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ASCO 2024 | Predicting ICI response in NSCLC with a deep learning radiomic biomarker
Ravi Bharat Parikh, MD, MPP, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, gives an overview of the development and validation of a CT imaging-based deep learning radiomic biomarker for predicting response to immune checkpoint inhibitors (ICI) in patients with advanced non-small cell lung cancer (NSCLC). Using various datasets, including a real-world dataset and a clinical trial (NCT02573259) assessing sasanlimab, the biomarker shows potential for guiding clinical decisions and identifying patients who might benefit most from ICI therapy. The novel biomarker may also be an alternative to existing biomarkers such as PD-(L)1. This interview took place during the 2024 American Society of Clinical Oncology (ASCO) Meeting in Chicago, IL.
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Disclosures
Stock and Other Ownership Interests – GNS Healthcare; Google; Merck; Onc.AI; Thyme Care
Honoraria – Wake Forest School of Medicine
Consulting or Advisory Role – Archetype Therapeutics; Biofourmis; ConcertAI; Credit Suisse; G1 Therapeutics; Humana; Merck; NanOlogy; Thyme Care
Research Funding – Emerson Collective; Humana; Mendel AI; Prostate Cancer Foundation
Patents, Royalties, Other Intellectual Property – Technology to integrate patient-reported outcomes into electronic health record algorithms
Travel, Accommodations, Expenses – The Oncology Institute of Hope and Innovation
