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Ibex Medical Analytics and Institut Curie Partner to Improve AI-Powered Breast Cancer Detection
Product News

Ibex Medical Analytics and Institut Curie Partner to Improve AI-Powered Breast Cancer Detection

Ibex Medical Analytics and Institut Curie Partner to Improve AI-Powered Breast Cancer Detection
Product News

Ibex Medical Analytics and Institut Curie Partner to Improve AI-Powered Breast Cancer Detection

Ibex Medical Analytics, a company in artificial intelligence (AI)-based cancer diagnostics and Institut Curie, France’s leading cancer center, today announced a research partnership aimed at improving diagnosis of breast cancer with AI.

Breast cancer is the most common malignant disease in women worldwide, with over 2 million new cases each year. As such, accurate and timely diagnosis of breast cancer is instrumental in guiding treatment decisions and improving patient survival rates. Analysis of breast tissue samples by a pathologist, typically using gross exam followed by examination under a microscope of tissue sections from biopsies or surgical specimens, remains the standard method of diagnosing and staging cancer. However, in recent years, an increase in cancer prevalence, coupled with a decline in the number of pathologists specialized in diagnosing cancer, has resulted in greater workloads and relatively long wait times for test results. Clearly, there is a growing need for automated solutions and decision support tools that can help pathologists diagnose cancer to the utmost accuracy more rapidly, while enabling comprehensive and affordable quality control.

This research partnership, the first of its kind, will include a rich dataset of breast biopsy slides, digitized using a digital pathology scanner, and analyzed for cancer detection by Ibex’s Galen™ Breast solution. Independently, multiple pathologists from Institut Curie will diagnose the slides, followed by blinded analysis of the AI-solution’s performance. Galen Breast, the first AI solution used for detection of breast cancer in pathology, was developed utilizing state-of-the-art AI and machine learning techniques, and trained on hundreds of thousands of image samples. The solution is already deployed at the pathology institute of Maccabi Healthcare Services, Israel’s second largest HMO, where it is used as a second read application.

“The importance of breast pathology is ever increasing, as new and more personalized treatments for breast cancer become available, many of which are based on precision medicine and require more tests and diagnosis by pathologists,” said Dr. Anne Vincent-Salomon, Director of Pathology at Institut Curie and the principal investigator in the study. “We believe that artificial intelligence can help us meet these challenges, and we are delighted to partner with Ibex, the leader in AI for cancer diagnosis in pathology. This collaboration will enable our pathologists to experience AI firsthand and evaluate its utility for diagnosing breast cancer.”

“We are excited to partner with Institut Curie, a global leader in research and treatment of breast cancer, for the first-ever blinded and independent evaluation of an AI-solution for breast cancer detection,” said Daphna Laifenfeld, PhD, Chief Scientific Officer at Ibex Medical Analytics. “Our Galen Prostate solution has demonstrated outstanding clinical outcomes and empowers pathologists worldwide to improve diagnostic accuracy and implement 100% quality control. We are continuing to expand our platform to new tissue types, focusing this time on breast biopsies, and are thrilled to work with Dr. Vincent-Salomon and her world-leading team on this important breast cancer study.” 

"This collaboration illustrates Institut Curie's approach to partnership-based research, combining the expertise of clinicians with the know-how of an innovation-driven technology company,” added Amaury Martin, PhD, Head of Technology Transfer and Industrial Partnerships Office at Institut Curie and Head of Carnot Curie Cancer. “It illustrates our commitment to play a major role in the development of artificial intelligence approaches applied to personalized medicine.”


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