Philips Collaborates with AI Startup Ibex to Accelerate Adoption of AI-Powered Digital Pathology Solutions
By LabMedica International staff writers Posted on 13 Apr 2021 |

Image: Philips Digital Pathology (Photo courtesy of Royal Philips)
Royal Philips (Amsterdam, The Netherlands) and Ibex Medical Analytics (Tel Aviv, Israel) have entered into 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. The 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.
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.
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, one to two-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.
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. The latest 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.
“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.”
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. The 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.
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.
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, one to two-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.
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. The latest 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.
“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.”
Latest Industry News
- Lunit and Microsoft Collaborate to Advance AI-Driven Cancer Diagnosis
- AMP Releases Best Practice Recommendations to Guide Clinical Laboratories Offering HRD Testing
- Illumina Acquires SomaLogic to Accelerate Proteomics Business
- Qiagen and Gencurix Partner on Development of QIAcuity Digital PCR IVD Assay
- QIAGEN and Incyte Enter into Precision Medicine Collaboration
- bioMérieux Acquires Day Zero Diagnostics Solutions and Technologies
- Aston University and BG Research Partner to Commercialize Groundbreaking Medical Diagnostic
- Fujirebio Collaborates with Stanford Medicine to Advance Infectious Disease Research
- QuidelOrtho to Acquire MDx Company LEX Diagnostics
- QIAGEN Enters into New Strategic Partnerships for Expanding MRD Testing Portfolio in Oncology
- Danaher and AstraZeneca Partner on Next Generation AI-Powered Diagnostics
- EuroMedLab 2025 Showcases Latest Technologies and Innovations in Laboratory Medicine
- Qiagen Acquires NGS Analysis Software Company Genoox
- Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions
- Grifols and Tecan’s IBL Collaborate on Advanced Biomarker Panels
- New Collaboration to Advance Microbial Identification for Infectious Disease Diagnostics
Channels
Clinical Chemistry
view channel
New Clinical Chemistry Analyzer Designed to Meet Growing Demands of Modern Labs
A new clinical chemistry analyzer is designed to provide outstanding performance and maximum efficiency, without compromising affordability, to meet the growing demands of modern laboratories.... Read more
New Reference Measurement Procedure Standardizes Nucleic Acid Amplification Test Results
Nucleic acid amplification tests (NAATs) play a key role in diagnosing a wide range of infectious diseases. These tests are generally known for their high sensitivity and specificity, and they can be developed... Read moreMolecular Diagnostics
view channel
RNA-Seq Based Diagnostic Test Enhances Diagnostic Accuracy of Pediatric Leukemia
A new unique test is set to reshape the way Acute Lymphoblastic Leukemia (BCP-ALL) samples can be analyzed. Qlucore (Lund, Sweden) has launched the first CE-marked RNA-seq based diagnostic test for pediatric... Read more
New Technique for Measuring Acidic Glycan in Blood Simplifies Schizophrenia Diagnosis
Polysialic acid is a unique acidic glycan predominantly found in brain regions associated with memory and emotion, but it is also present in the bloodstream. Research has shown that blood levels of polysialic... Read moreHematology
view channel
Disposable Cartridge-Based Test Delivers Rapid and Accurate CBC Results
Complete Blood Count (CBC) is one of the most commonly ordered lab tests, crucial for diagnosing diseases, monitoring therapies, and conducting routine health screenings. However, more than 90% of physician... Read more
First Point-of-Care Heparin Monitoring Test Provides Results in Under 15 Minutes
Heparin dosing requires careful management to avoid both bleeding and clotting complications. In high-risk situations like extracorporeal membrane oxygenation (ECMO), mortality rates can reach about 50%,... Read moreImmunology
view channel
Blood Test Detects Organ Rejection in Heart Transplant Patients
Following a heart transplant, patients are required to undergo surgical biopsies so that physicians can assess the possibility of organ rejection. Rejection happens when the recipient’s immune system identifies... Read more
Liquid Biopsy Approach to Transform Diagnosis, Monitoring and Treatment of Lung Cancer
Lung cancer continues to be a major contributor to cancer-related deaths globally, with its biological complexity and diverse regulatory processes making diagnosis and treatment particularly difficult.... Read more
Computational Tool Exposes Hidden Cancer DNA Changes Influencing Treatment Resistance
Structural changes in tumor DNA are among the most damaging genetic alterations in cancer, yet they often go undetected, particularly when tissue samples are degraded or of low quality. These hidden genomic... Read moreMicrobiology
view channel
Viral Load Tests Can Help Predict Mpox Severity
Mpox is a viral infection that causes flu-like symptoms and a characteristic rash, which evolves significantly over time and varies between patients. The disease spreads mainly through direct contact with... Read more
Gut Microbiota Analysis Enables Early and Non-Invasive Detection of Gestational Diabetes
Gestational diabetes mellitus is a common metabolic disorder marked by abnormal glucose metabolism during pregnancy, typically emerging in the mid to late stages. It significantly heightens the risk of... Read morePathology
view channel
AI Performs Virtual Tissue Staining at Super-Resolution
Conventional histopathology, essential for diagnosing various diseases, typically involves chemically staining tissue samples to reveal cellular structures under a microscope. This process, known as “histochemical... Read more
AI-Driven Preliminary Testing for Pancreatic Cancer Enhances Prognosis
Pancreatic cancer poses a major global health threat due to its high mortality rate, with 467,409 deaths and 510,992 new cases reported worldwide in 2022. Often referred to as the "king" of all cancers,... Read more
Cancer Chip Accurately Predicts Patient-Specific Chemotherapy Response
Esophageal adenocarcinoma (EAC), one of the two primary types of esophageal cancer, ranks as the sixth leading cause of cancer-related deaths worldwide and currently lacks effective targeted therapies.... Read more
Clinical AI Solution for Automatic Breast Cancer Grading Improves Diagnostic Accuracy
Labs that use traditional image analysis methods often suffer from bottlenecks and delays. By digitizing their pathology practices, labs can streamline their work, allowing them to take on larger caseloads... Read moreTechnology
view channel
Inexpensive DNA Coated Electrode Paves Way for Disposable Diagnostics
Many people around the world still lack access to affordable, easy-to-use diagnostics for diseases like cancer, HIV, and influenza. Conventional sensors, while accurate, often rely on expensive equipment... Read more