Galen™ Breast HER2 Aids Pathologists in Setting Higher
Standards for Accurate and Reproducible Biomarker Scoring to
Improve Patient Management
BOSTON, April 19,
2024 /PRNewswire/ -- Ibex Medical Analytics (Ibex),
the leader in AI-powered cancer diagnostics, today announced that
Galen™ Breast HER2 has been named a bronze winner of the 2024
Edison Awards in the Diagnostic Technologies category. The awards,
named after inventor Thomas Alva
Edison, honor companies and innovations that are shaping the
future, creating a positive impact in the world and improving
lives.
Breast cancer impacts one in eight American women and as such,
accurate and timely diagnosis is key to guiding treatment decisions
and improving survival rates. Ibex's Galen Breast HER2 is an
AI-powered scoring solution that helps pathologists assess HER2
expression in tumors to support identification of breast cancer
patients eligible for targeted therapies.
"The judges were thrilled to honor Galen Breast HER2 as a
groundbreaking category-changer this year, showcasing the power of
innovation to improve our lives for the better," declared
Frank Bonafilia, executive director
of the Edison Awards.
HER2, one of the proteins responsible for division and
proliferation of breast cancer cells, is expressed in many breast
tumors and its accurate assessment is critical for identifying
patients who are likely to benefit from HER2-directed therapies.
Traditionally, pathologists evaluate HER2 in tumor samples
visually, which may result in varied interpretations as scoring is
semi-quantitative and thus somewhat subjective1. The
recent emergence of antibody drug conjugates specifically targeting
HER2, which are also effective against HER2-low tumors, meant that
a new segment of HER2 expression became clinically actionable.
Pathologists now need to be able to evaluate and identify lower
levels of HER2 expression, despite limited experience in evaluating
those lower cut-offs. AI-powered tools may help pathologists with
accurate, rapid, and reproducible interpretation of HER2 protein
expression, particularly HER2 low, further
supporting oncologists in identifying effective therapies for
their patients.
Ibex's Galen Breast HER2 is an AI-powered HER2 IHC
(immunohistochemistry) scoring solution that detects invasive tumor
areas and quantifies HER2 expression, to support patient
identification for targeted therapies. The solution uses a novel
AI-powered computational pipeline to analyze HER2 IHC-stained
slides, automatically detect the invasive tumor areas, identify the
tumor cells, determine their staining pattern and rapidly calculate
the HER2 IHC score with high accuracy and reproducibility. Galen
Breast HER2 provides visualization of the AI findings to the
pathologist, who can review the invasive areas detected by the
algorithm, the cells' staining patterns, the percentage calculated
for each pattern, and make the final determination, thereby
retaining full control of the scoring process.
"The advent of new therapies which hold
great promise, and the continuously evolving knowledge of breast
cancer, require its diagnosis be more precise than ever before to
support oncologists in the identification of patients suited for
breakthrough treatments," said Joseph
Mossel, Co-Founder and Chief Executive Officer of Ibex
Medical Analytics. "We are grateful for this recognition by the
prestigious Edison Awards committee as we remain dedicated to
bringing accurate, timely and personalized diagnosis to every
patient. The award highlights our innovative approach in developing
AI-powered tools such as Galen Breast HER2 that set the new
standard in breast cancer diagnosis."
A multi-reader validation study demonstrated that pathologists
supported by Galen Breast HER2 showed higher consistency and
accuracy for HER2 scoring, particularly on the lower levels of HER2
expression, compared to pathologists who did not use AI. An early
evidence program to generate data on the accuracy and efficiency of
Galen Breast HER2 in clinical practice is now ongoing across 15
cancer centers and laboratories in the
United States, Canada,
Europe, the UK, and Brazil.
Galen Breast HER2 complements Galen Breast which helps
pathologists detect and grade different types of invasive and
non-invasive breast cancer, as well as identify multiple other
clinically significant features, such as tumor-infiltrating
lymphocytes (TILs), lymphovascular invasion (LVI) and
microcalcifications. Galen Breast is used in routine practice in
laboratories, hospitals and health systems worldwide and has
demonstrated robust outcomes across multiple clinical
studies2.3.
About Ibex Medical Analytics
Ibex Medical Analytics (Ibex) is transforming cancer diagnostics
with world-leading clinical grade AI-powered solutions for
pathology. Empowering physicians and supporting pathologists, Ibex
is on a mission to provide accurate, timely and personalized cancer
diagnosis for every patient. Ibex's Galen™ is the first and most
widely deployed AI-powered platform in pathology and demonstrated
outstanding outcomes in multiple clinical
studies2,3,4,5,6,7. Pathologists worldwide use Galen as
part of their everyday routine practice to improve the accuracy of
cancer diagnosis, implement comprehensive quality control measures,
reduce turnaround times and boost productivity with more efficient
workflows. For additional company information, please visit
https://ibex-ai.com/ and follow us on LinkedIn and X.
The Galen™ platform includes solutions which are for Research
Use Only (RUO) in the United
States and not cleared by the FDA. Multiple Galen solutions
are CE marked (IVDD and IVDR) and registered with the UK MHRA. For
more information, including indication for use and regulatory
approval in other countries, contact Ibex Medical Analytics.
Ibex Media Contact
Nechama
Rosengarten
FINN Partners
Nechama.rosengarten@finnpartners.com
[1] Robbins C.J. et al. Multi-institutional Assessment of
Pathologist Scoring HER2 Immunohistochemistry. Modern Pathology.
2023, 36(1):100032
[2] Sandbank et al., Validation and real-world clinical
application of an artificial intelligence algorithm for breast
cancer detection in biopsies, npj Breast Cancer, December 2022
[3] Vincent-Salomon et al., Primary Diagnosis of Breast Biopsies
supported by AI versus Microscope: Multi-Site Clinical Reader
Study. San Antonio Breast Cancer Symposium 2022.
[4] Pantanowitz et al., An artificial intelligence algorithm for
prostate cancer diagnosis in whole slide images of core needle
biopsies: a blinded clinical validation and deployment study, THE
LANCET Digital Health Aug 2020
[5] Rodriguez-Justo et al., Multi-Site Multi Reader Study on
Artificial Intelligence-Assisted Primary Diagnosis
of Gastric Biopsies, Virchows Arch (2023) 483 (Suppl 1): S1
[6] Comperat et al., Clinical Level AI-Based Solution for
Primary Diagnosis and Reporting of Prostate Biopsies in Routine
Use: A Prospective Reader Study, European Congress of Pathology
2021
[7] Raoux et al., Novel AI-Based Solution for Supporting Primary
Diagnosis of Prostate Cancer Increases the Accuracy and Efficiency
of Reporting in Clinical Routine, USCAP 2021
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SOURCE Ibex Medical Analytics