ArteraAI Breast Receives FDA Clearance for Risk Assessment in HR+, HER2– Breast Cancer

On May 6, the U.S. Food and Drug Administration (FDA) cleared ArteraAI Breast for use in patients with early-stage hormone receptor (HR)–positive, HER2-negative invasive breast cancer.

ArteraAI Breast is the first FDA-cleared digital pathology–based risk stratification tool for patients with breast cancer. The multimodal AI model generates a risk score estimating a patient’s likelihood of developing distant metastasis using digitized histopathology images and clinical variables. Based on a predefined cutoff, the tool stratifies patients into low- or high-risk groups for distant metastasis.

According to the company, ArteraAI Breast is designed to help clinicians gain additional insight into a patient’s prognosis within established clinical decision–making frameworks.

“This clearance represents an important advance on the road to personalizing treatments for patients with early-stage breast cancer,” stated Eric Winer, MD, medical oncologist and Director of Yale Cancer Center. “Using AI and digital pathology has the potential to streamline operational workflows while creating a strong interdisciplinary linkage between oncology and pathology. This approach may further improve clinicians’ ability to help patients make the best treatment decisions.”

Research on the development and evaluation of the multimodal model was presented at the 2025 San Antonio Breast Cancer Symposium. The model was developed using digitized pretreatment biopsy and surgical slides, along with clinical variables, from 8,616 patients in four phase III trials. The risk score was subsequently validated in cohorts from two additional phase III trials.

The multimodal AI model risk score was significantly associated with the risk of distant metastasis. Based on predefined cutoff points, patients could be classified as low, intermediate, or high risk.

In a separate analysis presented at the 2025 San Antonio Breast Cancer Symposium, the model demonstrated potential utility in guiding chemotherapy treatment decisions for select patients. Among patients aged 50 years or older with node-negative, HR-positive early-stage breast cancer enrolled in the NSABP B-20 trial, those classified as intermediate or high risk by the multimodal AI model were more likely to benefit from treatment with tamoxifen plus cyclophosphamide, methotrexate, and fluorouracil chemotherapy.

The findings support the potential use of the model as a lower-cost alternative to genomic testing for predicting chemotherapy benefit in older patients with HR-positive early-stage breast cancer.

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