Angharad Thomas

Head of Media Relations, Charities Aid Foundation

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WHAT DOES THERESA MAY'S SPEECH ON ARTIFICIAL INTELLIGENCE AND TECHNOLOGY IN THE HEALTH SECTOR MEAN FOR CHARITIES?

22 May 2018

Theresa May gave a speech on technology in the health sector recently. And it was a big one – she set rigorous targets for using artificial intelligence to diagnose prostate, ovarian, lung and bowel cancer at an early stage. This will be achieved by utilising new technologies to compare individuals’ genes and lifestyles, as well as merging medical records with national data.

The ultimate aim will be to cut UK cancer deaths to the tune of 10% by 2033, equivalent to 22,000 lives saved each year. This is a progressive target, continuing the recent trend of the UK Government engaging with civil society and modern technologies such as artificial intelligence.

At CAF our Giving Thought think tank – which explores global technology trends and opens up new opportunities for doing good – is a vocal champion of how scientific developments can be used to make people healthier, happier and more dynamic.

It’s clear from the Prime Minister’s speech that she expects charities to play a crucial role in achieving the Government’s target of reducing cancer deaths by 10%. Fortunately, medical charities have already built up a head of steam, acting as early adopters of exciting technologies such as machine learning and artificial intelligence. 

A wide range of projects have been launched over recent years. So, who are some of the charities involved, and how are they helping patients?

TECHNOLOGY IN HEALTH CARE AND EXISTING PARTNERSHIPS

One such partnership that stands out is between Moorfields Eye Hospital and Google DeepMind. Their initiative applies Google’s deep learning algorithms to the large numbers of Optical Coherence Tomography (OCT) scans taken each year, in order to develop more effective diagnostic tools. This will greatly reduce the time required for experts to assess all aspects of the scan, by spotting patterns and categorising results for faster diagnosis. The scheme aims to analyse one million de-personalised eye scans using machine learning in this way.

Another area of medical research where charities are playing a key role is around drug discovery. Traditionally, finding new drug treatments is enormously expensive and time-consuming, as it involves predictive guesswork about which molecules and substances may have the desired effect in combating a particular condition, which then has to be tested rigorously through experimental trials.

The potential benefit of using AI is that it enables accurate modelling of things like protein folding, which plays a huge part in the efficacy of many drugs and which was previously very difficult to predict. This means that it’s possible to estimate the likely effectiveness of a proposed drug much more accurately, and thus reduce the time and cost of focusing in on the most promising candidates. The charity LifeArc has partnered with the University of Cambridge on a new project along these lines, which seeks to identify and validate new drug targets in immuno-oncology and respiratory diseases using machine learning.

Parkinson’s UK, meanwhile, announced in March 2018 that it was partnering with Benevolent AI to explore the application of machine learning to data from smart phone handsets, which can detect miniscule movements when kept on someone’s person, and which could lead to new early warning indicators for the onset of Parkinson’s Disease.

RESPONSIBLE PATIENT DATA COLLECTION

Despite the successful implementation of the above mentioned schemes, it would be remiss not to strike a note of caution on the challenges of using patient data responsibly and proportionately. This is of course a topical issue, considering the introduction of GDPR’s new standards on Friday 25th May. A partnership between Google DeepMind and the Royal Free NHS Foundation Trust, over an app DeepMind developed to identify patients at risk of kidney disease, hit the headlines last year after the Information Commission (ICO) ruled that not enough had been done to safeguard patient data. 

Evidently, it’s still early days in the battle to beat deadly diseases using AI, machine learning and other emergent technologies. But the signs so far are encouraging. The willingness of the Government to explore new avenues, as well as their drive to get technology companies working side-by-side with civil society, demonstrates a joined-up approach to policy. Medical charities are already successfully experimenting with artificial intelligence and machine learning. With continued financing and support, many people in the future will live longer, healthier lives as a direct result of this willingness to invest in promising technologies.

 

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