A new AI tool developed at Cedars-Sinai could change how doctors select the most suitable presurgical therapy for breast cancer patients. The tool, named BRIDGE, was detailed in Annals of Oncology alongside early validation data. It reads genetic signals inside a tumor to identify which subtypes are present, rather than forcing the whole mass into one category.
This approach addresses a key challenge in breast cancer treatment: tumors are often heterogeneous, containing multiple subtypes that may respond differently to therapy. By using machine learning to analyze gene expression patterns, BRIDGE can pinpoint the specific subtypes within a tumor, enabling more targeted treatment planning. Early validation data suggest the tool accurately identifies subtypes, which could lead to better outcomes and fewer unnecessary side effects from broad treatments.
The development comes as other companies advance cancer-fighting technologies. For instance, Calidi Biotherapeutics Inc. (NASDAQ: CLDI) focuses on developing novel stem cell-based platforms for cancer therapy. Such innovations underscore the growing role of AI and biotechnology in personalizing cancer care.
The BRIDGE tool represents a significant step forward in precision oncology, potentially sparing patients from ineffective treatments and improving survival rates. Further studies are needed to validate its clinical utility, but the early results are promising for the future of breast cancer management.
