POSTMAN
In silico spatial proteomics from H&E
Request Early AccessFrom H&E to 180+ spatial protein maps
POSTMAN takes a standard H&E image and predicts virtual multiplex immunofluorescence across 180+ protein biomarkers, without touching the tissue.
Trained on a dataset of 20,000 slides of paired same-section H&E + mIF data, the largest in the field. Spanning immune, structural, and functional markers across pan-cancer, multi-tissue, multi-site cohorts.
Why this matters
Multiplex immunofluorescence is expensive, takes days, and damages the tissue in the process.
Most clinical samples are degraded, exhausted, or impossible to re-acquire, especially in retrospective cohorts.
Millions of patients. Decades of trials. Spatial proteomics on almost none of them.
1B parameter generative vision model. Fine-tunable to your indications and target panels.
Validation
We validate POSTMAN not just on pixel-level concordance with held-out ground truth, but on the metrics that matter: biomarker prediction, patient stratification, and clinical outcome prediction using imputed data.
Applications
Virtual Target Screening
Predict drug target expression across H&E slides where the drug is not yet approved.
Patient Stratification
From one H&E slide, predict all targetable markers simultaneously to guide treatment selection.
Population-Scale Drug Repurposing
Virtually stain entire archived tissue microarray banks to identify new therapeutic opportunities.