A strategic collaboration between Royal Philips and Ibex Medical Analytics will combine Philips IntelliSite Pathology Solution with Ibex’s Galen AI-powered cancer diagnostics platform. The agreement will give help pathologists to generate objective, reproducible results, increase diagnostic confidence, and enable the productivity and efficiency improvements needed to cope with ever-increasing demand for pathology-based diagnostics. Ibex’s Galen is currently not FDA approved and is for research use only in the US.
According to the companies, the combination of Philips’ digital pathology solutions and Ibex’s AI-powered Galen platform has improved reporting efficiency by 27%, driven 37% productivity gains, and improved consistency and accuracy to enhance diagnostic confidence. The agreement marks the latest extension to Philips’ AI-enabled Precision Diagnosis solutions portfolio to deliver cutting-edge clinical decision support and optimized workflows that enable healthcare providers to deliver on the Quadruple Aim of better patient outcomes, improved patient and staff experiences, and lower cost of care.
Digital pathology, enabled by solutions such as Philips IntelliSite Pathology Solution has already been shown to improve pathology lab productivity by 25%, according to a survey of 52 physicians in Europe conducted by Philips, while also allowing remote image reading by specialists and the immediate sharing of images with referring hospitals as part of comprehensive pathology reports. Ibex’s AI-powered Galen platform further streamlines workflow and improves accuracy via automated case prioritization, cancer heatmaps, grading and other productivity-enhancing tools.
Ibex’s Galen platform adds AI-powered cancer detection, case prioritization, grading and other productivity-enhancing insights. Users have reported significant improvements in diagnostic efficiency, with 27% reduction in time-to-diagnosis compared to conventional microscope viewing, 1- to 2-day reductions in total turnaround time, and 37% productivity gain1. In addition to cancer, the AI platform supports pathologists in the accurate grading, as well as detection and diagnosis of multiple clinical features, such as tumor size, perineural invasion, high-grade PIN (Prostatic Intraepithelial Neoplasia) and more. The accuracy level of Galen Prostate for cancer detection was the highest level reported in the field, with a sensitivity rate of 98.46%, specificity of 97.33% and an AUC of 0.9912. When used as an automated ‘second read,’ the platform alerts pathologists when discrepancies between their diagnosis and the AI algorithm’s findings are detected, providing a safety net against error or misdiagnosis, previously reported as high as 12%3, and increasing overall quality of care.
“Building on our strong portfolio to support clinical decision-making in oncology, we bring together the power of imaging, pathology, genomics and longitudinal data with insights from artificial intelligence (AI) to help empower clinicians to deliver clear care pathways with predictable outcomes for every patient,” said Kees Wesdorp, Chief Business Leader, Precision Diagnosis at Philips. “By teaming with Ibex to incorporate their AI into our Digital Pathology Solutions, we’re further able to provide a continuous pathway, where critical patient data is made visible to both pathologists and oncologists to help improve the clinician experience and patient outcomes.”
“Pathology is transforming at an increasing pace and AI is one of the major drivers, supporting a more rapid and accurate cancer diagnosis,” said Joseph Mossel, CEO and Co-founder of Ibex Medical Analytics. “By joining forces with Philips, the leader in digital pathology deployments, we can offer new end-to-end solutions enabling pathologists to implement integrated, AI-powered workflows across a broader segment of the diagnostic pathway, improving the quality of patient care and strengthening the business case for digitization.”
 Raoux D, et al, Novel AI Based Solution for Supporting Primary Diagnosis of Prostate Cancer Increases the Accuracy and Efficiency of Reporting in Clinical Routinehttps://uscap.econference.io/public/fYVk0yI/main/sessions/9644/31166
 The LANCET Digital Health, Aug 2020, 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 https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30159-X/fulltext
 Laifenfeld D et al, Performance of an AI-based cancer diagnosis system in France’s largest network of pathology institutes https://ibex-ai.com/wp-content/uploads/2019/09/poster-v6-web.pdfBack To Top
Philips, Ibex Medical Analytics Collaborate on AI-powered Digital Pathology. Appl Rad Oncol.