AI, big data and clinical trials
The
MIT Technology Review reported on a new research collaboration between
Google’s DeepMind – their machine learning division – and Moorfields Eye
Hospital in London; a renowned specialist in eye diseases and injuries.According to the article by Jamie Condliffe,
DeepMind’s artificial intelligence software will work its way through
over a million eye scans; analysing the common patterns in visual
degeneration cases. The software can detect precise detail that humans
can’t see, and of course it works much faster too. Eventually,
DeepMind’s software will learn how to spot early signs of sight loss and
catch at-risk patients while there is still time to help protect their
vision.This isn’t Google’s first foray into healthcare research and clinical trials. Their Connectivity Bridge and wearable health sensor are just a couple of other examples.The
emerging realm where technology, big data and clinical research meet is
starting to produce some of the most exciting and innovative shifts in
how we’ll conduct medical research in future. But it’s also raising new
issues around data privacy and informed consent that are catching
researchers and the wider biosciences industry off guard.We’ve
already seen examples where our enthusiasm for the potential of new
technology has led researchers to overlook data privacy risks and
concerns. DeepMind’s work with the Royal Free Hospital London, on an app
called Streams that
helps HCPs detect acute kidney injury, led to criticism that users were
not properly informed about how and what data would be shared with
Google. Similarly, NHS England’s care.data programme was delayed several times over concerns around data protection and opt-out options.Tech
giants like Google and Apple move fast – much faster than the heavily
regulated world of clinical research is used to. The opportunity
presented by new technology and big data could revolutionise healthcare
and how we do research; so how do clinical researchers and regulatory
authorities avoid standing in the way of progress, while ensuring
patient welfare and informed consent are not compromised?Some of the key questions that need to be answered are:-
How do we guarantee permanent anonymisation of data in a world where we
can’t predict how future innovations might change the nature of the
protections we put in place now?-
As we get better at detecting early signs of health risks among people
who have let researchers use their data, do we have a responsibility to
feed that information back to patients? If yes, how do we reconcile that
with the need for anonymisation and data privacy?The
answers to these questions are not simple. We may need to re-evaluate
how we work with research participants, to ensure they can benefit from
and have some ownership over research findings that are increasingly
detailed and personalised.As
we journey towards realising the full benefits of artificial
intelligence and big data for healthcare research, some things are for
sure:More than ever before, we need to maintain and build on the trust relationships between researchers and their participants.The capacity for clinical trial regulatory authorities to evolve in a timely way will truly be tested.
Tue, 24 Jan 2023
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