OneCell Diagnostics is now 1Cell.Ai
OneCell Diagnostics is now 1Cell.Ai
OncoPredikt® BreastRS™ is a next-generation diagnostic test that predicts the risk of breast cancer recurrence using AI-powered analysis of standard H&E biopsy slides. Designed for early-stage, hormone receptor-positive (HR+), HER2-negative breast cancer, this test empowers oncologists to make confident, timely decisions about chemotherapy—without the need for costly or invasive genomic sequencing.
This sequencing-free, cost-effective test enables risk stratification and treatment optimization using only digital pathology.
Non-destructive: Uses standard H&E slides—no additional tissue or molecular processing required
Cost-effective: Fraction of the cost of traditional genomic profiling
Shorter turnaround time (TAT): Fast reporting to support real-time treatment planning
Accessible: Easily deployable by pathologists without added lab infrastructure
AI-powered insights: Rapid analysis with clinically meaningful recurrence classification
Breast tumor FFPE sections are scanned, and H&E whole-slide images (WSIs) are uploaded.
Trinity AI evaluates visual and spatial gene expression patterns to classify recurrence risk as “Low” or “High.”
Results help oncologists identify patients who would or wouldn’t benefit from chemotherapy, improving personalized treatment.
Run recurrence scoring directly from pathology images
Avoid extra sequencing or tissue consumption
Review clear AI-driven gene expression overlays on digital pathology
Validated through multi-cohort studies, Trinity AI consistently demonstrates superior predictive performance compared to traditional single-modality approaches (gene expressions, imaging, clinical variables). Trinity AI achieves an impressive AUC of 0.91, emphasizing its robust predictive capabilities.
Figure: AI-driven gene intensity visualization highlights the expression levels of ER, PR, HER2, and Ki67 directly on the biopsy images.
Doesn’t consume tissue: Predictive analysis from existing H&E slides
Sequencing-free precision: No need for NGS or molecular assays
Validated performance: Proven predictive accuracy in multi-cohort studies (AUC = 0.91)
Visual biomarker intensity mapping: ER, PR, HER2, and Ki67 expression levels are highlighted directly on the image
Trained on thousands of breast cancer samples across omics, imaging, and clinical data, Trinity AI delivers:
High predictive accuracy (AUC = 0.91)
Superior performance vs. single-modality predictors
Rapid and reproducible results across institutions
