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Paige introduces AI-based biomarker for colon cancer diagnosis

Digital pathology and clinical AI firm Paige has announced a new AI-based digital assay to support pathologists in the detection and diagnosis of microsatellite instability (MSI) status in colon cancers.

Paige Colon MSI operates on whole slide images of haematoxylin and eosin (H&E)-stained slides alone, offering slide-level classification of MSI status in colon cancer samples* based on morphologies associated with the presence or absence of MSI/MMR phenotype. Paige Colon MSI is a new addition to Paige’s Colon Suite which also includes case and slide-level detection of suspicious regions including invasive carcinoma and high-grade dysplasia. Where permitted, Paige Colon MSI is for research use only, not for use in diagnostic procedures.

Paige Colon MSI aims to assist pathologists by providing additional insight in identifying those patients who may benefit from definitive MSI/MMR testing for one of the most common hereditary cancer syndromes and IO therapy. The system has been designed to be optimised for negative predictive value (NPV=0.99 when assessed on over 500 samples from various sources). AI results can be obtained immediately from digitised stained sections so there is no need to wait days to weeks for results for the ~85% of patients whose tumours are MS stable and could potentially avoid the expensive screening that is required today.

“Paige Colon MSI is another example of how the company is innovating to empower pathologists, transform pathology and improve the lives of patients with cancer,” said Dr Joe Oakley, MD, Medical Director of Biomarker Development at Paige. “We used the most advanced machine learning methods available on the most robust dataset in the industry to improve AI detection of MSI in colon cancer. We hope to demonstrate that this assay will offer laboratories and healthcare systems a chance to reduce MSI screening costs and accelerate their workflows. We believe this represents an important first step to more comprehensive MSI and mismatch repair deficiency detection in cancers.”

Despite guideline recommendations, recent studies have shown not all patients are being tested for MSI status. Introducing Paige Colon MSI as a cost-effective and time-efficient assistive testing method may improve access to diagnostic testing for more patients by highlighting cases likely to harbour MSI, which should then be confirmed by immunohistochemistry or molecular methods to inform precision treatment decisions.

While colon cancer is the initial focus, Paige is working to develop subsequent enhancements to enable screening in additional cancer types.

For further information, please visit: www.paige.ai

 

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