PathAI

Patient biopsy slides are scanned at the trial site.

Images are uploaded to PathAI Biopharma platform.

AI algorithm quantifies biomarker expression (e.g., PD-L1).

Platform generates a validated score for inclusion/exclusion criteria.

Sponsor receives structured data for regulatory submission.

Upload H&E stained breast tissue slides.

AI identifies regions of high mitotic activity.

Automated mitotic figure count is generated.

Pathologist reviews the AI-identified 'hotspots'.

Final Nottingham Grade is calculated with AI assistance.

Batch digitize thousands of biobank slides.

Run PathAI feature extraction algorithms.

Query the dataset for specific morphological signatures.

Correlate AI features with clinical outcome data.

Identify new predictive biomarkers for drug response.

Prostate core biopsies are scanned and analyzed pre-review.

AI flags slides with suspected Gleason pattern 3 or higher.

Cases are sorted in the LIS based on urgency and probability of cancer.

Pathologists focus first on high-risk cases.

Overall turnaround time (TAT) is reduced by 30%.

Collaborative development of a custom AI model for a novel drug target.

Validation of the model in Phase II/III trials.

Submission of the AI algorithm as a Medical Device (SaMD) to FDA.

Launch of the AI model as the official CDx for the drug.

Global deployment to labs via AISight.

Primary lab scans slides and uploads to cloud.

Remote specialist accesses the WSI through AISight viewer.

Specialist uses AI measurement tools to confirm diagnosis.

Collaborative review via screen-share or shared annotations.

Diagnostic report is finalized and sent to the treating physician.

Digitize multi-plex IHC slides.

Map spatial proximity of CD8+ T-cells to tumor cells.

Calculate 'Inflamed', 'Excluded', or 'Desert' phenotypes.

Generate a spatial biology report for clinical researchers.

Adjust treatment protocols based on spatial data.