Oxford onco-therapeutics

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Problem

Current cancer treatment resembles a one-size-fits-all approach where most patients receive similar treatments without patent stratification. We have initially focused on bowel cancer where over 40% of the patients develop cancer relapse due to lack of patient stratification or use of a single-biomarker approach. The single-biomarker approach fails to stratify close to 50% of the patient population and also does not take into account any secondary mutations, observed frequently in cancers.

Solution

We use a combination of lab-based tests and genetic sequencing of a patient’s cancer sample and then using our AI model, we generate a response score for each patient. The response score generated will allow the oncologist to select the right treatment for a cancer patient.

Market

We have identified two sequential market entry strategies for our product. We aim to partner with pharmaceutical companies to test their new drug candidates which are in pre/early clinical development. Next, our algorithm could be used to recruit patients for later-stage clinical trials. We will therefore generate initial revenue by providing a service to the pharmaceutical companies. This strategy will also enable our algorithm to serve as a co-approved biomarker for the tested drugs.

Contact 

 Ashwin Nandakumar

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