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Perception Medicine

Perception Medicine offers an AI-driven platform that converts standard H&E pathology slides into virtual spatial omics data, delivering single‑cell resolution proteomic and transcriptomic maps without additional reagents. By extracting predictive biomarkers, immune phenotypes, and cellular subtypes, the system enables large‑scale, quantitative analysis of tumor microenvironments for cancer treatment decisions and drug discovery. Users simply upload a slide and receive visualized spatial insights ready for downstream research.

Palo Alto, CaliforniaFounded 2024350+ followers
Updated 1 month ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Pathology labs rely on multiple staining protocols, specialized reagents, and expensive instrumentation to extract spatial omics information, limiting the scalability and speed of biomarker discovery and predictive diagnostics for cancer treatment.

Solution

Perception Medicine offers an AI-driven platform that converts a single standard H&E‑stained tissue slide into high‑resolution spatial proteomic and transcriptomic maps without additional reagents or equipment. Users upload the digital slide, and multimodal deep‑learning models infer cellular subtypes, immune phenotypes, and predictive biomarkers at single‑cell resolution. The resulting spatial omics data are visualized through an interactive web interface, enabling researchers and clinicians to perform virtual assays and large‑scale tumor microenvironment analyses directly from existing pathology workflows. By eliminating the need for multiplexed staining and specialized hardware, the platform accelerates drug discovery and supports precision oncology decision‑making.

Target Audience

Primary customers are oncology research laboratories, pharmaceutical drug discovery teams, and clinical pathology departments seeking scalable, predictive spatial biomarker analysis.

Features

  • Single‑slide input: accepts standard H&E images, no extra staining or tissue required
  • Multimodal AI engine that predicts spatial proteomics and transcriptomics from histology
  • Single‑cell resolution mapping of cellular subtypes, immune phenotypes, and predictive biomarkers
  • Interactive visualization dashboard for spatial data exploration and virtual assay design
  • Cloud‑based processing compatible with existing laboratory digital pathology infrastructure
  • Scalable analysis pipeline enabling high‑throughput biomarker discovery across large cohorts
This profile is AI-generated and may contain inaccuracies.