Oksana Kryshevich

Innovative tests to help in the diagnosis and detection of upper gastro-intestinal tract cancers

My project is based on the PinPoint test, which uses a machine-learning algorithm to calculate the probability of a patient having cancer. It can accurately rule out 20% of low-risk patients and identify 50% of those at highest risk. The intended use-case for it is as a triage tool, to help clinicians make decisions about whether to refer a patient for cancer testing. It is currently undergoing a service evaluation and the data generated from this rollout will be used for studies throughout my PhD. I will be investigating the end-diagnosis of patients who have had the test and assess the acceptability of it among patients and clinicians.

During my master’s in Medicinal Chemistry at UCL, I worked in pre-clinical drug discovery, where I developed new cytotoxic compounds to use as potential cancer treatments. After university, I worked as a Biospecimen Coordinator in GI clinical trials at the Royal Marsden Hospital, where I facilitated patient visits and organised all trial-related biological samples. My experience in a healthcare environment has shifted my academic interests from pre-clinical drug discovery to translational and implementation studies. My interests are early cancer diagnosis in primary care, implementation of new diagnostic tools and improving patient outcomes.