Burlington, U.S. and Amsterdam, the Netherlands - LabCorp® (NYSE: LH) and the Mount Sinai Health System today announced another element in their shared goal of improving laboratory services and patient care. LabCorp, a leading global life sciences company, and Mount Sinai, New York City's largest integrated healthcare delivery system, will work together to establish the Mount Sinai Digital and Artificial Intelligence (AI)-Enabled Pathology Center of Excellence.
“LabCorp and Mount Sinai continue to focus on innovations to enhance the quality and lower the costs of patient care, and we’re pleased to introduce digital pathology to Mount Sinai as the next phase of our collaboration,” said William B. Haas, senior vice president of LabCorp Diagnostics’ Northeast Division. “We’ve taken significant steps to enhance laboratory services across the Mount Sinai system since early 2017, and we look forward to continuing to build on those successes to advance LabCorp’s mission and our shared goal to improve health and improve lives.”
LabCorp, which has implemented the Philips IntelliSite Pathology Solution in four of its laboratories and plans to introduce it to additional laboratories, will use its experience and expertise to lead the integration of digital pathology into clinical practice across Mount Sinai’s hospitals. Initially, digital pathology will be used for interpretations of genitourinary malignancies, mainly prostate tumors, as well as cancers of the head and neck. The next planned stage of implementation is for Mount Sinai pathologists to use the digital pathology solution to provide consultations for cases interpreted by LabCorp’s Dianon Pathology specialty laboratory. This will give physicians and patients from across the U.S. access to the leading expertise of Mount Sinai specialists.
The Center of Excellence will be housed within Mount Sinai’s Department of Pathology, Molecular and Cell-Based Medicine and will use the Philips IntelliSite Pathology Solution to expand digital pathology capabilities for primary diagnosis and consultations across the Mount Sinai system. The department processes more than 80 million diagnostic tests a year, making it one of the largest academic departments of its kind in the country.
“Digital pathology gives us the unprecedented opportunity to expand our services to the community at large, and engage members of our department, considered key opinion leaders in their field, to provide expert diagnostic opinions in complex cases. This, in addition to our new predictive AI-based tests, introduces the potential for optimization of treatment efficacy, and provides the opportunity for improved clinical outcomes,” said Carlos Cordon-Cardo, M.D., Ph.D., chairman of the Department of Pathology, Molecular and Cell-Based Medicine at Mount Sinai Health System and professor of Pathology, Genetics and Genomic Sciences, and Oncological Sciences at the Icahn School of Medicine at Mount Sinai.
Don Scanlon, chief financial officer and chief of corporate services at Mount Sinai, added, “The Digital and AI-Enabled Pathology Center of Excellence stands to offer major operational efficiencies, extending our joint unique resources and intellectual assets more effectively to improve the lives of patients.”
The Center of Excellence will include deployment of the Philips IntelliSite Pathology Solution at each of Mount Sinai’s eight hospitals and select ambulatory care locations. Digital pathology will allow for real-time pathology interpretations for physicians and patients throughout the New York metropolitan area without requiring the pathologist to be on-site where the patient is receiving care. Mount Sinai participated in Philips’ digital pathology performance evaluation to obtain market clearance in the U.S., gaining valuable expertise with the research version of the digital pathology system, providing the foundation for Mount Sinai’s AI diagnostic test development. Implementation of the clinical Philips IntelliSite Pathology Solution is underway and Mount Sinai expects to begin its use in the next several months.