Ibex Medical Analytics (Ibex), the leader in AI-enabled cancer diagnostics, today announced an agreement with AstraZeneca and Daiichi Sankyo to develop, clinically validate and early launch an AI-enabled product to empower pathologists with accurate and reproducible assessment support HER2 immunohistochemistry (IHC) scoring in breast cancer patients.
Assessing HER2 (human epidermal growth factor receptor 2) protein expression in breast cancer is used to identify patients who are likely to benefit from HER2-targeted therapies. Currently, pathologists routinely assess HER2 in tumor samples visually using a microscope, which can be challenging when HER2 expression is low because the assessment is subjective and can lead to different interpretations. Computational tools developed using artificial intelligence have the potential to help pathologists accurately and objectively assess HER2, which can help oncologists select therapies approved for the treatment of patients with HER2-positive or HER2-low breast cancer.
“Regarding the important role pathologists play in the diagnosis and treatment of cancer patients, we are very excited 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. “Because it is the most commonly diagnosed cancer in women, this collaboration will allow pathologists to use our technology to streamline breast cancer diagnosis and ultimately improve patient identification for HER2-targeted therapy.” are.”
Ibex Galen™ Breast HER2 is an IHC assessment product that detects tumor areas and quantifies HER2 expression in four standard categories, 0, 1+, 2+ and 3+, based on the 2018 ASCO/CAP assessment guidelines1 Under the terms of the collaboration, Ibex will work with AstraZeneca and Daiichi Sankyo to develop and clinically validate its HER2 IHC scoring product and generate evidence to further support the adoption of the technology.
A multi-site validation study of Galen Breast HER2 included a cohort of 453 breast tumors of different subtypes. The study demonstrated that Galen’s AI algorithm provides pathologists with an accurate and automated HER2 score and was recently presented at the San Antonio Breast Cancer Symposium2.
Beyond this collaboration, Ibex supports pathologists with AI-based diagnostic solutions that help detect and categorize different types of invasive and non-invasive breast cancer and other tumor types, and are used in daily practice in laboratories, hospitals, and healthcare systems worldwide. Ibex’s Galen Breast Solution demonstrated robust results in detecting and staging multiple types of breast cancer and other clinically relevant features in clinical studies conducted on numerous diagnostic workflows, one of which was recently published in Nature’s peer-reviewed npj Breast Cancer Journal3,4.
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 toolkit for breast cancer diagnosis. With these expanded capabilities, Galen Breast can further improve diagnostic efficiency and enable more accurate and objective assessment of breast biomarkers, improving treatment decisions and patient care.
