Onc.AI to Unveil Advanced AI Radiomic Biomarker Results at 2025 ASCO Annual Meeting, Boosting Predictive Capabilities for Lung Cancer Survival

Onc.AI to Present Groundbreaking Deep Learning Radiomic Biomarker Results at the 2025 ASCO Annual Meeting CHICAGO—(BUSINESS WIRE)—Onc.AI, a leading digital health company focused on AI-driven oncology clinical management solutions, announced today that it will present new validation study results at the 2025 American Society of Clinical Oncology (ASCO) Annual Meeting, scheduled to take place from May 30 to June 3, 2025, in Chicago, Illinois. These results stem from collaborations with Pfizer, Baylor Scott & White, and the University of Rochester Medical Center. The core of Onc.AI's presentation is the Serial CTRS, an FDA-breakthrough designated deep learning radiomics model. This innovative tool assesses changes across routine CT scans over time to predict overall survival in patients with late-stage non-small cell lung cancer (NSCLC) and other solid tumors. Key findings from the collaboration include: Validation of Serial CTRS for Early Immunotherapy Response Prediction in Metastatic NSCLC: Abstract #253138 The model has shown promising results in predicting early responses to immunotherapy in metastatic NSCLC patients, leveraging real-world data (RWD) and data from a pharma-sponsored clinical trial. Retrospective Single-Institution Application of a Deep Learning-Based Radiomic Score in Metastatic NSCLC: Abstract #251996 This study demonstrates how Onc.AI’s Deep Learning Radiomic baseline score can serve as a valuable prognostic tool for first-line treatment decisions in patients with mutation-negative NSCLC. Image Harmonization for PD-(L)1 Immune Checkpoint Inhibitor Response Prediction Using Deep Learning Radiomic Features in Advanced NSCLC: Abstract #245837 The research focuses on improving the accuracy of response prediction to immune checkpoint inhibitors in advanced NSCLC through image harmonization techniques. Dr. Ronan Kelly, MD, Director of Oncology at the Charles A. Sammons Cancer Center, Baylor University Medical Center in Dallas, Texas, commented on the significance of these findings: "These robust validation study results encompass both real-world data and a pharma-sponsored clinical trial. Serial CTRS has the potential to become a crucial tool for medical oncologists and can optimize pharma clinical development processes." Arpan Patel, MD, and Associate Professor of Medical Oncology at the University of Rochester Medical Center, further emphasized the clinical impact: "Our retrospective study highlights how Onc.AI’s Deep Learning Radiomic baseline score can significantly aid medical oncologists in making prognostic markers for first-line mutation-negative NSCLC patients." In addition to its poster presentation, Onc.AI will showcase its latest deep learning radiomic models at the ASCO Innovation Hub (IH13). Attendees, including medical oncologist investigators and biopharma companies, will have the opportunity to learn more about how these tools can accelerate oncology clinical development. About Onc.AI Onc.AI is a pioneering digital health company dedicated to creating AI-powered solutions for oncology clinical management. By applying advanced deep learning techniques to routine diagnostic images, the company's platform supports medical oncologists at the point of care and assists global pharmaceutical leaders in speeding up the development of oncology drugs. Onc.AI is backed by prominent institutional investors, including Blue Venture Fund, Action Potential Venture Capital (GSK), and MassMutual Alternative Investments. The company also receives support from the National Cancer Institute SBIR program (1R44CA291456-01A1). For more information, visit www.onc.ai. Media Contact For media inquiries, please contact: [email protected]