We read cancer’s signal

Starting from a deep knowledge of the disease, we have built a technological platform able to “read” the signal of cancer in blood.

What makes our approach unique


Fit for purpose clinical sample acquisition

We tailor our multi-centric clinical sample acquisition studies and trials to the end-use population. We assure that patient populations properly represent the clinical question, assure high sample quality by using strict collections protocols, accompanied with relevant clinical data needed for proper study design, biomarker discovery, cancer pattern recognition and prediction algorithm development.


Biology oriented biomarker discovery

We begin with extensive quality checked, plasma, tissue and buffy coat whole genome level profiling to discover biologically meaningful biomarkers for individual cancer types using proprietary bioinformatics tools for biomarker discovery. Our proprietary tools facilitate cutting edge, accurate biomarker discovery with the most informative DNA regions.


Multi-omics approach

We use a combined approach of methylomics, fragmentomics and microbiomics to analyse multiple biological layers of cancer signal and identify pre-cancer and early-stage cancers with high sensitivity and specificity.


Scalable commercial NGS platform and high analytical sensitivity

A targeted Next Generation Sequencing (NGS) assay workflow carried out in a certified laboratory enriches for hundreds of carefully selected biomarker regions, allowing for increased analytical signal needed for capturing rare and heterogenous early cancer signals.


Combining proprietary in-house developed cancer signal recognition tools with state-of-art machine learning algorithms

We combine knowledge of cancer and pre-cancer biology with in-house developed algorithms which score cancer signal based on identified cancer and pre-cancer patterns using read-wise methylation and fragmentation information. Cancer and pre-cancer signal scores are further used in machine learning algorithms, allowing us to achieve high accuracy early cancer detection

Other cancers

We are applying our multi-omics + computational biology + machine learning approach to capture cancer’s signal for high-burden gastrointestinal cancers, including pancreatic (Signal-P™), liver (Signal-L™), Lung (Signal-LU ™), and gastric/stomach (Signal-G™). We presented proof of concept studies for various cancers with high accuracy, including for early stages (abstract presented at ESMO 2020).

Pancreatic cancer

496 K
new cases
466 K

Pancreatic cancer accounts for nearly as many deaths (466,000) as cases (496,000) as a result of poor early-stage detection. It is the 7th leading cause of cancer deaths for men and women.

Liver cancer

906 K
new cases
830 K

With approximately 906,000 new cases and 830,000 deaths, primary liver cancer is the 6th most commonly diagnosed cancer and 3rd leading cause of cancer deaths worldwide.

Gastric/Stomach cancer

1 M
new cases
769 K

Gastric/stomach cancer is responsible for more than 1 million new cases and an estimated 769,000 deaths. Gastric cancer represents the 5th most commonly diagnosed cancer and is the 4th leading cause of cancer deaths worldwide.

Lung Cancer

2.2 M
new cases
1.8 K

In 2020, 2.206.771 new lung cancer cases have beenestimated worldwide, making lung cancer the 2nd mostcommonly diagnosed cancer worldwide. Given its poor early-stage detection and its poor prognosis at late stages,lung cancer is the 1st leading cause of cancer deaths worldwide, responsible for an estimated 1.796.144 deathsin 2020.

Source: Globocan · Global Cancer Statistics 2020