Test predicting effective treatments from routine cancer samples approved

A new AI-based test that can predict the most effective treatment from images of routine cancer samples has been approved for use in the UK and EU, speeding up diagnosis and reducing the need for lab testing. Developed by Cambridge-based company Panakeia, the PANProfiler test analyses digital images of routinely collected breast tumour samples that are normally checked down a microscope by a trained pathologist to determine the presence of cancer. The usual next step would be to send a further sample for lab testing to identify the best treatment approach, with the results taking days or weeks and costing hundreds or even thousands of pounds depending on the test. However, the PANProfiler Breast test skips the need for testing by directly predicting whether the cancer contains ER or PR receptors, marking the patient out as a candidate for hormone therapy, or HER2, targeted by the drug Herceptin. All this happens from the original digital image in a matter of minutes, with accuracy comparable to lab testing, making the PANProfiler test far faster and significantly cheaper than existing tests.