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PathExploreTM offers unprecedented spatial and cellular resolution of the tumor microenvironment (TME) from H&E images.
PathExplore logo

PathExplore is an AI-powered panel of histopathology features that spatially characterize the tumor microenvironment (TME) with single-cell resolution1

Automated Tissue and Cell Detection

PathExplore’s underlying AI models classify both tissue regions and cell types across the entire image of a digitized H&E slide.

HIFs – Structured, Standardized, and Scalable TME Characterization

The number of cells and their spatial orientation within or near certain tissue regions are delivered as a panel of structured metrics called human interpretable features (HIFs).

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Introducing PathExplore

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Robustly Trained, Trusted by Partners

>6.5 million

pathologist annotations

>66K slides

used for training

120K+ slides

deployed in research to date


scientific presentations and publications

PathExplore delivers hundreds of standardized, reproducible HIF metrics to unlock insights into TME biology

Results across large-scale datasets can be achieved in days or weeks rather than months

PathExplore will continue to grow the number of disease areas and feature sets including nuclear morphology, stromal subtyping, and TLS

Harmonized features (i.e., Tumor Infiltrating Lymphocytes) across tumor types enables analysis of shared disease pathways and resistance mechanisms

Available across 8 cancer indications for scalable analysis across multiple development programs

Standardized TME spatial features for comparable analyses across eight cancer indications.

Scalable and efficient quantification of millions of cells across the entire H&E image.

Proven Research and Applications


Improve quantification of established biomarkers and disease signatures.


Identify novel histological biomarkers and drivers of therapeutic efficacy.


Scale research and insights across disease areas and drug programs.

Case Study 1

PathExplore HIFs demonstrate biologically-relevant correlations with multi-omic hallmarks of cancer (HoC)

PathExplore HIFs demonstrate biologically-relevant correlations with multi-omic HoC.

Correlations between HIFs and HoC highlight the link between underlying disease biology and histopathology features. These insights may power new or deeper investigations behind mechanisms of action, biomarker expression, and patient outcome prediction.
Full Abstract Here

Case Study 2

Novel H&E-Based Biomarkers

PathAI's analysis of the TME revealed a relationship between cancer cell nuclear morphology and outcomes in high-grade serous ovarian cancer (HGSOC).

Greater variability in nuclear size was correlated with reduced overall survival, providing support for the predictive power of biological events identified by HIFs.
Full Abstract Here
nuclear morphology chart

Rapid, Scalable Deployment of PathExplore

PathExplore Data Access Program

PathAI is now offering academic researchers access to PathExplore's human interpretable features (HIFs) that have been deployed on publicly available samples from The Cancer Genome Atlas (TcGA). This program allows researchers to access PathExplore HIFs from H&E whole-slide images via our platform and link them with genomic and outcomes data across eight cancer indications: NSCLC, Breast, CRC, Melanoma, Gastric, RCC, PDAC, and Prostate.

This data is free to academic researchers, and we also offer a license for non-academic partners. To learn more and apply to the PathExplore data access program, please contact [email protected]. If you are an industry-based researcher interested in licensing these data, please reach out to [email protected]
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Connect with our business development team to learn more about PathExplore.
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PathExplore is for research use only. Not for use in diagnostic procedures.