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Using molecular biology
and machine learning to

detect cancer


Seeing What Humans Cannot

By decoding cell-free biomarker patterns of once unthinkable complexity, Freenome’s blood tests are powered by our multiomics platform and designed to detect cancer at its earliest stages to help clinicians optimize the next generation of precision therapies.

 
 

How our multiomics platform works

By training on thousands of cancer-positive blood samples, our multiomics platform learns which biomarker patterns signify a cancer’s stage, type, and most effective treatment pathways.

Training on healthy samples helps us establish what a normal composition of cell-free biomarkers should look like.

 
 

What we detect

Freenome’s multiomics platform detects key biological signals from a routine blood draw. The platform integrates assays for cell-free DNA, methylation, and proteins with advanced computational biology and machine learning techniques to understand additive signatures for early cancer detection.

This strategy incorporates a multidimensional view of both tumor- and immune-derived signatures that enable the early detection of cancer, instead of relying only on tumor-derived markers, which may miss the early signs of cancer.

 

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Mapping the multiomics of blood

 

cfDNA

Provides insights into immune response and tumor heterogeneity.

cfRNA

Reveals gene expression changes in the body associated with tumor formation.

Proteins

Provides a higher-order dimension to immunogenic and oncogenic signals.

 
 

Detecting beyond the tumor

Freenome’s multiomics platform allows it to process all of these analytes that come from immune and tumor in the blood, giving clinicians a clearer picture of early-stage cancer and generating powerful therapeutic insights.