Seer and Korea University Showcase AI-Driven Proteomics for Multi-Cancer Screening — Seer, Inc.

Event summary

Seer and Korea University presented preliminary data at ASMS 2026 demonstrating the potential of AI-driven plasma proteomics for multi-cancer screening.
The study analyzed over 5,500 plasma samples spanning ten major cancer types and healthy controls using Seer's Proteograph® Product Suite.
Researchers reported deep and highly reproducible plasma proteome coverage, averaging more than 14,000 protein groups per sample.
The collaboration aims to analyze over 20,000 clinical plasma samples across ten of Korea's highest-incidence cancer types.

The big picture

Seer's collaboration with Korea University highlights the growing intersection of AI and deep proteomics in cancer detection. The ability to analyze large-scale, high-quality proteomic data could redefine early cancer screening strategies, positioning Seer at the forefront of this emerging field. The ongoing study's expansion to 20,000 samples underscores the potential for significant advancements in multi-cancer diagnostics.

What we're watching

Data Scale and Quality: How the depth and reproducibility of Seer's proteomic datasets will impact the reliability of AI-driven cancer screening.
AI Integration: Whether the ID-Free AI framework can effectively leverage uncharacterized mass spectrometry data for biological pattern recognition.
Clinical Translation: The pace at which these findings will transition from research to practical multi-cancer screening applications.