This startup provides AI-powered virtual immunohistochemistry technology that predicts biomarker expression from standard H&E stained tissue images. Their platform allows pathologists and researchers to visualize and analyze biomarker data without needing dedicated lab equipment or additional staining, streamlining diagnostic and research workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional immunohistochemistry (IHC) and immunofluorescence (IF) methods for biomarker detection are time-consuming and costly, requiring specialized lab equipment, dedicated staining procedures, and can lead to inconsistent results. Obtaining biomarker results from diagnostic labs can take weeks, and interpretation of these results can vary significantly between pathologists. Furthermore, physical IHC staining consumes scarce tissue samples, limiting the potential for comprehensive biomarker characterization.
Solution
ViewsML provides an AI-powered virtual IHC platform that predicts biomarker expression from standard Hematoxylin and Eosin (H&E) stained tissue images, eliminating the need for manual staining and specialized equipment. The platform uses deep learning algorithms trained to specific biomarkers of interest, generating virtual representations of physical IHC stains in seconds. This approach delivers spatial and quantitative biomarker expression analysis from a single H&E slide, enabling detailed per-cell analysis for multiplex biomarker studies. The platform is adaptable to any biomarker, disease area, or species, and integrates into existing preclinical and clinical workflows.
Target Audience
The primary target audience includes clinical labs, contract research organizations, and researchers involved in preclinical, translational, and clinical research, as well as those focused on developing precision medicines and diagnostics.
Features
- AI-driven virtual staining that predicts biomarker expression from standard H&E slides
- Deep learning algorithms tailored to specific biomarkers, disease areas, and species
- Rapid generation of virtual IHC stains in seconds, eliminating manual staining processes
- Spatial and quantitative biomarker expression analysis, enabling detailed per-cell analysis
- Virtual multiplexing capabilities for greater biomarker characterization
- Cloud-based platform accessible for biomarker discovery, translational research, clinical research, and virtual diagnostics assays
- Algorithms adaptable to any biomarker of interest