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Leading UK Diagnostics Provider Source LDPath Expands AI Capabilities with Ibex Medical Analytics

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TEL AVIV, Israel, and LONDON – Ibex Medical Analytics (Ibex), the leader in AI-powered cancer diagnostics and Source LDPath, a part of Source BioScience (Source), a leading international provider of integrated state-of-the-art laboratory services and products, today announced an agreement to expand the deployment Artificial Intelligence (AI) to the entire pathology network at Source.

 

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The expansion builds on Ibex’s previous work with LDPath, which was acquired earlier this year by Source to create Source LDPath, one of the largest private providers of cellular and digital pathology services in the UK. The deployment will include new AI-powered tools for diagnosing multiple tissue types and support pathologists with improved diagnostic accuracy and efficiency. 

Across the UK, patients have faced significant delays in cancer diagnosis due to a shortage of pathologists, a rise in cancer cases, growing workloads imposed on pathology departments and a significant backlog in cases following the pandemic. Despite advancements, with roughly 275,000 women undergoing breast biopsy and 100,000 men undergoing prostate biopsy in the UK each year1,2, NHS pathology services often miss on their reporting targets, leading to delays in treatment initiation which may impact patients’ survival rates.

Clearly, there is a growing need for automated solutions and decision-support tools that help pathologists detect cancer to the utmost accuracy more rapidly. Ibex’s Galen™ platform will be made available to the entire Source network, spanning more than 200 pathologists who will use Ibex’s AI-powered workflows integrated into an inhouse developed LIS and reporting system.

The Galen suite of solutions from Ibex is the first and most widely deployed AI technology in pathology, used in routine clinical practice in laboratories, hospitals, and health systems worldwide. It supports pathologists in a variety of tasks during the diagnosis of breast, prostate, and gastric biopsies and helps improve the accuracy of cancer diagnosis, reduce turnaround time, boost productivity, and improve user experience for pathologists. Galen demonstrated outstanding outcomes across multiple clinical studies performed on various tissue types and diagnostic workflows3,4,5,6,7.

“We are building the largest private digital pathology network in the UK, helping in mitigating the impact of the continued shortage of pathologists and addressing the NHS backlog in cancer diagnosis, which has become a national priority,” added Sanj Lallie, Commercial and Digital/AI Director, Source LDPath. “We are proud to expand our diagnostic capabilities with Ibex’s world-renowned AI technology, adopted at scale across our network to help ensure that cancer patients receive an accurate and timely diagnosis.”

Dr. Alistair Robson, FRCPath, DipRCPath and Medical Director of Source LDPath added, “I have seen first-hand how transformative and impactful AI-powered tools can be for a pathologist’s work. I am encouraged by the continued rollout of Ibex AI across UK hospital trusts and am looking forward to seeing Ibex’s newly announced biomarker scoring tools helping breast pathologists improve diagnosis of IHC stained slides.”

“We are thrilled to expand the deployment of our innovative AI technology, already used in routine clinical practice in the UK, into additional NHS trusts,” said Stuart Shand, Ibex Medical Analytics Chief Commercial Officer. “It is exciting to see our Galen platform become available to many more pathology services through our partnership with Source, empowering pathologists who face unprecedented case-loads and helping oncologists improve care for cancer patients.”

About Ibex Medical Analytics

Ibex Medical Analytics (Ibex) is transforming cancer diagnostics with world-leading, clinical grade AI-powered solutions, empowering physicians to provide accurate, timely and personalized cancer diagnosis for every patient. Our Galen™ suite of solutions is the first and most widely deployed AI-technology in pathology and used as part of everyday routine, supporting pathologists and providers worldwide in improving the quality and accuracy of diagnosis, implementing comprehensive quality control, reducing turnaround times and boosting productivity with more efficient workflows. Ibex’s Artificial Intelligence technology is built on Deep Learning algorithms trained by a team of pathologists, data scientists and software engineers. For additional company information, please visit https://ibex-ai.com/ and follow us on LinkedIn and Twitter.

About Source LDPath

Source LDPath, a part of Source BioScience, specializes in digitalizing pathology diagnostics with its ground-breaking bespoke modular digital pathology and AI, transforming surgical pathology reporting for client laboratories. Marked improvement of turnaround times, from sample receipt to pathology report, and seamless integration of AI analytics, facilitates patient management and rapid access to appropriate treatment. We are your expert guiding hand in digital pathology and AI integration. More details can be found here: www.sourcebioscience.com.

[1] https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer 

[2] https://www.gov.uk/government/news/new-hospitals-join-pioneering-study-to-improve-prostate-cancer-diagnosis-using-ai

[3] 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

[4] Vincent-Salomon et al., A Multi-Feature AI-Based Solution for  Cancer Diagnosis in Breast Biopsies: A Prospective Blinded Multi-Site Clinical Study, European Congress of Pathology 2021  

[5] 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

[6] 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

[7] Sandbank et al., Validation and Clinical Deployment of an AI-Based Solution for Detection of Gastric Adenocarcinoma and Helicobacter pylori in Gastric Biopsies, USCAP 2022