SOPHiA GENETICS Provides an Update on its DEEP-Lung-IV Multimodal Clinical Study at ASCO 2022
SOPHiA GENETICS provided an update on its DEEP-Lung-IV clinical study during the 2022 ASCO Annual Meeting. The study focuses on predicting patient response to immunotherapy using multimodal data analysis. Currently, 19 sites across 7 countries have recruited over 500 patients. Early findings suggest promising potential for identifying predictive signatures for individual patients. Additionally, an agreement with GE Healthcare aims to enhance radiomics analysis workflows. Insights from this study could significantly impact precision medicine for stage IV non-small cell lung cancer.
- Study has recruited over 500 patients across 19 sites globally.
- Early findings conceptually validate the potential for multimodal signatures in predicting treatment response.
- Agreement with GE Healthcare to enhance radiomics analytics workflows.
- None.
Study leverages deep learning-enabled analysis of the aggregation of real-world multimodal data to validate predictive signatures associated with response to immunotherapy and prognosis of patients with stage IV non-small cell lung cancer
Nearly 20 participating sites activated worldwide with over 500 patients recruited to date. Early findings conceptually validate the potential for multimodal signatures to predict response to immuno-chemotherapy with promising first results
New agreement signed with GE Healthcare to utilize Imaging Fabric to further accelerate radiomics analysis workflows in the context of the study
BOSTON and LAUSANNE, Switzerland, June 6, 2022 /PRNewswire/ -- SOPHiA GENETICS (Nasdaq: SOPH), the creator of a global data pooling and knowledge sharing platform that advances data-driven medicine, provides an update on its multimodal DEEP-Lung-IV clinical study (NCT04994795) at the 2022 American Society of Clinical Oncology (ASCO) Annual Meeting. This will be discussed during the company's joint Innovation Symposium with GE Healthcare Monday, June 6th from 6:30 – 8:00 pm CDT.
Immunotherapy has revolutionized the management of metastatic non-small cell lung cancer. Despite its promise, the majority of patients fail to respond to the therapy while being exposed to potentially severe side effects. Existing biomarkers are suboptimal as they do not allow to predict which patients will benefit from the therapy. There is an urgent need to identify biomarkers that are predictive of response to immunotherapy at the individual patient level.
SOPHiA GENETICS launched the DEEP-Lung-IV clinical study to leverage its multimodal machine learning-powered analytics capabilities to identify multimodal predictive signatures of response to immunotherapy for patients with advanced lung cancer. Through its global footprint, the study is intended to maximize exposure of the machine learning algorithms to a wide range of diverse, real-world data. Insights from the DEEP-Lung-IV study will power one of the applications of the CarePath module of the SOPHiA DDMTM platform, offering advanced data visualization, cohorting, and predictive capabilities in a single solution.
To date, 19 sites across seven countries have signed up for participation in the study, including Roswell Park Comprehensive Cancer Center in New York. "I am personally very excited to join the DEEP-Lung-IV study. I see tremendous value in the multimodal machine learning-powered approach to real-world data analytics and look forward to potentially applying it to other clinical questions of high relevance in lung cancer", said Dr. Prantesh Jain, Assistant Professor of Oncology at Roswell Park Comprehensive Cancer Center. Together, these sites have already recruited over 500 patients.
Early findings are promising and conceptually validate the potential for multimodal signatures to predict response to immuno-chemotherapy at the individual patient level. First results will be discussed during SOPHiA GENETICS' joint Innovation Symposium with GE Healthcare on Monday, June 6, at 6:30 pm CDT.
"We are very excited by the strong operational traction in recruiting patients to the study, as well as the promising early findings. With its unique machine learning-powered multimodal study design and its focus on collecting very diverse real-world data from lung cancer patients around the world, we feel that the DEEP-Lung-IV study has the potential to usher a new era of precision medicine that would enable predictions at the individual patient level. We look forward to further validating our vision of building a multimodal decentralized collective intelligence, leveraging on real-world data to generate novel insights at the individual patient level," said Dr. Philippe Menu, SVP & Chief Medical Officer, SOPHiA GENETICS.
SOPHiA GENETICS has also entered into an agreement with GE Healthcare to utilize their Imaging Fabric Core and Imaging Fabric Annotation Template, as part of the Edison Digital Health Platform. In the context of the DEEP-Lung-IV clinical study, Imaging Fabric services will be used to visualize, segment, and annotate lung lesions for medical imaging visualization and annotation purposes. This allows SOPHiA GENETICS to further accelerate proprietary radiomics analytics workflows in the context of the study, in particular to move towards automatic whole-body tumor identification, segmentation, and quantification.
"We're eager to further strengthen our collaboration with SOPHiA GENETICS. The use of Imaging Fabric and the SOPHiA DDMTM Platform are key to create the world of tomorrow, in which we aim to jointly break data silos across data modalities to deliver insights to physicians to help them optimize patient treatment workflows. We look forward to seeing how the DEEP-Lung-IV study results can help improve outcomes for those diagnosed with lung cancer," said Ben Newton, MD, General Manager, GE Healthcare Oncology Solutions.
SOPHiA GENETICS' DEEP-Lung-IV clinical study aims to predict immunotherapy treatment response upon first evaluation at the individual patient level using data across multiple modalities including genomics, radiomics, clinical, and biological data. The study also aims to validate an algorithm that will allow the prediction of outcomes of the individual patient such as progression-free survival (PFS) and overall survival (OS). This predictive model will help identify patients that are likely to benefit from immunotherapy versus those that are not. It will stratify patients according to risk, helping clinicians make more informed therapeutic decisions for their patients, supporting biopharma to ensure the right patients are selected for clinical trials.
For more on the DEEP-Lung-IV clinical study, visit https://clinicaltrials.gov/ct2/show/NCT04994795.
SOPHiA GENETICS (Nasdaq: SOPH) is a health care technology company dedicated to establishing the practice of data-driven medicine as the standard of care and for life sciences research. It is the creator of the SOPHiA DDM™ Platform, a cloud-native SaaS platform capable of analyzing data and generating insights from complex multimodal data sets and different diagnostic modalities. The SOPHiA DDM™ Platform and related solutions, products and services are currently used by more than 790 hospital, laboratory, and biopharma institutions globally. For more information, visit www.sophiagenetics.com, or connect on Twitter, LinkedIn and Instagram. Where others see data, we see answers.
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