It has been estimated that the overwhelming focus on Covid-19 could cause up to 35,000 excess cancer deaths in the UK during the next 12 months (1), and Zegami, the Oxford University data visualisation spin-out which has worked on several projects focused on the detection, diagnosis, or management of cancer, is calling for greater use of technology to speed up the process of diagnosis and treatment. It says technical advances in combinatorial chemistry, genomics, and proteomics have helped to develop huge databases of biological and chemical information that can potentially dramatically improve levels of understanding of cancer biology at the molecular level. This could lead to huge improvements in how cancer is detected, diagnosed, and managed.
New research on delays on diagnosis and treatment of cancer before Coronavirus
New research(2) from Zegami reveals that of 537 people interviewed who have either suffered from cancer over the past five years or know someone who has, 31% said they felt it took too long to get the cancer diagnosis from first seeing the doctor. Nearly one in four (23%) said the length of time to receive the diagnosis was about right, and 28% said it was received quickly.
Some 29% said the diagnosis was received on the day given for getting the test results, 9% said it was received before this and 13% after. Some 49% said they couldn’t remember or didn’t know.
Overall, 19% of people who have suffered from cancer over the past five years or know people who have, say the start of treatment was delayed. Of those that said there was a delay, 21% said this was over 30 days, and 16% said it was between 21 and 30 days.
Roger Noble, CEO and founder of Zegami said: “Despite the huge effort from the NHS and the UK’s healthcare system in general, many cancer sufferers feel that they have had delays in their diagnosis and treatment. Coronavirus will have made this situation much worse given the huge focus the healthcare sector has placed on managing the crisis. To address the backlog of cancer diagnosis and treatment caused by Coronavirus and the overall growing pressure facing the healthcare service from an aging and growing population, the medical profession needs to make more use the latest technology to ensure it is as efficient as possible. Machine Learning and data visualisation, for example, have a huge role to play in terms of helping the oncology profession.
“Clinical oncologists face a huge challenge in how best to extract clinically useful knowledge from the huge and often overwhelming amount of raw molecular data that is available to them. Data visualisation and machine learning techniques can play a key role in extracting clinically useful knowledge from a heterogeneous assortment of molecular data.”
After winning Cancer Research UK’s Early Cancer Detection Sandpit Challenge in 2019, Zegami is currently working with Professor Barbara Braden (Oxford University), Dr Xiohang Gao (Middlesex University) and Dr Wei Pan (Herriot Watt University) on a range of cancer projects.
One such project is linked to oesophageal cancers, most of which are detected by endoscopy when they have reached an advanced stage and treatment is less effective and patient prognosis is poor. Detecting early cancer on the other hand, offers a significantly higher chance of cure, as the tumour can be easily removed during an endoscopic examination.
Zegami is working with researchers to train machine learning algorithms to develop a cancer detection system which identifies cancerous lesions in real-time by highlighting them on the video as the patient is being examined. This not only helps speed up the process of detection but also ensures early signs of cancer aren’t missed saving both time and lives.
Zegami launched out of Oxford University in 2016. It is currently exploring new ideas and making new discoveries for 35 clients and counting, across an ever-growing variety of sectors.
