Biotechnology firm Oxford BioDynamics has signed its fifth collaboration agreement for the development of predictive biomarkers for immuno-oncology (IO) therapeutics.
The deal with a major US biopharmaceutical company demonstrates value of the range of immuno-oncology biomarker applications recently developed using EpiSwitch platform.
EpiSwitch is an industrial platform for the discovery, evaluation, validation and monitoring of a novel class of epigenetic biomarkers called chromosome conformation signatures (CCCs).
IO is said to be a fast-growing field with multiple therapies for the treatment of cancers, specifically immune checkpoint inhibitors.
The stratification of patients is required to accurately exclude which will not respond to IO therapeutics. Oxford BioDynamics has multiple biomarker-based predictive patient stratifications for several IO assets, including both PD-1 and PD-L1 inhibitors.
Oxford BioDynamics will use its EpiSwitch platform to provide high resolution mapping of epigenetic profiles in patients, enabling to gather information from other regulatory modalities to provide clinical benefit of treatment.
Oxford BioDynamics CEO Christian Hoyer Millar said: “We are pleased to have entered into this new agreement with a major US biopharmaceutical company in the dynamic field of immuno-oncology, as there is a high need for the identification of epigenetic biomarkers to evaluate drug performance in therapeutic development programmes.
“This agreement represents the fifth contract we have signed in IO, continuing to validate the potential of our EpiSwitch technology in this space.”
Oxford BioDynamics is engaged in the discovery and development of epigenetic biomarkers for use within the pharmaceutical and biotechnology industry.
The firm’s EpiSwitch platform will help enhance the drug discovery and development process, improve the success rate of therapeutic product development and benefit from personalised medicine.
According to the company, the EpiSwitch platform holds capacity to reduce time to market, failure rates and the costs at every stage of drug discovery.
The technology is said to provide significant insights into disease mechanisms for drug discovery and product re‐positioning programs and allows personalisation of therapeutics for patients in the context of challenging pricing environments.