Clinical AI Systems

AI-Powered Biomarker Assessment

Reduce ocular cognitive fatigue and eliminate subjective variability in pathological assessment through automated learning algorithms.

The Clinical Challenge

IHC Scoring is Subjective and Exhausting

Evaluating membrane tumor staining under high-power fields requires pathologists to select subjective hotspots, count thousands of individual cellular structures manually, and separate brown DAB pigmentation from violet cell nuclei visually.

~18 mins/case

Manual Pathologist Assessment

Repetitive search routines and diagnostic backlog stress increase borderline scoring error rates.

The AI Breakthrough

Automated Quantitative Precision

PCI's digital pathology assessment suite utilizes machine learning algorithms for stain deconvolution and nuclear segmentation. It returns quantitative biomarker scores in minutes.

~10 mins/case

PCI Machine-Assisted Scoring

Allows pathology laboratories to reclaim nearly 45% of evaluation schedules, ensuring highly reproducible results.

System Engineering

Under the Hood: OpenSlide & AI Networks

How our cloud-hosted engine parses multi-gigabyte scans on the fly.

01

Whole Slide Tiling

Pathologist uploads a massive scanner file (e.g., SVS or NDPI). Our backend uses OpenSlide to split the gigapixel array into local 256x256 tiles, loading only what is navigated.

02

Stain Deconvolution

The mathematical algorithm separates stained colors by isolating violet cell nuclei (Hematoxylin) from biomarker protein expression (brown DAB) into separate pixel matrices.

03

Segmental Validation

Neural networks draw cell boundaries, evaluate stain densities against calibrated reference cell plugs, and calculate tumor proportion scores.

Calibrated Ground Truth

Trained on Standardized Cell Line Plugs

Unlike other digital pathology software trained on highly subjective, inconsistent patient resections, our algorithms are trained directly on PCI's proprietary sequence-characterized reference cell lines. This establishes an absolute baseline calibrated against known genomic targets, preventing staining variations from corrupting model outputs.

99.2% Model Accuracy
<5% Inter-observer Drift

Fully Integrated Biomarkers:

p53 Validation PD-L1 (TPS/CPS) HER2 (IHC/ISH) MMR Panel (all 4) p16 cervical risk PTEN tumor loss BRAFV600E mutation MYC lymphoma
Interactive Demo

See the AI Overlays in Action

Our viewer allows pathologists to toggle raw WSI images with AI scoring masks dynamically, isolating tumor regions of interest from normal tissue compartments.

Open Slide Viewer
pcibio.ai/assessment-tool
PLUG #1 Expression 92%
PLUG #2 Expression 42%
ACTIVE PIPELINE: HER2 BREAST_BIOPSY
AI Segmentation Overlay: ACTIVE

Integrate PCI AI in Your Pathology Lab

Our digital whole slide scoring tools support standard hospital information systems and clinical API connections.

Request AI Integration Trial