Artificial intelligence (AI) software developer Sophia Genetics plans to highlight results from its multimodal DEEP-Lung-IV clinical study at the 2022 American Society of Clinical Oncology (ASCO) annual meeting in Chicago.
The study is testing the company's Sophia DDM platform for assessing the response of lung cancer patients to immunotherapy through tracking multimodal signatures. Sophia DDM offers data visualization, cohorting, and predictive tools, the company said. The study includes 19 sites in seven countries; to date, 500 patients have been recruited to participate.
The company has also inked an agreement with GE Healthcare to use that firm's Imaging Fabric Core and Imaging Fabric Annotation template, both of which are part of GE's Edison Digital Health platform. Sophia will use GE's Imaging Fabric services in the DEEP-Lung-IV study for medical imaging and annotation, it said.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
