Our
multiomics
platform

We’re developing early cancer detection blood tests using our comprehensive platform that combines expertise in biological and computational sciences to look beyond tumor signals and detect the body’s early warning signs of cancer.

Our platform consists of three powerful components:

mulitiomics, machine learning, and real-world data feedback loop

Detecting the body’s early warning signs
through multiomics

Why it’s important to look beyond tumor signals

Signals differ by cancer stage

Biological signals indicating the presence of cancer can differ by cancer stage. Tumor-derived signals, such as DNA shed by the tumor, are typically more abundant in later stages of cancer. However, non-tumor-derived signals from the tumor’s microenvironment, such as proteins from your immune system or from tissues surrounding the tumor, may contribute more significantly in earlier stages of cancer.

Signals differ by cancer type

There are over 100 different types of cancer and the biological signals indicating the presence of those cancers can vary widely. For example, the amount of DNA shed by different cancer types varies by orders of magnitude, so only leveraging cfDNA is likely insufficient to detect a wide range of cancers in their earliest stages.

How Freenome's multiomics platform looks beyond tumor signals

Multiomics is the comprehensive analysis of blood by looking across multiple levels of biology, enabling us to look at both tumor-derived and non-tumor-derived signals. This holistic analysis will empower us to detect the earliest indications of cancer.

Proteomics

Transcriptomics

Genomics

Other Omics

Multiomics

Learn more about our findings using our multiomics platform

Discovering hidden patterns through machine learning

Multiomics helps us analyze the blood comprehensively to find any possible cancer signal at the earliest possible stages. This leads to billions of data points. Freenome uses advanced computational techniques and machine learning to identify complex patterns of cancer among the data points resulting from multiomics analysis.