Oxford BioDynamics has announced the successful clinical validation and US launch of its Checkpoint Inhibitor Response Test (EpiSwitch CiRT).

The first-of-its-kind clinical blood test predicts the likelihood of a cancer patient’s response to an essential, widely used class of therapeutics – Immune Checkpoint Inhibitors (ICIs) – including anti-PD-L1 and anti-PD-1 immunotherapies. The robust EpiSwitch qPCR blood test has demonstrated best-in-class performance, with high sensitivity (93%), specificity (82%), and accuracy (85%) across several ICI’s from multiple pharmaceutical companies and more than 15 key oncological indications.

Every cancer patient travels a unique path from diagnosis to treatment that requires making complex decisions with their doctor. Many patients are considered for ICI immunotherapy – an alternative approach to chemotherapy or radiation – that works with a patient’s immune system to fight cancer. ICIs have been the paramount breakthrough in cancer treatment and are now used against more than 15 types of cancer. However, typically less than 1 in 3 patients receiving ICIs shows any benefit; instead, many experience serious toxicity events affecting almost any organ as well as facing significant financial burden to pay for these specialised biologic medicines.

Rapid expansion of the checkpoint inhibitor class (with 8 currently approved and many more in the review pipeline) has led to appeals by the FDA and leading oncologists for harmonization and coordination of the latest ICI developments. Robust and universal prediction of response to ICI treatment is seen as one of the key tools for harmonization: assisting physicians in their decisions on choices of treatment, protecting patients, leading to greater efficiency in drug development, reducing costs and protecting valuable resources.

Dr Jon Burrows, CEO of Oxford BioDynamics, said, “Oxford Biodynamics Checkpoint Inhibitor Response Test (EpiSwitch CiRT) is a very important step forward for precision medicine. 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 maximize benefits for patients.

“In terms of the healthcare economics, ICIs alone cost the US healthcare system US $ 17 billion 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.”