Stratipath And Proscia Announce Partnership, Paving The Way To Bring Relapse Risk Prediction To More Breast Cancer Patients

STOCKHOLM – Press Release – Stratipath, a global leader in artificial intelligence (AI)-based precision diagnostic solutions, and ProsciaÂź, a leading provider of digital and computational pathology solutions, have partnered to help oncologists and pathologists determine the most suitable treatment path for more breast cancer patients. The collaboration paves the way for integrating AI-based decision support into routine diagnostic workflows, enabling the identification of patients with increased risk of disease progression.

Breast cancer is the most common cancer worldwide and affects over 2.3 million women every year. Over 50% of all, and around 60% of ER-positive/HER2-negative, breast cancers are classified as histological grade 2, an intermediate risk group that provides limited value to guide decisions on choice of therapy. Computer-based image analysis has shown to be able to divide intermediate tumours into a low- and high-risk group associated with risk of recurrence.

The partnership paves the way for delivering an integrated solution that combines Stratipath Breast with Proscia’s CE-IVDR marked Concentriq¼ Dx* enterprise pathology platform. Stratipath Breast is the first EU regulatory-compliant solution for risk stratification of breast cancer using AI-based precision diagnostics. This deep learning-based solution analyzes digitized hematoxylin and eosin-stained histopathology images of breast cancer tissue to enable the identification of patients with increased risk of disease progression, thus providing novel decision support for clinicians in the diagnostic evaluation of breast cancer. In contrast to conventional molecular tests, AI-based risk profiling offers shorter turnaround times for results, delivers new insights at the point of diagnosis, and substantially reduces the reliance on expensive molecular testing. As a result, Stratipath Breast provides broader accessibility and benefits for a greater number of breast cancer patients.

“Stratipath Breast represents a significant advancement by offering a faster and more cost-effective alternative to traditional molecular assays. Through our partnership with Proscia, we look forward to enabling clinicians to receive rapid diagnoses accompanied by valuable prognostic insights, all while streamlining laboratory processes and minimizing costs” says Johan Hartman, co-founder of Stratipath and professor of pathology at Karolinska Institutet, Stockholm.

Concentriq Dx is an enterprise pathology platform that drives primary diagnostic workflows for reference laboratories, hospitals, and health systems of all sizes. It offers a compelling user experience that allows pathologists to quickly transition away from the microscope and work with speed and ease. An open platform, Concentriq Dx is designed to integrate AI applications from Proscia, Proscia’s customers, and leading third parties, including Stratipath, into routine workflows so that laboratories can realize the full promise of pathology’s computational future at scale.

“We are seeing firsthand that an open approach to digital pathology is better enabling laboratories to meet their short and long-term goals,” said Stephan Fromme, Proscia’s Head of Strategic Alliances. “Stratipath Breast is already delivering clinical and economic benefits impacting laboratories, pathologists, and patients. We are excited to pave the way for adding it to the portfolio of solutions we will make available to our customers.”

To learn more about the partnership, visit Stratipath at booth 38 and Proscia at booth 15 during the 10th Digital Pathology and AI Congress: Europe. 

*Concentriq Dx is CE-marked under IVDR.

“Breast Cancer.” World Health Organization: Fact Sheets. July 12, 2023. https://www.who.int/news-room/fact-sheets/detail/breast-cancer

Wang Y, Acs B, Robertson S, Liu B, Solorzano L, WĂ€hlby C, et al. Improved breast cancer histological grading using deep learning. Ann Oncol. 2022;33(1):89-98. https://doi.org/10.1016/j.annonc.2021.09.00