BostonGene logo

Digital pathology

BostonGene's AI-based digital pathology platform identifies distinct characteristics of the tumor and microenvironment, significantly reducing the need for manual analysis and minimizing variability across various types of pathology data.

H&E (hematoxylin and eosin)

BostonGene’s AI-based pathology platform detects and characterizes tissue composition, including tumor, stroma, fibrosis, fat, necrosis and other features. It enables high-throughput analysis, characterizing 100 slides in just 20 minutes.
The clusterization approach significantly improves the efficiency and accuracy of tissue slide analysis, including classification and segmentation, aiding in faster diagnosis and disease subtyping.

IHC (immunohistochemistry)

BostonGene’s AI-based algorithm accurately detects the expression of target biomarkers in both tumor and immune cells. The automated workflow can be applied to various markers, including:

  • Nuclear markers (AR, PR, FOXP3, etc.)
  • Cytoplasm/membrane markers (HER2, TROP2, HLA-DR, CD4/8, etc.)
  • Complex membrane staining (0, 1+, 2+, and 3+ cells for HER2)
  • Targets for novel antibody-drug conjugates (ADC)

MxIF (Multiplex Immunofluorescence)

BostonGene's advanced ML/AI-based pipeline for whole-slide images (WSI) provides single-cell resolution insights into tissue biology and spatial dynamics