Jessica Liu, Research Assistant at Yale University, Molecular Biophysics and Biochemistry, shared a post on LinkedIn:
“Top 7 AI/ML Applications in Digital Precision Oncology to Watch at SABCS2025.
The integration of AI/ML with digital pathology and clinical data is rapidly redefining breast cancer care. This year’s San Antonio Breast Cancer Symposium will showcase a powerhouse of clinically actionable AI tools for patient-treatment matching and risk stratification.
Here are 7 impactful abstracts and presentations covering digital precision oncology:
#1 Full Multimodal AI (GS1-09): Integrating digital pathology, clinical, and genomic data (TAILORx trial) for early/late recurrence risk assessment.
#2 AI sTILs Refinement (GS1-06): Quantifying Tumor-Infiltrating Lymphocytes (sTILs) using digital pathology to predict benefit from pertuzumab (APHINITY trial).
#3 AI Refines CDK4/6i Eligibility (PS3-06-03): Ataraxis Breast AI validates adjuvant CDK4/6i eligibility (NATALEE criteria) to guide safe de-escalation/escalation.
#4 MMAI Predicts Chemo Benefit (RF3-03): Multimodal AI (NSABP B-20 trial) identifies older patients (50+) with HR+ BC who gain a 52% relative reduction in distant metastasis risk with chemotherapy.
#5 ML Predicts ET + CDK4/6i Failure (PS3-04-29): Multicenter ML model predicts early progression on first-line treatment in advanced BC (PALMARES-2 cohort) to guide alternative initial therapies.
#6 ML for Chemo De-escalation (PS2-02-28): ML tool predicts genomic recurrence score from standard IHC, supporting cost-effective chemotherapy de-escalation in cohorts where genomic assays are unavailable (e.g., Brazilian public health).
#7 AI Streamlines Clinical Trial Enrollment (PS2-02-14): AI & NLP-powered platform screens 45k+ patients, enhancing the efficiency of identifying eligible patients for major BC clinical trials.
BONUS: Don’t miss Educational Session 15 on the current roadmap of AI in breast cancer, including pathology and patient/trial matching.
Which of these AI applications do you think will be adopted first in clinical practice? Let me know in the comments!”
Maryam Lustberg, Director Breast Center/Chief Breast Oncology at Yale University School of Medicine, shared this post, adding:
“Great summary of the most exciting AI/ML presentations in SABCS25 by our team’s.”
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