A large real-world study has found that an AI-powered digital tool developed by Megi Health can significantly reduce blood pressure over time while maintaining high long-term patient engagement –  a combination that has remained a major challenge in hypertension care.

The peer-reviewed research, published in JMIR mHealth and uHealth, analysed real-world data from more than 5,000 adults using Megi’s digital blood pressure management platform as part of their everyday lives.

The results showed meaningful reductions in systolic blood pressure, with the greatest improvements seen in people who started with higher readings.

Crucially, the study found that outcomes improved the longer people stayed engaged with the platform.

Dr Petroula Laiou, chief scientific officer at Megi and senior author of the study, said: “High blood pressure can’t be managed through occasional GP visits alone.

“This study shows that ongoing, easy-to-use digital support can help people control their blood pressure in the real world –  particularly those at highest risk.

“It also demonstrates how combining digital tools with routine clinical care creates a more effective ‘phygital’ model for managing long-term conditions.”

Around half of users were still active after one year, while patient feedback showed high satisfaction, greater confidence in self-managing blood pressure, and reduced anxiety around monitoring.

Rather than relying on a tightly controlled clinical trial, the study examined how people actually use digital health tools in real life.

Users interacted with Megi through WhatsApp, receiving reminders to measure their blood pressure and take medication, and entering readings directly into the chat.

This approach enabled continuous tracking of blood pressure, engagement and outcomes over time.

The research was led by a multidisciplinary team from King’s College London, King’s College Hospital NHS Foundation Trust, Megi Health, the Magdalena Clinic for Cardiovascular Diseases in Zagreb, and the University of Zagreb.

The cohort included both women and men aged 17 to 95, with more than 90 per cent of participants regularly submitting blood pressure readings.

The findings add to growing evidence that home-based digital monitoring can overcome many of the limitations of clinic-based blood pressure checks, which are often affected by white-coat or masked hypertension.

By combining regular home readings with behavioural support, digital tools such as Megi could play an increasingly important role in long-term cardiovascular care.

Dr Nina Šesto, CEO of Megi Health, said: “What’s striking is not just the blood pressure reductions, but how long people stayed engaged.

“That level of sustained use is exactly what hypertension care has been missing.

“As health systems move towards prevention, home monitoring and long-term condition management, this approach aligns closely with the direction set out in the NHS 10-Year Health Plan.”

Ten FemTech innovations have been chosen for Accelerating FemTech: Evaluate, led by Health Innovation South London and DigitalHealth.London with UK partners.

The accelerator, part of the Innovate UK Biomedical Catalyst, supports women’s health solutions at technology readiness level 4 or higher, meaning prototypes proven in a lab or relevant setting and preparing for market entry.

Delivered with Health Innovation Yorkshire & Humber, the programme will help companies grow, connect with decision-makers and plan real-world testing in health services.

Women spend around 25 per cent more of their lives in ill health than men, yet only one per cent of global health research and innovation focuses on women-specific conditions.

Selected innovations include a heated bra for cyclical breast pain, cognitive behavioural therapy for menopause support, biosensors to help detect respiratory disease, compassionate support after pregnancy loss and an AI-powered thermal imaging tool for breast screening. Cognitive behavioural therapy is a talking therapy that helps people change unhelpful thoughts and behaviours. Thermal imaging maps heat patterns on the skin to highlight potential concerns. Biosensors are small devices that detect biological signals.

Dr Sean Clarkson, head of strategic operations at Health Innovation Yorkshire & Humber, said: “The ten selected innovations have huge potential to make an impact on women’s health. I am delighted to support the programme and excited to see how these innovative solutions develop.”

“At Yorkshire & Humber we have a strong focus on women’s health and we will be providing mentorship, subject matter expertise and business coaching.”

Several solutions draw on lived experience, including a microbiome serum inspired by recurrent urinary tract infections, and a maternity training platform that brings local women’s experiences to life through virtual reality.

The cohort also includes tools that support community-based care, such as a digital preventive maternal health platform, a therapeutic platform for people living with premenstrual dysphoric disorder and premenstrual syndrome, and an agency-building app for chronic pelvic pain.

Over three months, innovators will follow a hybrid curriculum with virtual training and in-person support from a business coach, plus guidance on evaluation routes such as health economic analyses.

Companies will also attend two residentials, take part in expert-led webinars, receive one-to-one mentoring across the health and care system and join an end-of-programme showcase, with the chance to apply for closed-call feasibility funding through Innovate UK’s Biomedical Catalyst.

Dr Chiara Board, chief executive and founder of P.Happi, said: “We need more innovation and access to better care in women’s health—and with limited funding flowing into the sector, programmes like this are so vital. We’re thrilled to have the opportunity to join the Accelerating FemTech: Evaluate programme alongside other changemakers. P.Happi, born from science and personal experience, will use this opportunity to advance our mission of making pioneering microbiome innovation accessible to more women through community and public healthcare.”

Anja Ueland, director of Meyva, said: “I’m really proud that Meyva has been selected for the Accelerating FemTech: Evaluate programme. This opportunity will help us build the evidence needed to support heat therapy as a safe, effective option for women experiencing cyclical mastalgia. For too long, breast pain has been dismissed or overlooked. It means a lot to see this issue recognised and to be part of a programme helping women’s health innovations move from personal experience to real-world impact.”

Geetha Manjunath, chief executive of Niramai Health Analytix, said: “We are honoured to be selected for the Accelerating FemTech: Evaluate programme. This recognition reinforces our mission to make advanced, accessible health screening available to women everywhere. Through this initiative, we look forward to collaborating with the UK’s vibrant health innovation ecosystem to expand Niramai’s clinically proven, AI-based Thermalytix technology, improve early breast cancer detection, and contribute to the NHS’s goals for equitable and preventive women’s health.”

A new AI model can predict a person’s risk of developing breast cancer up to five years in advance by analysing mammograms.

The technology could make screening more effective by identifying women who need additional imaging.

In one study, women the algorithm flagged as high risk were four times more likely to develop breast cancer than those with a low AI score.

The Clairity Consortium, an international association of 46 research institutions in North and South America and Germany, developed the model, Clairity Breast, trained on more than 420,000 mammograms.

Christiane Kuhl, director of the department of diagnostic and interventional radiology at RWTH Aachen University Hospital, said: “With this newly-developed AI model, we can predict with much greater precision that a woman will develop breast cancer in the next five years, on the basis of mammograms that are normal and show no signs of breast cancer.”

Unlike traditional risk models, the AI does not need family history, genetics or lifestyle data. It calculates risk from mammograms alone and classifies women into risk categories.

The model assesses not only the amount of glandular tissue but also its texture and arrangement, another breast cancer risk factor.

Kuhl said current “one-size-fits-all” screening is outdated.

“The AI model can decide within seconds whether a woman needs an MRI for early detection or not,” she said.

MRI uses magnetic fields and radio waves to create detailed images but is more expensive than mammography.

Kuhl advocated a two-step approach: “First, mammography for early detection; then an AI analysis to determine the risk of disease over the next five years.”