EDX Medical launches AI breast cancer test in UK

EDX Medical Group plc

EDX Medical Group plc (LON:EDX), which develops and supplies innovative digital diagnostic products and services to improve the early detection and treatment of major diseases, has announced the Company is launching in the UK the first prognostic test that assesses both short and long-term risk of breast cancer recurrence. The test provides an assessment of long-term risk up to 15 years.

The Caris MI Clarity test leverages AI to transform how the risk of breast cancer recurrence is understood for postmenopausal patients with HR-positive/HER2-negative, node-negative early-stage breast cancer, and has been validated by robust clinical data from tens of thousands of participants in clinical trials1 &2. The test is applied at the time of initial diagnosis.

EDX Medical has entered into an agreement with Caris Life Sciences, a leading US-based next-generation AI TechBio and precision medicine company, to supply the test in the UK.

Professor Sir Chris Evans, founder and chief scientific officer of EDX Medical, commented: “Bringing this truly pioneering test to the UK offers breast cancer patients and their doctors the opportunity to gain invaluable insight into the risk, both short and long term, of disease recurring. This test is a very significant step forward in terms of risk assessment and treatment planning for those patients.”   

Dr Mike Hudson, chief executive, EDX Medical, commented: “MI Clarity fits superbly into our portfolio of advanced diagnostic tests, which provide doctors and their patients the most accurate digital diagnostic tools to inform treatment decisions.”

“Breast cancer clinicians have long been forced to make some of the most consequential treatment decisions with an incomplete picture of how recurrence risk changes over time,” said George W. Sledge, Chief Medical Officer at Caris. “Caris MI Clarity is designed to bring early and late distant recurrence risk together in a single test at the time of initial diagnosis, when treatment decisions matter most. By leveraging AI on tumour pathology sample combined with clinical data, Caris MI Clarity has the potential to fundamentally improve how we personalize care for postmenopausal patients with HR-positive/HER2-negative, node-negative breast cancer.”

For patients with early-stage breast cancer, accurately assessing the risk of distant recurrence is essential, as distant recurrence is the primary driver of mortality and is considered to be a key factor in treatment decisions.

Using tests currently available, clinicians frequently evaluate early and late distant recurrence risk separately, adding complexity to treatment planning. The Caris MI Clarity test is based on a multimodal Artificial Intelligence (AI) model integrating image, clinical and molecular data to assess both short and long-term risk at the time of diagnosis.

The test provides distinct risk stratification into low- or high-risk categories for both early (0–5 years) and late (5–15 years) distant recurrence, enabling clinicians to understand how recurrence risk may unfold over time.

References:

  1. Sparano, J. A., Gray, R. J., Makower, D. F., Pritchard, K. I., Albain, K. S., Hayes, D. F., Geyer, C. E., Jr., Dees, E. C., Goetz, M. P., Olson, J. A., Jr., Lively, T., Badve, S. S., Saphner, T. J., Wagner, L. I., Whelan, T. J., Ellis, M. J., Paik, S., Wood, W. C., Ravdin, P. M., . . . Sledge, G. W., Jr. (2018). Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med, 379(2), 111-121. https://doi.org/10.1056/NEJMoa1804710
  1. Mamounas, E. P., Bandos, H., Rastogi, P., Lembersky, B. C., Jeong, J. H., Geyer, C. E., Jr., Fehrenbacher, L., Chia, S. K., Brufsky, A. M., Walshe, J. M., Soori, G. S., Dakhil, S. R., Wade, J. L., 3rd, McCarron, E. C., Swain, S. M., & Wolmark, N. (2023). Ten-year update: NRG Oncology/National Surgical Adjuvant Breast and Bowel Project B-42 randomized trial: extended letrozole therapy in early-stage breast cancer. J Natl Cancer Inst, 115(11), 1302-1309. https://doi.org/10.1093/jnci/djad078

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