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For Andrew Morris, being appointed president of the UK Academy of Medical Sciences this spring came “at a particularly exciting time for medical research”. In his view, “the breadth of new technologies emerging is just remarkable.”
From genomics to gene editing, stem cells to virology, immunology to neurotechnology, scientific papers are pouring out of the world’s biomedical labs more rapidly than ever. At the same time, insights are emerging from the analysis of multiple sources of health data, from clinical trials to patient records and social and environmental statistics — enhanced with the addition of artificial intelligence.
“The fusion of biology with computational science, social science and medical science means that we have a whole generation of new tools coming down the track,” says Morris, who is professor of medicine at Edinburgh university and director of Health Data Research UK. “If we get this right, it could be one of those inflection points in medicine as important as the discovery of antibiotics.”
Getting it right means, above all, maintaining the trust of everyone with a stake in the system. “Countries that can curate their data in a trustworthy way will produce models which are more accurate, more representative and more impactful in terms of patient and public benefit,” he argues.
“Other industries have done this better than healthcare. For example, I could send you £100 in two minutes because your bank and mine subscribe to Swift [the international financial transfer system]. It’s about standards, interoperability, security, ethics and governance of trustworthy data.”
Up until now, healthcare innovations have tended to back up the “law” identified by American futurist Roy Amara 50 years ago: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”
For example, for decades, the media has buzzed with news of technologies that promised to transform healthcare — such the first draft of the human genome which was met with a crescendo of excitement when it was released almost 25 years ago. However, today, most patients encounter little new technology when they see their doctor, observes David Weinkove, bioscience professor at Durham university.
The pandemic may have accelerated the adoption of a few technologies, such as RNA vaccines and Covid infection tests, “but genomics hasn’t really hit the clinic yet”, Weinkove says. “You don’t go routinely to your GP and get your genome sequenced — and then the doctor looks at the results and says: ‘This is what you’ve got.’”
Weinkove also chairs the British Society for Research on Ageing, a charity embarking on a campaign to raise funds for projects “that will impact the lives of the general public.” He says: “Evidence-based research is needed to understand how people can stay healthier for longer — and then we must make that knowledge available to as many people as possible.”
“The problem with applying new technologies to medicine is that they have to be relatively cheap to run and they’ve got to be understandable by medics,” Weinkove explains. “One reason why we don’t use genome sequencing is that we don’t know enough about gene function to know what [a particular] sequence actually means for a patient and their treatment.”
He says high blood pressure is the best example of “something that you can actually measure easily and treat with drugs that work in a way that we understand. We know that long-term high blood pressure is a risk factor for cardiovascular disease. We need more things [like this] that are measurable, treatable and understandable.”
Neurotechnology is a futuristic field that illustrates Amara’s law in action. Clinical trials of brain-computer interfaces (BCIs) that can restore some mobility to paralysed patients began in the early 2000s. These devices, implanted under the skulls of several disabled patients, decipher enough neural activity to restore some movement to paralysed limbs, control a simple robot or computer keyboard, or give a synthetic voice to someone who cannot speak.
Back in 2012, researchers at Brown University in the US enabled two tetraplegic patients, Cathy and Bob, to manipulate objects with a robotic arm by thinking about the movements required. A video of Cathy smiling as she managed to lift a drink to her lips for the first time in 15 years won hearts around the world.
Since then, medical BCIs have developed further in several university and company labs, including Elon Musk’s Neuralink. But researchers have deliberately progressed slowly — monitoring the effect of brain implants intensively on small numbers of volunteers. Anyone who expected cyborgs to emerge rapidly from their early success will have been disappointed.
Leigh Hochberg, one of the original BCI pioneers at Brown, and still closely involved in the field as director of the Center for Neurotechnology at Massachusetts General Hospital, estimates that, since clinical research started, only 50 or so volunteers worldwide have received a long-term BCI implant.
“One of the advantages of this technology is that we learn a tremendous amount from each trial participant,” says Hochberg. “Ten years ago, when asked when these devices would be [widely] available, my answer was that it would take decades. The field is still in its early days but, now, I think it’s only a few years before the first of these devices will become available to people who will benefit, after a successful clinical trial.”
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