Stratipath and Roche Join Forces to Help Expand Access to AI-Powered Precision Diagnostics

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 analyses digitised haematoxylin 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. By integrating with Roches navify® Digital Pathology enterprise software, a large number of pathology labs globally now gain rapid access to AI-based prognostic insights, all while streamlining laboratory processes and minimising costs.” says Fredrik Wetterhall, CEO and co-founder of Stratipath.

This collaboration between Stratipath and Roche represents a significant step forward in breast cancer diagnostics. By harnessing the power of artificial intelligence and digital pathology, the two organisations are committed to improving the lives of breast cancer patients worldwide.

Stratipath is an AI company dedicated to revolutionising cancer treatment decisions and enhancing patient outcomes by assisting physicians in delivering optimal treatment to every patient. Stratipaths pioneering solutions and AI-powered precision diagnostic software platform transform tissue sample analysis, enabling breakthrough insights for enhanced and faster patient stratification across healthcare, clinical trials, and drug development. By expanding the reach of precision medicine, Stratipath aims to make this advanced healthcare approach accessible to a wider patient population. Founded as a spin-out of Karolinska Institutet in Stockholm, Sweden, Stratipath is built upon years of groundbreaking research and development.

For more information, please visit www.stratipath.com.

Breast cancer

Breast cancer is the most common cancer worldwide and affects over 2.3 million women every year.¹ Over 50% of all 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 breast tumours of grade 2 as well as tumours of all grades into a low- and high-risk categories associated with risk of recurrence.^2,3

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

2. Wang Y, Acs B, Robertson S, Liu B, Solorzano L, Wählby 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.2021.09.007

3. Sharma A, Kang Lövgren S, Ledesma Eriksson K, Wang Y, Robertson S, Hartman J, Rantalainen M. Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images. Breast Cancer Research. 2024 (in press)