Ibex Medical Analytics (Ibex), the leader in AI-powered cancer diagnostics,announced an agreement with AstraZeneca and Daiichi Sankyo, for the development, clinical validation and early adoption of an AI-powered product to aid pathologists with an accurate and reproducible assessment of HER2 immunohistochemistry (IHC) scoring in breast cancer patients.
Scoring of HER2 (human epidermal growth factor receptor 2) protein expression in breast cancer is used to identify patients who are likely to benefit from HER2-directed therapies. Currently, pathologists routinely score HER2 in tumor samples visually using a microscope, which can be challenging in cases of low HER2 expression as scoring is subjective and may lead to varied interpretations. Computational tools developed using Artificial Intelligence have the potential to support pathologists in accurate and objective scoring of HER2, which can help oncologists in selecting therapies that are approved for treating patients with HER2-positive or HER2-low breast cancer.
“Recognizing the vital role pathologists play in the diagnosis and treatment of cancer patients, we are thrilled to partner with AstraZeneca and Daiichi Sankyo to clinically validate our automated HER2 scoring product and offer it to laboratories around the world,” said Joseph Mossel, Co-founder and CEO of Ibex Medical Analytics. “As the most commonly diagnosed cancer in women, this collaboration will allow pathologists to utilize our technology to optimize breast cancer diagnosis and ultimately improve the identification of patients eligible for HER2-directed therapy.”
Ibex’s Galen™ Breast HER2 is an IHC scoring product that detects tumor areas and quantifies HER2 expression into four standard categories, 0, 1+, 2+ and 3+, based on the 2018 ASCO/CAP scoring guidelines1. As part of this collaboration, Ibex will work with AstraZeneca and Daiichi Sankyo to develop and clinically validate its HER2 IHC scoring product and generate evidence that further supports adoption of the technology.
A multi-site validation study on Galen Breast HER2 involved a cohort of 453 breast tumors of diverse subtypes. The study demonstrated that Galen’s AI algorithm provides an accurate and automated HER2 score for pathologists and was recently presented at the San Antonio Breast Cancer Symposium.
Beyond this collaboration, Ibex supports pathologists with AI-based diagnostic solutions that help detect and grade different types of invasive and non-invasive breast cancer and other tumor types, and are used in everyday practice in laboratories, hospitals and health systems worldwide. Ibex’s Galen Breast solution demonstrated robust outcomes in detecting and grading multiple types of breast cancer and other clinically relevant features across clinical studies performed on numerous diagnostic workflows, one of which was recently published in Nature’s peer-reviewed npj Breast Cancer journal.
In addition to HER2, Ibex is further expanding Galen Breast to include automated quantification of additional IHC-stained slides, such as ER, PR and Ki-67, intended to provide pathologists with a comprehensive set of tools for breast cancer diagnosis. With these expanded capabilities, Galen Breast may further enhance diagnostic efficiency and enable more accurate and objective scoring of breast biomarkers, improving treatment decisions and patient care.