industry and philanthropy to enable rapid advances in research.

OSIC's goal is to increase the efficiency and effectiveness of ILD research by bringing together radiologists, clinicians and computational scientists to develop digital imaging biomarkers for accurate imaging-based diagnosis, prognosis and prediction of therapy response.

After working together to create a rich repository of approximately 15,000 anonymized image scans and clinical data (1,500 by the end of 2019), OSIC will use machine learning to develop algorithms and then promote the incorporation of those algorithms into commercial analysis tools.

"OSIC was created on behalf of the countless patients around the world living with idiopathic pulmonary fibrosis and other largely ignored lung diseases," says Elizabeth Estes, executive director of OSIC. "By bringing together the world's 'best in class' in an open source, collaborative effort, we can collectively speed diagnosis, aid prognosis and ultimately allow doctors to treat patients more efficiently and effectively."



"The current methods for identifying ILDs can be challenging,” says Kay Tetzlaff, therapeutic area head medicine, respiratory and biosimilars for Boehringer Ingelheim, one of the founding partner organizations. “By incorporating machine learning technology into the process, there is great opportunity for improvement.

"Using digital biomarkers to predict outcome and response to therapy is key to precision medicine and drug development,” she adds. “OSIC's open science model is the best approach to speed up progress and ultimately deliver benefits to radiologists, healthcare systems, pharmaceutical companies, medical technology vendors, academic institutions and, most importantly, patients."

The organization's other founding partners include Siemens Healthineers, CSL Behring and FLUIDDA, a leader in the field of functional respiratory imaging (FRI) research and development. Under the arrangement, all of OSIC's partners will work in pre-competitive areas for mutual benefit.

"OSIC is an excellent example of the way that new, high-impact solutions for patients can be developed when pharmaceutical companies, hospitals and medical technology join forces," says Christian Wolfrum, head of new business development for Siemens Healthineers. "Today, it frequently takes up to two years after symptoms first appear before a patient receives the correct diagnosis and starts the right therapy. By applying and expanding our expertise in digitalization and artificial intelligence, we can work together to significantly shorten this period."

The group is looking for additional member partners, collaborators and contributors. More information regarding commitment benefits and opportunities can be found at www.osicild.org.

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