On November 24, 2025 Artera, the developer of multimodal artificial intelligence (MMAI)-based prognostic and predictive cancer tests, reported that three abstracts will be presented at the San Antonio Breast Cancer Symposium (SABCS), held December 9-12.

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The studies collectively highlight the prognostic and predictive power of Artera’s MMAI model to help personalize treatment decisions, particularly in evaluating chemotherapy benefit in post-menopausal women. Leveraging data from four independent Phase III trials across Germany, Austria, and North America, these studies validate the performance of this unique AI model across more than 7,000 patients.

"These abstracts hold tremendous weight as they cover a diverse set of patients with HR+ early breast cancer, giving clinicians a lot of confidence in the validity of these results," said Prof. Nadia Harbeck, Director of the Breast Center at LMU University Hospital in Munich, Germany. "Traditional approaches can result in patients, especially those who are post-menopausal with node-negative tumors, receiving chemotherapy with limited benefit while still facing significant toxicities. It’s exciting to witness the emergence of new technologies that allow us to deliver the optimal breast cancer care."

Approximately 1 in 8 women (13%) in the U.S. will develop invasive breast cancer at some point in their lives, and many face complex treatment decisions. Chemotherapy carries well‑documented side effects, including neuropathy, risk of infection, and, for younger women especially, infertility and impaired fertility potential. These risks underscore the need for tools that help clinicians tailor treatment decisions, ensuring each patient receives care that is necessary, appropriate, and aligned with their unique clinical profile.

"Advancing precision medicine means ensuring every patient can benefit from individualized care," said Andre Esteva, CEO of Artera. "As we validate this technology across countries and cancer types, we’re showing that precision medicine can be more personalized and accessible while helping clinicians avoid unnecessary treatments without added time, cost, or complex processes."

Presentations at SABCS 2025

Poster Spotlight 11 (PD11-01) Development of a Multi-Modal Artificial Intelligence (MMAI) Model for Predicting Distant Metastasis in HR+ Early-Stage Invasive Breast Cancer (Abstract #1251)

Demonstrates the development of Artera’s MMAI model using data from over 12,000 patients enrolled in six Phase III clinical trials conducted in the United States, Germany, and Austria. The model effectively stratifies patients by 10-year risk of distant metastasis, identifying high-risk individuals who may benefit from closer monitoring, while 68% of patients were classified as low-risk and achieved an estimated 10-year DM-free survival of approximately 95%. These findings show the model’s potential to provide actionable prognostic information across diverse, international populations.

Poster Session 3 (PS3-04-08) Independent Validation of a Pathology-Based Multimodal Artificial Intelligence Biomarker for Predicting Risk of Distant Metastasis in Postmenopausal, Estrogen Receptor-Positive, Early-Stage Breast Cancer Patients: Analysis of the ABCSG Trial 8 (Abstract #1410)

Focuses on postmenopausal patients in the ABCSG 8 trial, a prospective study of individuals receiving endocrine therapy only. MMAI successfully classified patients into low, intermediate, and high-risk groups, with corresponding 10-year DM-free survival rates of roughly 95%, 89%, and 77%, respectively. Validation confirmed robust performance across clinical subgroups, including lymph node status, tumor grade, histology, and proliferation markers. The study further highlights the advantages of MMAI as a non-tissue-destructive, fast-turnaround test, providing an accessible alternative to more costly genomic assays.

Rapid Fire 3 (RF3-03) Evaluation of a digital pathology-based multimodal artificial intelligence model for prognosis and prediction of chemotherapy benefit in node-negative, hormone receptor-positive breast cancer patients: analysis of the NSABP B-20 trial. (Abstract #3685)

Evaluates MMAI’s ability to predict benefit from chemotherapy in node-negative HR+ patients in the NSABP B-20 trial. Among patients aged 50 and older, MMAI high-risk individuals experienced a 52% relative reduction in 10-year DM with chemotherapy, while MMAI low-risk patients derived no additional benefit. These findings demonstrate MMAI’s potential to guide personalized treatment decisions, helping clinicians avoid unnecessary chemotherapy for low-risk patients while identifying high-risk patients who are most likely to benefit.

Artera will be exhibiting at booth #1525 during SABCS, where attendees can learn more about the MMAI platform and the ArteraAI Breast Test.

(Press release, Artera, NOV 24, 2025, View Source [SID1234660922])