AI Tool BRIDGE Predicts Optimal Presurgical Treatments for Breast Cancer

A novel artificial intelligence tool developed at Cedars-Sinai could transform how physicians select presurgical treatments for breast cancer patients. The tool, called BRIDGE, was detailed in the journal Annals of Oncology alongside early validation data. Unlike traditional methods that classify a tumor as a single subtype, BRIDGE reads the genetic signals within a tumor to identify the presence of multiple subtypes, enabling more personalized therapy recommendations.

The implications of this announcement are significant. Breast cancer is not a single disease but comprises several subtypes, each with distinct genetic profiles and responses to treatment. Current approaches often force a heterogeneous tumor into one category, which can lead to suboptimal therapy. By recognizing the diversity within a tumor, BRIDGE could help oncologists choose treatments that target the most aggressive or dominant subtypes, potentially improving outcomes and reducing the risk of resistance.

The tool builds on other advances in cancer research being made by companies such as Calidi Biotherapeutics Inc. (NASDAQ: CLDI), which focuses on developing innovative therapies. However, BRIDGE specifically addresses the challenge of tumor heterogeneity in breast cancer. Its early validation showed promising accuracy in predicting which patients would benefit from certain presurgical therapies, such as chemotherapy or targeted agents.

If validated in larger clinical trials, BRIDGE could become a standard tool in breast cancer care, allowing for more precise treatment planning. This would not only enhance patient outcomes but also reduce unnecessary side effects from ineffective treatments. The tool represents a step toward personalized medicine, where treatment decisions are based on the unique genetic makeup of each patient's tumor.

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