Research highlights the use of multimodal machine learning to identify non-small cell lung cancer patients predicted to derive the most benefit from combination immunotherapy
BOSTON and ROLLE, Switzerland, Sept. 14, 2024 /PRNewswire/ — SOPHiA GENETICS (Nasdaq: SOPH), a cloud-native healthcare technology company and a leader in data-driven medicine, will unveil new research at the European Society for Medical Oncology (ESMO) 2024. The study, conducted in collaboration with AstraZeneca, leverages advanced AI-driven techniques to identify subgroups of stage IV non-small cell lung cancer (NSCLC) patients who could most benefit from the addition of tremelimumab to durvalumab and chemotherapy.
The research is a retrospective, multimodal analysis of the POSEIDON Phase 3 clinical trial (NCT03164616). This trial originally demonstrated that the combination of tremelimumab, durvalumab, and chemotherapy significantly increases progression-free survival (PFS) and overall survival (OS) versus chemotherapy in patients with metastatic NSCLC, which lead to approval of this regiment globally in 1L mNSCLC. The SOPHiA GENETICS study used cutting-edge multimodal machine learning models to analyze clinical, biological, genomic, and imaging data, pinpointing patient subgroups who are most likely to benefit from the combination treatment.
The research highlighted signatures identifying patients with non-squamous metastatic NSCLC who may derive higher OS benefit from the addition of tremelimumab to durvalumab plus chemotherapy in the first-line treatment setting. In particular, EGFR wild-type, FGFR3 wild-type, CDKN2A wild-type, KRAS mutation, and STK11 mutation comprised elements of a signature was identified as being associated with a higher OS benefit. These findings could have significant implications for the treatment of NSCLC, as it provides an exploration avenue towards a more tailored approach to patient care.
“Our collaboration with AstraZeneca represents a major step forward in personalized oncology. Non-small cell lung cancer remains one of the most challenging cancers to treat due to its complex biology and the late stage at which it is often diagnosed,” said Jurgi Camblong, Ph.D., Co-founder and CEO of SOPHiA GENETICS. “This study harnesses the power of multimodal data and advanced AI to identify which patients are most likely to benefit from specific therapies. By tailoring treatment strategies based on a patient’s unique multimodal profile, we aim to improve outcomes and offer new hope to those battling this difficult disease.”
The study will be presented as a poster by Ferdinandos Skoulidis, Department of Thoracic Medical Oncology, University of Texas MD Anderson Cancer Center at ESMO 2024 hosted in Barcelona, Spain from September 13-17, 2024. His presentation showcases the operational feasibility and clinical impact of large-scale multimodal analyses in identifying heterogeneous treatment effects in oncology.
For more information on SOPHiA GENETICS, visit SOPHiAGENETICS.COM, or connect on LinkedIn.
About SOPHiA GENETICS
SOPHiA GENETICS (Nasdaq: SOPH) is a cloud-native healthcare technology company on a mission to expand access to data-driven medicine by using AI to deliver world-class care to patients with cancer and rare disorders across the globe. It is the creator of the SOPHiA DDM™ Platform, which analyzes complex genomic and multimodal data and generates real-time, actionable insights for a broad global network of hospital, laboratory, and biopharma institutions. For more information, visit SOPHiAGENETICS.COM and connect with us on LinkedIn.
SOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures unless specified otherwise. The information in this press release is about products that may or may not be available in different countries and, if applicable, may or may not have received approval or market clearance by a governmental regulatory body for different indications for use. Please contact [email protected] to obtain the appropriate product information for your country of residence.
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SOURCE SOPHiA GENETICS
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