Royal Philips, a global leader in health technology, and Ibex Medical Analytics, a pioneer in artificial intelligence (AI) based cancer diagnostics, announced a strategic collaboration to jointly promote their digital pathology and AI solutions to hospitals, health networks and pathology labs worldwide. The combination of Philips digital pathology solution (Philips IntelliSite Pathology Solution) and Ibex’s Galen™ AI-powered cancer diagnostics platform, currently in clinical use in Europe and the Middle East, empowers 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.
Today’s announcement marks the latest extension to Philips’ AI-enabled Precision Diagnosis solutions portfolio, which leverages Philips and third-party AI solutions 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.
The trend towards centralized pathology labs, the global shortage of trained pathologists, and increasing demands on histopathology posed by the growing number of cancer patients, leads pathology labs to actively seek efficiency-enhancing solutions that enable to maintain high accuracy levels. Digital pathology, enabled by solutions such as Philips IntelliSite Pathology Solution has already been shown to improve pathology lab productivity by 25% , 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.
“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.”
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 gain . 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 0.991 . 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% , and increasing overall quality of care.
“We have been using Philips’ IntelliSite Pathology Solution together with Ibex’s Galen™ platform as part of our routine practice since 2020, and this ‘second read’ implementation has already helped us improve our diagnostic quality,” said Delphine Raoux, MD, pathologist and Head of Innovation Technologies at Medipath, the largest network of private pathology labs in France. “The work we presented recently showed that Ibex’s AI platform can further provide significant productivity gains when used during primary diagnosis and helps us reduce total turnaround time. This is an important step forward as we look for new technologies that can help meet an increasing demand for pathology services and could enable seamless remote reading of biopsies in times of COVID restrictions.”
Philips digital pathology solution is a comprehensive turnkey solution that helps to speed and simplify access to histopathology information across cancer care and beyond, supports full-scale digitization of histology in pathology labs and lab networks, and help increases workflow efficiency. At the heart is Philips IntelliSite Pathology Solution, which comprises an ultra-fast pathology slide scanner, an image management system and display , which includes advanced software tools to manage slide scanning, image storage, case review, and the sharing of patient information. By fully digitizing post-sample-preparation histopathology, it facilitates the streamlining of pathology workflows and enables the connectivity needed between multi-disciplinary teams and specialties when making complex cancer diagnosis and treatment decisions, from early detection and precision diagnosis through to precision treatment and predictable outcomes.
Through breakthrough innovations and partnerships, Philips integrates intelligence and automation into its Precision Diagnosis portfolio, including smart diagnostic systems, integrated workflow solutions that transform departmental operations, advanced informatics that provides diagnostic confidence, and care pathway solutions that allow medical professionals to tailor treatment to individual patients. By developing and integrating these AI-enabled applications, the company aims to enhance the ability to turn data into actionable insights and drive the right care in the right sequence at the right time.
Today’s partnership announcement with Ibex follows recent AI partnership announcements with DiA Imaging Analysis for AI-powered ultrasound applications, and AI software provider Lunit, incorporating its chest detection suite into Philips diagnostic X-ray suite. These partner solutions complement Philips own AI solutions in personal health, precision diagnosis and treatment, and connected care.
About Royal Philips
Royal Philips is a leading health technology company focused on improving people’s health and well-being, and enabling better outcomes across the health continuum – from healthy living and prevention, to diagnosis, treatment and home care. Philips leverages advanced technology and deep clinical and consumer insights to deliver integrated solutions. Headquartered in the Netherlands, the company is a leader in diagnostic imaging, image-guided therapy, patient monitoring and health informatics, as well as in consumer health and home care. Philips generated 2020 sales of EUR 19.5 billion and employs approximately 82,000 employees with sales and services in more than 100 countries.
About Ibex Medical Analytics
Ibex uses AI to develop clinical-grade solutions that help pathologists detect and grade cancer in biopsies. The Galen™ platform is the first-ever AI-powered cancer diagnostics solution in routine clinical use in pathology and deployed worldwide, empowering pathologists to improve diagnostic accuracy, integrate comprehensive quality control and enable more efficient workflows. Ibex’s solutions are built on Deep Learning algorithms trained by a team of pathologists, data scientists and software engineers.