Onc.AI to Present Immunotherapy Response Prediction Using Radiomics in Late-Stage Lung Cancer

SAN CARLOS, Calif. & WATERLOO, Canada -- (BUSINESS WIRE) -- Onc.AI, a digital health company innovating oncology clinical management solutions, revealed that new data will be presented at the 2024 Annual Society of Clinical Oncology (ASCO). This data stems from their collaboration with Pfizer, aimed at assessing the efficacy of Onc.AI’s radiomics-based multimodal signature in predicting immunotherapy response in metastatic lung cancer patients.

ICI therapy is the standard treatment for patients with mutation-negative metastatic lung cancer. However, identifying which patients are likely to respond to this treatment remains a significant challenge. Onc.AI’s radiomic survival prediction model aims to address this by categorizing stage IV NSCLC patients based on their likelihood of being progression-free at six months while undergoing single-agent checkpoint inhibition therapy, according to RECIST 1.1 criteria. The model’s performance was thoroughly trained and validated across various NSCLC patient cohorts.

1L Real-World Cross-Validation Cohort: The model demonstrated a Progression Free Survival Hazard Ratio (PFS HR) of 0.49 (0.38-0.63) in a broad patient population, and 0.28 (0.17-0.46) in patients treated exclusively with single-agent immunotherapy.

1L Real-World Holdout Cohort: The PFS HR was 0.18 (0.05-0.61) in patients receiving single-agent immunotherapy.

2L+ Clinical Trial Cohort (NCT02573259): Among NSCLC patients treated with Sasanlimab (Pfizer), the model showed a PFS HR of 0.30 (0.14-0.68) and an Overall Survival Hazard Ratio (OS HR) of 0.29 (0.10-0.83).

"We are excited to present the results of our collaboration with Pfizer, which highlight the effectiveness of our foundational model in predicting treatment responses across diverse patient groups," commented Akshay Nanduri, CEO of Onc.AI. "Developing non-invasive tools to support clinical decision-making is central to Onc.AI’s mission."

The details of the oral presentation are as follows:

Date and Time: June 1st, 2024, at 8:00 am CDT
Session Topic: Using “Artificial” Intelligence to Achieve “Real” Improvements in Cancer Care
Abstract Number: #102
Title: Real-world and clinical trial validation of a deep learning radiomic biomarker for PD-(L)1 immune checkpoint inhibitor response in stage IV NSCLC

About Onc.AI

Onc.AI is a privately held digital health company focused on creating a precision oncology care management platform with the aim of revolutionizing clinical decision-making. The company's foundation is built on the concept that radiomics-based multi-modal Machine Learning models can significantly improve the prediction of patient responses to PD-(L)1 immunotherapy. Onc.AI is committed to developing an innovative radiomic solution to address the unpredictable responses to PD-(L)1 ICI therapy, thus improving patient outcomes and reducing the financial burden on healthcare systems and payers.

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