News
AI to be rolled out more widely across the NHS
The £21 million funding will be open for bids for any AI diagnostic tool that trusts want to deploy
Artificial intelligence (AI) is set to be rolled out more widely across the NHS in a bid to diagnose and treat patients faster.
NHS staff will be given the latest AI technology as part of a new £21 million fund announced by the Health and Social Care Secretary aimed at accelerating the deployment of the most promising AI imaging and decision support tools to detect conditions such as cancers, strokes and heart conditions.
The Health and Social Care Secretary, Steve Barclay, has committed to rolling out AI stroke-diagnosis technology to all the stroke networks by the end of 2023, up from 86 per cent today.
“Artificial intelligence is already transforming the way we deliver healthcare and AI tools are already making a significant impact across the NHS in diagnosing conditions earlier, meaning people can be treated more quickly,” Barclay said in a statement.
“As we celebrate the NHS’s 75th birthday and look ahead to the future, I’m focused on adopting the latest cutting-edge technology across our health and care system to ensure we can continue to deliver the best care for our patients and cut waiting times, which is one of the government’s five priorities.”
This AI Diagnostic Fund will include the use of AI tools to analyse chest X-Rays, the most common tool used to diagnose lung cancer – which is the leading cause of cancer death in the UK.
With over 600,000 chest X-rays performed each month in England, the deployment of diagnostic AI tools to more NHS trusts is hoped to support clinicians to diagnose cancer patients earlier.
In the UK, one in 15 women will be diagnosed with lung cancer in their lifetime. However, if diagnosed at an early stage, the cancer is more likely to be treated successfully.
“At a time when diagnostic services are under strain, it is critical that we embrace innovation that could boost capacity – and so we welcome the Government’s announcement,” said Dr Katharine Halliday, president of the Royal College of Radiologists.
“All doctors want to give patients the best possible care. This starts with a timely diagnosis, and crucially, catching disease at the earliest point.
“There is huge promise in AI, which could save clinicians time by maximising our efficiency, supporting our decision-making and helping identify and prioritise the most urgent cases,” she added.
“Together with a highly trained and expert radiologist workforce, AI will undoubtedly play a significant part in the future of diagnostics.”
Professor Stephen Powis, NHS national medical director, said: “The NHS is already harnessing the benefits of AI across the country in helping to catch and treat major diseases earlier, as well as better managing waiting lists so patients can be seen quicker.
“As we approach our milestone 75th birthday, this is another example of how NHS is continuing its proud history of adopting the latest proven technology to deliver better care for patients, and better value for taxpayers.”
Secretary of State for Science, Innovation, and Technology, Chloe Smith, said: “Improving diagnosis and speeding up treatments for patients through AI is a game-changer.
“The application of AI across the NHS is supported by our balanced regulatory approach and has the potential to be truly transformative, both for patients and our unrivalled health and social care workforce both now and in the decades to come.”
Dr Deb Lowe, national clinical director for Stroke Medicine, NHS England, added: “The use of AI decision support software in the initial stages of stroke care means patients get interventions quicker, reducing the likelihood of disability and saving the brains.”
The £21 million funding will be open for bids for any AI diagnostic tool that trusts want to deploy, but the government says it will have to represent value for money for the funding to be approved.
An early PET scan after one cycle of chemotherapy may help predict how aggressive breast cancer responds to treatment, a study suggests.
Research led by The Institute of Cancer Research, London and King’s College London suggests that an early scan taken after one cycle of chemotherapy could help predict how well a patient’s cancer will respond to treatment.
The study focused on patients with triple-negative breast cancer (TNBC), an aggressive form of the disease in which cancer cells lack receptors for the hormones oestrogen and progesterone, as well as the HER2 protein.
Patients with TNBC are usually treated with chemotherapy prior to surgery. While many respond well, residual disease at surgery, typically around six months later, is associated with a significantly poorer prognosis. Identifying people sooner who are unlikely to respond remains a major clinical challenge.
The research explored whether using PET imaging shortly after treatment begins, rather than relying only on MRI scans later in the treatment process, could provide earlier insight into how a patient’s cancer is responding. Twenty-two patients were recruited, with fourteen undergoing FDG-PET scans before treatment and after the first cycle of chemotherapy.
The findings, published in Clinical Cancer Research, showed that changes seen on PET scans after just one cycle of chemotherapy were strongly associated with subsequent response, including whether there was no detectable cancer, known as a complete response, by the end of treatment. Importantly, early PET response showed stronger associations with treatment outcomes than standard mid-treatment MRI scans in this study.
Being able to identify patients who are not responding well at an early stage could allow clinicians to adjust treatment sooner or consider alternative approaches. These findings may also support future strategies to better tailor treatment intensity to individual patients.
The study also compared two types of PET tracers, FDG and FLT, to determine which was most suitable. While both met the study’s technical criteria, FDG-PET was selected for further evaluation due to its better image quality, greater consistency and wider use in clinical practice.
