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PathAI Announces Early Adoption of its Digital Pathology Platform and Algorithms by Leading Anatomic Pathology Laboratories

PathAI, a global leader in AI-powered pathology, announced the launch of AISight, PathAI’s digital pathology platform, and the AIM-PD-L1 NSCLC RUO algorithm, which quantitates the percent of PD-L1 positive tumor and immune cells in non-small cell lung cancer (NSCLC) samples across the whole slide image (WSI), in 13 leading academic medical centers, health systems, reference laboratories, and independent pathology organizations across the United States. These organizations are part of PathAI’s Early Access Program to gather real-world evidence about the use of digital pathology tools to advance precision medicine for the benefit of patients around the world.

“We’re pleased to bring our technology and the advantages of a digital pathology workflow directly to some of the country’s leading laboratories,” said Andrew Beck, MD, PhD, co-founder and CEO of PathAI. “This network of laboratories will serve as pioneers in transforming anatomic pathology and will be the first to access PathAI’s extensive and growing menu of algorithm products across oncology and non-oncology indications.”

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AISight is a digital pathology platform that was designed with input from more than 200 pathologists and can be used by physicians, academic institutions, biopharma companies, and CROs to support AI-driven research. The AIM-PD-L1 NSCLC RUO algorithm was built using a series of convolutional neural networks, each trained on a diverse real-world dataset consisting of more than 5,000 samples with inputs from 350,000+ cell and tissue-level annotations from 50+ pathologists. The algorithm analyzes NSCLC surgical specimens stained with any of the four major clones and provides quantification and visualizations of PD-L1 positivity on tumor and immune cells for use in immune oncology research applications.

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“We recognize the benefits that digital pathology will provide to pathologists, oncologists and other clinicians, but there are still barriers to its adoption that need to be overcome such as cost and confidence in algorithm performance,” said Douglas Hartman, MD, Vice Chair of Pathology Informatics at The University of Pittsburgh Medical Center (UPMC), a world-renowned health system headquartered in Pittsburgh, Pennsylvania that operates 40 hospitals and more than 700 doctors’ offices and outpatient centers. “PathAI has a deep understanding of these obstacles, as shown by their significant investment in creating a simple and intuitive user interface to easily interpret the outputs of their algorithms. We’re pleased to be part of this first cohort of leading institutions to help advance the understanding and use of this technology.”

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PathAI previously published validation data for the AIM-PD-L1 NSCLC Algorithm that was presented at the 2022 AACR Annual Meeting. As part of the AISight Early Access Network, participating laboratories will be building on this work to test the performance of the AIM-PD-L1 NSCLC algorithm on real-world data. These labs will also be able to access a suite of additional immunohistochemistry (IHC) quantitation algorithms across Breast Cancer, Urothelial Carcinoma, Head and Neck Squamous Cancer, and Melanoma. PathAI has previously published data in Modern Pathology highlighting the potential for AI-powered PD-L1 algorithms to identify more patients who would benefit from treatment with immuno-oncology therapy compared with current guidelines using manual assessment.

“As a leader in precision medicine and digital pathology, PathGroup is committed to transforming patient care and providing our clients with cutting-edge technology,” stated Derek Welch, MD, FCAP, Chief Medical Officer of Anatomic Pathology at PathGroup, one of the largest independent anatomic pathology laboratories in the United States serving more than 200 hospitals and 15,000 referring physicians. “Our partnership with PathAI allows us to deploy their AI-powered algorithms in our work to enhance our industry-leading efficiency and accuracy and improve outcomes for the patients who are at focus of everything we do.”

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