Portrai Insights
Insights on data analysis, AI, and the platform we're building at Portrai.
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23 articles
[Spatial at Scale – Part 6] No-Code Alone Will Not Democratize Analysis
Democratizing analysis does not mean hiding complexity. It means enabling more people to inspect that complexity. A researcher’s work does not end when a spatial transcriptomics experiment is…
[Spatial at Scale – Part 5] Data Explosion: Memory Fails Before Storage Does
The next bottleneck in spatial biology may not be biology, but memory. You check the size of the spatial transcriptomics data files and provision sufficient disk space.
[Spatial at Scale – Part 4] Why Experimental Success Cannot Depend on “Skilled Hands” Alone
Researchers who place precious patient tissue on a slide often remain on edge until the experiment is complete. If the tissue section is damaged, preprocessing conditions vary even slightly, or an...
[Spatial at Scale – Part 3] Tissue Is Not Just a Sample. It Is Context.
Consider two lung cancer tissue sections analyzed using spatial transcriptomics. One was collected from a primary tumor before treatment, while the other came from a metastatic lesion after multi...
[Spatial at Scale - Part 2] From Seeing More to Making Better Decisions
The widespread adoption of spatial transcriptomics begins when spatial data changes consequential decisions. Anyone encountering spatial transcriptomics results for the first time is likely to be…
[Spatial at Scale - Part 1] What Is Holding Back the Mass Adoption of Spatial Transcriptomics?
What Is Holding Back the Mass Adoption of Spatial Transcriptomics? Spatial transcriptomics does not have a resolution problem alone.
Innovation in Tumor Drug Delivery Through Spatial Biology
How Far Can We Move from “Hypothesis-Driven DDS” to “Spatially Precise DDS”? Over the past two decades, tumor drug delivery systems (DDS), particularly nanomedicines, have advanced rapidly based on…
Comprehensive PortrAIgent Visium Analysis
This six-part series demonstrates an end-to-end spatial transcriptomics workflow using the PortrAIgent platform to analyze TNBC and ER+ breast cancer tissues by integrating Visium data with a…
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[Sid’s Data Journey - Part 3] Virtual Tissue Pharmacology: Bringing In Silico Drug Testing to a Patient Tissue
From target expression to tissue pharmacology: modeling how radiopharmaceuticals distribute, accumulate, and deliver dose across Sid’s tumor tissue.
WRITTEN BY
Portrai's Authors
Capturing and compounding Portrai's insights.
Daeseung Lee
CEO
Physician-scientist who left clinical practice to bring spatial biology into oncology drug discovery
Hongyoon Choi
CTO
Builds the algorithms that turn spatial transcriptomics into actionable target intelligence
Hyung-Jun Im
CSO
Nuclear medicine specialist linking imaging biomarkers to next-generation radiopharmaceuticals
Kwonjoong Na
CMO
Translates platform insights into IND-enabling decisions across oncology programs
Portrai
Official posts from the Portrai team, decoding disease with spatial intelligence