Evening Standard
· collected 2026-10-03 · by James Briscoe and Charles Swanton
Story summary
James Briscoe and Charles Swanton from the Francis Crick Institute argue that artificial intelligence (AI) has the potential to revolutionize healthcare by improving disease prevention and treatment. They highlight AI's current roles in supporting diagnostic screening and accelerating drug discovery, but emphasize its broader potential to understand how life works—factors that keep us healthy, cause diseases to start and progress, and affect patient responses to treatments.
Given the increasing burden of chronic diseases like cancer, dementia, and heart disease, which account for approximately 70% of health and social care spending in England, there is an urgent need to shift medical focus earlier, towards preventing rather than merely managing diseases. The UK, with its strong research institutions, national health datasets, biotech sector, and collaborative environment, is uniquely positioned to leverage AI's potential.
The authors stress the importance of sustained public and charitable investment in discovery science, training researchers across biology, medicine, and computing, and fostering partnerships that link London’s scientific and clinical expertise with innovative companies and research excellence across the UK.
Written for “AI And Lifespan Improvement” on 2026-10-05,
grounded in this article and the 0 other(s) covering the same event.
AI is already improving healthcare, from supporting diagnostic screening, to accelerating drug discovery.
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AI → improve → discovery
Its true potential, however, is to help us understand how life works: what keeps us healthy, what causes disease to start and progress, why we respond differently to infection, and why two patients with the same diagnosis can experience different treatment outcomes.
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patients → help → outcomes
Our ageing population and rising incidence of chronic disease, including cancer, dementia and heart disease, are placing an ever-increasing burden on our society.
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population → age → society
Long-term conditions account for around 70% of health and social care spending in England because too much of modern medicine is spent managing disease once it’s established.
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it → account → disease
AI can help shift the focus earlier, to the biology that sets disease in motion.
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that → shift → motion
This next frontier is AI that learns from biology and nature, revealing and predicting patterns in living systems.
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that → learn → systems
And the UK, with its world-class universities and research institutions, national health datasets, medical research charities, burgeoning biotech sector and collaborative ethos, is uniquely positioned to lead this revolution.
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UK → burgeon → revolution
AI can help us understand why risk and resilience differ between people
Many human diseases evolve over decades.
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diseases → help → decades
AI can help us understand why risk and resilience differ between people, based on their genetics, sex, age, infections and exposures.
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risk → help → genetics
Cancer is a good example: by 60, the average person can harbour sover 100 billion cells with cancer-linked mutations, yet almost none become a tumour.
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none → harbour → mutations
Identifying what keeps most cells in check, while a few might escape, could unlock new avenues for prevention.
uncertain
few → identify → prevention
At the Francis Crick Institute and University College London Hospitals, researchers have used machine learning to analyse blood plasma protein data from more than 48,000 UK Biobank participants, identifying a unique protein signature that can predict lung cancer risk more than five years before diagnosis.
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that → use → diagnosis
One day, that kind of test could help target preventive treatment before cancer takes hold.
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cancer → help → hold
In Parkinson’s disease, researchers at the Crick and UCL Queen Square Institute of Neurology, working with Faculty AI, have shown that machine learning can accurately predict subtypes of the disease using images of patient-derived stem cells.
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learning → work → cells
This could pave the way for personalised medicine and targeted drug discovery.
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This → pave → medicine
We need biology-first science, with AI in the loop
Life is hard to predict.
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Life → need → loop
We need biology-first science, with AI in the loop, helping scientists make unanticipated connections, design experiments and validate results across scales, from single cells to whole bodies.
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scientists → need → bodies
This means integrating AI into experimental science, where computational models are tested against biological data, AI learns from life complexity, and discovery moves faster.
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discovery → mean → complexity
Discovery science, world-leading universities and hospitals, and AI companies are close enough for us to move ideas from lab to company to clinic.
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us → lead → clinic
Turning that proximity into progress requires sustained public and charitable investment in discovery science, researchers trained across biology, medicine and computing, and partnerships that link London’s concentration of science, clinical insight and AI talent with research excellence, data resources and innovative companies across the UK.
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that → turn → UK
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The goal is not merely to deploy AI but to reimagine how we study health and disease, enabling a shift from reactive disease management to proactive prevention and true precision medicine.
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we → read → prevention
That could mean routine blood tests that flag risk years before cancer appears, or a patient’s own cells being used to understand which treatments are most likely to help.
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treatments → mean → risk
The future of medicine depends on whether we can teach machines to understand life and use that knowledge to nurture it.
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we → depend → it
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