Freenome has teamed up with Siemens Healthineers to jointly identify appropriate biomarkers to improve the detection of breast cancer.

The collaboration will use Freenome’s machine learning and multi-omics capabilities to detect early breast cancer.

It will use epigenetic, proteomic, genomic, immunologic and other data types to enhance the accuracy of screening tests, augmenting existing imaging technologies.

Both parties will combine their imaging and clinical data with molecular data to identify new suitable markers of breast cancer, in line with those identified using current imaging.

Freenome will model its multi-omics data, using artificial intelligence and machine learning technologies, to help researchers identify effective biomarkers.

Freenome CEO Mike Nolan said: “Siemens Healthineers is an established leader in the development of imaging and diagnostic technologies, especially in breast cancer screening with more recent improvements leveraging 3D mammograms or digital breast tomosynthesis.

“This collaboration will give us even more insights on how we can incorporate unique data types to address the unmet medical needs for one of the most common cancers.”

Freenome is a biotechnology company that provides the most comprehensive multi-omics platform for early cancer detection, through a normal blood draw.

The company has expertise in molecular biology, computational biology and machine learning to detect disease-related patterns among cell-free biomarkers.

Siemens Healthineers is a medical technology company based in Erlangen, Germany, engaged in providing AI-supported applications and digital offerings.

The company claims that the new applications will enhance its in-vitro diagnostics, image-guided therapy, in-vivo diagnostics, and advanced cancer care capabilities.

Siemens Healthineers centre for innovation in diagnostics (CID) head Rangarajan Sampath said: “With their multi-omics approach in molecular diagnostics, Freenome is our partner of choice for this study.

“Our collaboration in the identification and development of new biomarkers will allow us to work together toward a new patient-centric pathway to diagnose early-stage breast cancer.”