Purensis is building an integrated platform to generate deep, unbiased spatial proteomic data at scale.
Most approved drugs target proteins, but proteomic data measured spatially across human tissue at scale does not currently exist. Public spatial datasets are dominated by transcriptomics, narrow marker panels, or small cohorts. Models for target discovery, response prediction, and tissue biology are constrained by the absence of this data.
Purensis combines whole-slide imaging, AI-guided laser microdissection, and proteomic measurement in a single automated workflow. Each tissue region is captured with paired imaging, spatial coordinates, and a proteomic readout. The platform is being built to produce these measurements without panel preselection, at depths and throughput not feasible by manual methods.
Scaled.
Automated, unattended operation across full tissue cohorts.
Unbiased.
Region-agnostic measurement; no preselected antibody panel.
Deep.
Proteome-scale measurement per region — thousands of proteins, not dozens.
Engineers and scientists building the spatial proteomics data layer.
Founder & CEO
Engineering
Science
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Working on AI for drug discovery, or generating spatial data at scale? Contact us.
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