Accelerating the Creation of an AI Medical Industry Ecosystem
Seoul St. Mary's Hospital, affiliated with the Catholic University of Korea, announced on February 27 that the CODiPAI (Consortium for Digital Pathology Artificial Intelligence) project, led by Professor Chan Kwon Jung from the Department of Pathology and involving multiple institutions, has achieved the construction of large-scale cancer digital pathology data and significant commercialization outcomes for participating companies.
Professor Chan Kwon Jung of the Department of Pathology at Seoul St. Mary's Hospital is explaining the digital pathology data established through the CODiPAI project. Seoul St. Mary's Hospital
Supported by research funding from the Ministry of Health and Welfare, this project has been conducted over five years since 2021. The consortium has built an infrastructure comprising more than 160,000 whole slide images (WSI) of cancer pathology and highly detailed, pathologist-level annotation data, establishing Korea’s premier digital pathology data infrastructure. Annotation data involves the precise distinction and labeling of regions such as cancer tissue and normal tissue within pathology images, which is essential for AI to learn lesions and improve diagnostic accuracy. These data have been standardized and subjected to rigorous quality control using actual clinical cancer pathology materials generated by participating hospitals, ensuring their usability throughout the entire process of developing AI-based medical products.
Digital pathology is a technology that analyzes tissue using high-resolution digital images instead of traditional glass slides. Recently, when combined with AI, it is expected to improve diagnostic accuracy and increase work efficiency. According to the global market research firm MarketsandMarkets, the global digital pathology market is projected to grow at an average annual rate of 13.6%, expanding from USD 900 million (approximately KRW 1.2892 trillion) in 2023 to USD 1.8 billion (approximately KRW 2.5785 trillion) in 2028, owing to these advantages.
In particular, the CODiPAI consortium is recognized for having established Korea’s first and largest cloud-based digital pathology platform, successfully bridging the gap between research-stage technology and real-world industry applications. At the same time, medical AI companies have been provided with a foundation to develop products and pursue commercialization by utilizing high-quality pathology data.
The project involved 15 university hospitals, with Seoul St. Mary's Hospital at the center, as well as nine companies including Urban Data Lab, Suphath, Avis, DEEP:PHI, and Digital Pharm. By leveraging the digital pathology data built by the consortium, participating companies advanced their AI technologies and developed medical device products, resulting in five companies acquiring Class 2 medical device and in vitro diagnostic software certifications.
Notably, the project led to the development of automated pathology image analysis, quantitative assessment technologies, and AI solutions applicable to clinical practice. Some companies have been selected for the Techstars Healthcare Accelerator Program in the United States, marking the start of overseas market expansion through collaborations with Permanente Medicine, one of the largest healthcare networks in the US.
In addition, the participating companies have played a leading role in establishing the Korea Digital Pathology Association, creating a collaborative foundation for the dissemination of digital pathology technology and the development of the industry ecosystem. Furthermore, they are expanding examples of international cooperation by collaborating with global healthcare and biotechnology companies, continuing to achieve business milestones.
Professor Chan Kwon Jung, the principal investigator of the study, stated, "The CODiPAI project is significant because it goes beyond simply building datasets and provides a digital pathology data infrastructure that can actually be utilized by researchers and companies. The large-scale cancer pathology data constructed during the project period and the resulting achievements of companies demonstrate that data-driven medical AI research and industry development can progress together. We will continue to enhance the quality and utility of digital pathology data, furthering our role as an open platform that connects research and industry."
Professor Chan Kwon Jung is regarded as one of the most active and accomplished researchers in the field of tissue diagnosis technologies based on digital pathology and artificial intelligence, both domestically and internationally. In the past three years, he has published over 40 papers in international journals, accumulating significant research outcomes in pathology image analysis, label-free tissue diagnosis, diagnostic algorithm advancement, and the development of AI platforms for clinical application. He has also led numerous national research projects, contributing to expanding the clinical applicability of AI-based pathology diagnosis technologies.
Professor Jung's research focuses on establishing foundational technologies to improve the accuracy and efficiency of histopathology. In particular, he has advanced the standardization and automation of pathology diagnosis through the development of core technologies in digital pathology, such as virtual staining, quantitative analysis of cellular structures, and tumor classification algorithms. These research achievements are regarded as an important foundation for improving the reliability and accessibility of pathology diagnosis. Drawing on his extensive experience in digital transformation and AI utilization in the field of pathology, as well as his academic accomplishments, he also serves as the Chief of Smart Hospital Information at Seoul St. Mary's Hospital.
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