From lab to clinic: AI-driven blood test breaks new ground in early breast cancer detection

Australia’s first commercialised lipid-based blood test for breast cancer, powered by artificial intelligence (AI), has entered clinical use marking a major step forward in non-invasive cancer diagnostics.

Developed in collaboration with Australian biotech BCAL Diagnostics, the BREASTEST plus offers a novel approach to early breast cancer detection.

“The way cancer detection works now is that it often only picks up the tumour when it is already established,” said Associate Professor Fatemeh Vafaee School of Biotechnology and Biomolecular Sciences at UNSW and Deputy Director (Science), UNSW AI Institute. “The method of detection itself relies on imaging and invasive tissue biopsies, which carry their own risks and may miss parts of the tumour. So, depending on where the needle goes in, we’re always going to miss the entire population that exists for that tumour.”

Blood-based biomarkers, in contrast, offer the potential to detect cancer well before a tumour is visible -sometimes months or even years in advance – with minimal risk and discomfort to the patient.

The BREASTEST plus transitioned from research to clinical practice in March 2025 and is now available in specialist breast clinics across Sydney and Melbourne. The test has shown particular promise in enhancing early detection among the 50% of Australian women with dense breast tissue who participate in national screening programs and where traditional imaging techniques often fall short.

Associate Professor Vafaee is spearheading a large-scale study into multi-analyte blood testing—a more sophisticated method that simultaneously analyses proteins, metabolites, and RNA rather than relying on a single biomarker. This multi-layered approach enhances both sensitivity and specificity of cancer detection.

“The challenge remains that we are trying to integrate diverse data types into a cohesive system for a holistic view of a patient’s health,” she explained. “We are highly adaptive in applying a range of methods from traditional machine learning to cutting-edge AI techniques. We’re also looking to create tests based on other biofluids such as urine or saliva.”

The Vafaee Lab is at the forefront of a growing national and international effort to integrate these AI-driven blood tests into existing screening frameworks, aiming to extend their benefits across diverse populations.

As the complexity of AI models continues to grow, the team is prioritising the development of interpretable systems – an essential step to gain acceptance within the clinical community.

“We can use AI not only to detect cancer early but to improve the lives of those who have it,” added Associate Professor Vafaee.

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