Adoption of AI in the NHS should be faster, experts say

The adoption of artificial intelligence (AI) by the NHS should be faster, and more frameworks should be in place to get emerging technologies to as many patients as possible, experts have told MPs.

A number of senior figures from medicine and biotechnology gave evidence to the Health and Social Care Committee as part of its inquiry into cancer technology.

Committee chairman Steve Brine said the probe will determine “what forward planning needs to happen in 2023 to make sure that in 2034 and 2044 we are in a place to make use of this emerging technology”.

AI is currently being used by the NHS to detect certain cancers, and to help clinicians diagnose strokes.

Stephen Duffy, a professor of cancer screening at the Wolfson Institute of Population Health at Queen Mary University of London, told MPs there is “strong potential” for AI, particularly in areas such as reading mammograms for the breast screening programme.

However, he warned that there will be “staff issues in terms of the number of staff needed to double-read mammograms”.

He added: “Those issues aren’t going away. It seems to me that AI systems have already been shown to be very good in terms of detection of cancer on from mammograms, so they’re safe in that respect.

“People are treating it still as a research issue; that we don’t quite know enough. But my feeling is that the circumstances of staff pressures and so on, really dictate that we get on.

“Technology goes much faster than the research community can evaluate it in any case. And the trouble is that we can’t always wait because we’ve got the problem now.”

Sara Hiom, vice president of NHS implementation and external affairs at Grail Europe, shared her view on the technology in terms of the groundbreaking Galleri blood test, which can detect up to 50 cancers before symptoms start.

She said the test – which is set to be offered to one million people in England as part of a pilot programme from 2024 – is able to distinguish the difference in cancer cells and normal cells “because of constant rounds of machine learning and honing”.

“We have a classifier, which is AI-based, and that is the test that essentially looks at the patterns, is able to distinguish both between cancer and non-cancer, and then an idea of where in the body that cancer is going to be so that it can direct the subsequent diagnostic tests that will be needed.”

Prior to joining Grail, Ms Hiom spent two decades at Cancer Research UK. She said the project’s ambition is “to see a future when cancer is detected at an early stage where it can much more easily be treated and will have longer term survival”.

Marcel Gehrung is the co-founder and chief executive of biotechnology company Cyted, which has created a capsule to detect early cancer in the upper part of the digestive system.

The patient swallows the pill, which is attached to a string and contains a small sponge. After a few minutes, the casing dissolves and the sponge is pulled back up, collecting cells along the way.

He hailed the “agility” of the NHS in adopting Cyted’s technology during the Covid-19 pandemic and said it had “a significant impact on endoscopy demands across the country”.

Comparing this to the rollout of AI, he said: “I think a big point for us to look at right now is… we’ve adopted this technology in a very rapid way during Covid – and I think this is very similar for Grail and the Galleri test – what happens to these technologies next?

“They’ve been proven, they’re well evidenced – what frameworks and what strategies and programmes are in place in the NHS to really take technologies that have that traction and have that background and get it to as many patients as possible?”

In June, NHS England chief executive Amanda Pritchard said more uses of AI in the NHS are “on the horizon”.

The Government also invited NHS trusts to bid for a portion of £21 million to implement AI tools for the likes of medical imaging and decision support.

The Department of Health and Social Care (DHSC) said the technology could help cut NHS waiting lists ahead of winter.

The Government has invested £123 million in 86 AI technologies to date.