Oxford BioDynamics has launched EpiSwitch CIRT, its checkpoint inhibitor response test for oncology, in the US.
Developed using the company’s EpiSwitch 3D genomics platform, the clinical blood test is used to predict the response of a cancer patient to immune checkpoint inhibitors (ICIs), which include anti-PD-L1 and anti-PD-1 immunotherapies.
CiRT obtains a personal fingerprint of each patient’s complex cancer genomic and immune system interactions.
The company stated that the new qPCR blood test has shown 82% specificity, 93% sensitivity and 85% accuracy across many ICIs from pharmaceutical firms as well as more than 15 key oncological indications.
The EpiSwitch CiRT helps physicians make decisions regarding the start or continuation of treatment with an ICI.
According to Oxford BioDynamics, CiRT provides quick and personalised guidance using a routine blood test instead of an invasive biopsy.
How well do you really know your competitors?
Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.
Thank you!
Your download email will arrive shortly
Not ready to buy yet? Download a free sample
We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form
By GlobalDataTo clinically validate the blood test within the high complexity CLIA-certified laboratory, the company collaborated with NEXT Molecular Analytics.
Oxford BioDynamics CEO Dr Jon Burrows said: “EpiSwitch CiRT directly links clinical outcome to gene regulation and, with high accuracy, predicts patient response.
“Since one in two of us will be diagnosed with cancer in our lifetime, it is essential to develop smart testing that can rapidly predict treatment response and guide us to the most efficacious therapies and maximise benefits for patients.
“In terms of the healthcare economics, ICIs alone cost the US healthcare system $17bn annually. The ability to stratify patients based on their likelihood of response will enable the system to better manage these costs while allowing us to deliver smarter, better care to patients.”