Founded by Yue Dai
Predict spatially resolved protein marker maps directly from standard hematoxylin and eosin slides
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You can use Strand AI to predict spatial proteomics maps directly from routine hematoxylin and eosin tissue slides. Instead of cutting fresh tissue sections or running expensive multiplex immunofluorescence assays, the system generates virtual biomarker channels computationally across whole patient cohorts. You send digitized whole slide images, and the dry lab service performs cell segmentation, phenotyping, and tumor microenvironment characterization. This allows research teams to profile archived biopsy collections, stratify patient populations, discover biomarker targets, and prioritize samples before investing in wet lab testing.
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