Multimodal data integration to advance personalized medicine in lung cancer: An overview of DLIV study

Over the last 20 years, targeted compounds have been proven effective for non-small cell lung cancer (NSCLC patients), but recent scientific breakthroughs have made immunotherapies a new pillar of cancer care. These recent advances, coupled with the avalanche of health data, have made it hard for medical professionals to identify the patient sub-groups that will benefit the most from immunotherapy, alone or in combination with chemotherapy, without experiencing significant side effects.

By using deep learning and artificial intelligence frameworks to integrate multiple biomarkers, SOPHiA GENETICS’ DEEP-Lung-IV study (NCT04994795) aims to improve the accuracy of prognosis and first-line treatment planning. Join us to discover how this study is helping medical researchers integrate different health data modalities in a meaningful way, breaking through data silos and expanding the power and reach of collective intelligence in healthcare.

As one of the Principal Investigators of the DEEP-Lung-IV Study (NCT04994795), Dr. Akerley will share his perspective on lung cancer care and his long-term vision for multimodal data integration in clinical routine.

About DEEP-Lung-IV: DEEP-Lung-IV is a multicentric observational study leveraging the power of machine learning to integrate different data modalities and understand the prognosis and treatment responses of patients diagnosed with stage IV non-small cell lung cancer.