Triple-Negative Breast Cancer
Triple Negative Breast Cancer (TNBC) is an aggressive subtype of breast cancer that lacks estrogen, progesterone, and HER2 receptors, making it difficult to treat with traditional therapies. Precision AI is working to advance our ML algorithms to analyze large datasets of TNBC patients, identifying unique molecular signatures and potential therapeutic targets. By integrating genomic, proteomic, and clinical data, Precision AI aims to develop personalized treatment strategies that can improve outcomes for TNBC patients, ultimately advancing the field of oncology and offering new hope for those affected by this challenging disease.
The Problems
Aggressive biology. Few biomarkers. A need for better predictive treatment pathways
Aggressive Biology
Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes. It accounts for
The 5-year survival rates drop to just
Lacks Conventional Biomarkers
Limited Precision
Patient Impact
- Increased toxicity exposure
- Disease progression delays
- Higher financial burden
- Reduced survivability
Clinical Burden
- Limited precision tools
- Minimal guidance beyond NCCN
- Case-by-case uncertainty
Equity & Underserved Populations
TNBC disproportionately impacts underserved populations, particularly black women who face worse outcomes and later diagnoses. Treatment initiation delays compound these disparities.
White women
Average time to treatment initiation
Black Women
Average time to treatment initiation
27-day delay — These extended treatment delays contribute significantly to worsened survival rates and highlight the critical need for equitable access to precision oncology solutions.
Our Approach
Precision AI's AI-powered transcriptome-wide treatment prediction
AI-Powered Transcriptome Analysis
Oncology CoPilot moves beyond limited biomarkers to analyze the entire tumor genome, enabling probability-ranked treatment recommendations grounded in systems-level molecular biology.
Whole Transcriptome Analysis
~20,000 coding genes for complete molecular profile
Network-Level Biology
Captures complex tumor biology beyond single markers
Clinically Annotated Reference
Compares against thousands of documented cancer cases
Integrated Analysis
Drug mechanisms, immunity, and microenvironment
Treatment Pathway Comparison
Watch how Oncology CoPilot streamlines patient care
Today's Standard of Care
Each ineffective treatment cycle costs patients critical time
With Oncology CoPilot
Confidence upfront. Fewer trial-and-error cycles.
By increasing confidence in treatment selection upfront,
Oncology CoPilot reduces avoidable trial-and-error cycles, enabling patients to begin well-informed, probability-ranked therapies from day one.
Ready to learn more?
