Re-IMAGinING the Pathway for Clinical Decision Making in Rare Lung Diseases: Moving Towards a United Vision
OSIC Member CSL Behring hosted a symposium during the European Respiratory Society (ERS) International Congress which included presentations from several internationally renowned experts in rare lung diseases. The panel discussed the need to improve clinical decision making to expedite disease recognition, prognostic prediction, and early treatment in interstitial lung disease (ILD) and alpha 1 antitrypsin (AAT) deficiency-related chronic obstructive pulmonary disease (COPD).
Radiologists are teaming up to gather data on IPF, a deadly lung disease, utilizing AI to more quickly diagnose and treat those who are affected.
Could a repository of anonymized CT scans and clinical information provide critical clues about rare, unclassified lung diseases? Elizabeth Estes, executive director of Open Source Imaging Consortium, and Dr. Simon Walsh, consultant radiologist and NIHR clinician scientist, sure think so.
In this episode, Elizabeth and Dr. Walsh discuss the exciting role machine learning and algorithms may play on enhancing our disease knowledge—from diagnosis and prognosis to biomarker discovery and therapy response.
Companies across a range of industries are deploying image- and video-based artificial intelligence to improve and optimize key business processes and products. The OSIC Data Repository, supported by PwC and Microsoft, is building a platform to share anonymized imaging data to help with diagnosing the disease.
The Open Source Image Consortium (OSIC) is working to democratize medicine by giving OSIC clinicians and members everywhere the ability to access and benefit from the same technology and information as those affiliated with major research centers. “If we can figure out how to drive collaboration in healthcare, we will change the paradigm,” says Executive Director Elizabeth Estes.
For decades, the healthcare industry has lacked a long list of elements necessary to understand the nature of hundreds of rare diseases — industry cohesiveness and data transparency chief amongst them. With the help of PwC and Microsoft, one pioneering group of minds may have finally found a key part of the solution: an open-source approach to medical research.
“We have a lot of smart, motivated, dedicated people together who want to see these patients have a different path. The technology is there for personalized medicine. The technology is there to make advances in rare disease,” says Elizabeth Estes, OSIC executive director.
A first-of-its-kind open source medical imaging and data repository platform is highlighting new possibilities to help improve the speed and accuracy of diagnosis and help patients, providers and researchers better manage the disease.
A large and multi-ethnic database, reported to be the first of its kind for rare lung diseases, is now compiling real-world clinical and imaging data on people with pulmonary fibrosis (PF) and other interstitial lung diseases (ILDs) from centers across the globe.