The research also explored how imaging changes after just one cycle of chemotherapy relate to the body’s immune response to treatment. Biopsies taken before and after the first cycle of chemotherapy showed that an increase in immune cells within the tumour was strongly associated with both early PET changes and improved treatment outcomes.
The researchers emphasise that these findings now need to be validated in larger studies. Future work will aim to confirm these results in broader patient groups and explore more accessible imaging approaches, such as ultrasound, alongside PET and MRI.
Sheeba Irshad, professor of cancer immunology at King’s College London and lead of the Breast Cancer Now KCL Research Unit, said:
“In patients who had PET scans both before treatment and after the first cycle, we found that this early scan could predict whether they were likely to achieve a complete response by the end of treatment. These findings highlight the potential of early imaging to guide treatment decisions, and now need to be validated in larger, modern clinical trials.”
Andrew Tutt, professor of breast oncology at The Institute of Cancer Research, London, said:
“Research that helps us determine early who is already benefitting from standard neoadjuvant chemotherapy and who might benefit from clinical trials to find better treatments is vital. This study shows that FDG-PET may have great value in this regard. We hope to be able to design studies that further investigate and validate these findings.”
The study was supported by funding from King’s College London and Guy’s and St Thomas’ NHS Foundation Trust, Breast Cancer Now, Cancer Research UK, and Guy’s and St Thomas’ Charity.
We are excited unveil the three finalists competing for one of the Femtech World Awards’ most coveted honours: the Startup of the Year Award, sponsored by Future Fertility.
This award celebrates an early-stage company making a bold impact in women’s health through innovation, vision and execution.
The winner will be announced at our virtual ceremony on 19 June, with the decision made by a representative from category sponsor Future Fertility.
Congratulations to the shortlist and thank you to everyone who entered or nominated.
Startup of the Year Shortlist
Hello Inside is the first women’s health AI company to turn daily metabolic signals into outcomes women feel and healthcare systems reimburse.
Women’s health has long been under-researched, and current AI benchmarks fail on women’s health questions roughly sixty percent of the time.
Hello Inside built the architecture to close that gap.
Across four years and 12,000+ validated metabolic profiles, three in four women improve at least one symptom within ninety days.
They lose four kilograms in three months, moving from overweight into the healthy range. In a clinical study with Alisa Vitti’s Flo Living, 91.9 per cent reduced PMS burden within sixty days.
U-Ploid is an early-stage biotechnology company tackling one of the most fundamental challenges in fertility care: the sharp, age-related decline in egg quality that limits outcomes across IVF and egg freezing.
While much of the field focuses on improving assessment and selection, U-Ploid is developing a first-in-class therapeutic approach designed to improve egg quality itself by addressing the biological causes of age-related chromosomal errors.
Supported by strong preclinical evidence and now advancing into human studies, U-Ploid combines scientific rigour, regulatory discipline and long-term vision to help redefine what is possible in fertility care.
Gestational diabetes is a strong risk factor for future type 2 diabetes, even in women with normal pre-pregnancy weight, according to a study at the University of Gothenburg.
The researchers call for earlier testing and better follow-up.
“Our results show that gestational diabetes functions as a kind of stress test for the body’s ability to manage blood sugar, and identifies women with a greatly increased risk of future type 2 diabetes”, said Jon Edqvist, PhD and affiliated to research at the University of Gothenburg, and operating room nurse at Sahlgrenska University Hospital.
Gestational diabetes is a special type of diabetes that can affect pregnant women.
The condition is defined as elevated blood sugar levels, without previously known diabetes. Treatment involves self-monitoring of blood sugar, advice on lifestyle habits and, if necessary, medication.
Identifying gestational diabetes is important because the disease increases the risk of complications such as preeclampsia, the need for a cesarean section and high birth weight for the baby.
Those who have had gestational diabetes are also at higher risk of later developing type 2 diabetes.
In the current study, published in eClinicalMedicine, researchers now show that gestational diabetes is a strong indicator of future risk of developing type 2 diabetes, even in women with normal weight before pregnancy.
Elevated risk even with normal weight
The study is based on data from the Medical Birth Registry on just over 1.15 million first-time mothers in Sweden, who gave birth between 1987 and 2019. 16,870 women with confirmed gestational diabetes were compared with age-matched women without the diagnosis. The median follow-up period was nine years.
The results show that women with a BMI of 35 and above, i.e. severe obesity, had an almost tenfold increased risk of developing gestational diabetes compared to women with normal weight.
The risk of subsequent type 2 diabetes also increased with higher BMI, but it was significantly increased even with normal weight, which the researchers describe as particularly worrying.
More follow-up and more studies
The researchers behind the study welcome the recently updated recommendations on gestational diabetes in Sweden, where a higher proportion of pregnant women at increased risk are expected to be offered testing earlier in pregnancy, and if necessary, interventions.
“Diagnostics and care of gestational diabetes have looked very different in different parts of the country,” said Annika Rosengren, professor at the University of Gothenburg.
“There is a need for both improved follow-up after gestational diabetes, and more studies that investigate how such follow-up affects future health and prognosis”
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