News
Shrinking the gender health gap through innovation in clinical trial AI
By Paula Bellostas Muguerza, Global Lead, Healthcare and Life Sciences at Kearney
The lack of female representation in clinical research is finally getting the recognition it deserves as a driving factor of the gender health gap.
With only 7 per cent of healthcare research focused on conditions that exclusively impact women’s health, it’s an area that has frustratingly been overlooked and underfunded for decades.
Clinicians have been forced to make decisions about women’s health based on limited data and male-centric trials.
As a result, women are routinely subjected to missed diagnoses and delayed treatments.
However, like nearly every sector, AI is reshaping healthcare, and if used correctly, there’s a real opportunity to redesign clinical trials, close long-standing gaps, and make research far more inclusive and effective.
Incorporating AI
Unlocking innovation in women’s health, including more diverse women in clinical trials, disaggregating data by sex, redesigning clinical trials with women in mind, and deepening insights on sex differences were all recognised as core principles for improving healthcare policy in the World Economic Forum’s recent “Prescription for Change” white paper, in collaboration with Kearney and the Gates Foundation.
This focus is critical in improving healthcare outcomes for women.
Conditions such as heavy menstrual bleeding, endometriosis, fibroids, and ovarian cysts cost the UK economy approximately £11 billion per year, but fixing the gaps in treatment and trials goes beyond profit – it’s our moral duty.
And to unlock innovation at scale, policymakers should pair regulatory incentives with financing tools like targeted tax credits and dedicated grant programmes.
However, shrinking the gender health gap will take more than good intentions.
Clinical trials still face a range of issues, from under-reported side effects to low female participation. AI can help by improving how data is captured, making trials more inclusive and leading to fairer, higher-quality outcomes.
According to the National Centre for Biotechnology (NCBI), AI’s ability to analyse complex and diverse information allows for an improved understanding of gender differences, leading to more effective treatments for women in the future.
The World Economic Forum’s push to expand inclusion in clinical trials by involving more women highlights the importance of raising awareness among regulators and trial teams.
Inclusion must be prioritised in the early phases of trials, particularly in cardiology and oncology, and extended to underserved groups, including women of colour and post-menopausal women.
Attitudes to inclusion are also moving in the right direction, and AI can help drive that momentum.
By analysing large datasets, advanced algorithms can identify underrepresented women for targeted recruitment, leading to more representative trials.
AI can also review trial protocols to detect potential gender bias and recommend designs that address gender-based differences and women’s specific health needs.
Approach with caution
Paula Bellostas Muguerza
Although AI offers powerful capabilities, it’s not a fail-safe tool, and the need for human oversight has never been more important.
Models trained on biased data risk repeating existing inequalities, especially when sex-based differences in conditions like heart disease, stroke, and neurological disorders are still underrepresented in many datasets, leading to fatal consequences.
In doing so, AI could reinforce the very misconceptions about women’s health it’s meant to correct.
A study by the London School of Economics and Political Science (LSE) found evidence that AI tools are more likely to downplay women’s health issues compared to men’s. The increasing use of AI models by local authorities to supplement the workload of social workers across the country could result in widespread unequal care provision, perpetuating the gender bias.
The recommendation for researchers, clinicians, and developers to enhance sex-disaggregated data is especially relevant here.
Without data that clearly captures sex and gender differences, AI systems can’t be expected to recognise or respond to them accurately.
This requires standardised collection methods and consistent terminology so women’s health signals are properly captured and acted upon.
Healthcare organisations process huge amounts of data containing important clinical information, spread out and stored in different formats.
Improving the way data is captured makes clinical trials more inclusive and produces fairer, higher-quality results.
AI can combine structured and unstructured data, turning clinical records into meaningful and actionable insights.
AI regulation also varies wildly across countries.
The EU’s AI Act is one of the first major attempts to introduce clear rules, but elsewhere, regulation remains patchy.
While pharmaceuticals go through rigorous testing and approval processes, AI-driven tools often slip through regulatory gaps.
That’s why it’s even more important to design inclusive clinical trials from the start, ones that properly capture sex and gender differences and feed better data into these systems from the outset.
Mind the gap
Having reached crisis status, the task of reducing the gender healthcare gap can appear overwhelming.
But despite the scale of the challenge, there are real reasons for optimism.
We’re already seeing progress, and growing pressure from researchers, investors, and campaigners is pushing the system in the right direction.
But progress won’t come from technology alone. Transparency and inclusivity are just as important.
AI systems must be developed through processes that involve patients, clinicians, community advocates, as well as data scientists and engineers.
This kind of collaborative participation will help highlight blind spots, challenge assumptions, and build tools that reflect the complexities of healthcare, ultimately dispelling the one-size-fits-all myth.
If AI is going to play a role in closing the gender health gap, it must be guided by more than innovation.
Yes, we’re making technological breakthroughs, but if they simply replicate the inequities of the past, what use are they?
Light exercise and less sitting may reduce pregnant women’s risk of serious blood pressure complications, according to a new study.
Researchers have proposed a daily activity and sleep guide that they say was linked to a nearly 30 per cent lower risk of hypertensive disorders of pregnancy.
The suggested pattern includes fewer than eight hours of sedentary time, at least seven hours of light physical activity, around 22 minutes of more intense activity and nearly nine hours of sleep.
The University of Iowa-led study examined the daily behaviours of 470 pregnant women across all stages of pregnancy.
Participants wore monitors that measured physical activity over 24-hour periods and recorded how long they spent asleep.
Hypertensive disorders of pregnancy include chronic high blood pressure, gestational hypertension and pre-eclampsia.
Gestational hypertension is high blood pressure that develops during pregnancy, while pre-eclampsia is a potentially serious condition involving high blood pressure and signs that organs may be affected.
Sedentary behaviour means being mostly inactive, such as sitting or lying down.
Light physical activity can include casual walking, moving around the home or standing.
Moderate to vigorous activity includes movement such as brisk walking, where breathing and heart rate increase.
Kara Whitaker, associate professor in the department of health, sport, and human physiology at Iowa and corresponding author of the study, said: “We are identifying the optimal composition of movement behaviours across the day associated with the lowest risk of developing HDP and the most improved health outcomes.
“This blueprint holds for each and every trimester of pregnancy.”
Study participants were enrolled at sites in Iowa City, Pittsburgh and Morgantown, West Virginia.
The women wore activity and sleep monitors for at least one week during each trimester of pregnancy.
Four in five participants were non-Hispanic white and nearly a quarter lived in rural areas.
The data showed a steep rise in risk among pregnant women who were sedentary for more than 10 hours a day.
Women who increased light physical activity to at least four hours a day reduced their risk of hypertensive disorders of pregnancy to 15 per cent from 30 per cent.
Whitaker said: “Just moving around more seems to have significant health benefits.
“And I think it also may be a more feasible target for women who are pregnant who are not exercising regularly.”
The researchers said they were surprised that longer durations of moderate to vigorous physical activity did not appear to provide additional benefit.
Sleep beyond a certain duration also did not appear to bring major further benefits.
Whitaker said: “Through this study, we are providing evidence that reducing sedentary behaviour and engaging in light physical activity are important, and maybe more important, when it comes to pregnancy and health.”
The findings may be relevant beyond pregnancy because clinical research has shown that women who develop hypertensive disorders of pregnancy are more than twice as likely to develop heart disease later in life.
Cardiovascular disease includes conditions affecting the heart and blood vessels, such as heart disease and stroke.
Whitaker said: “We know that cardiovascular disease is the number one killer of women, and if we can intervene in pregnancy and prevent women from developing a hypertensive disorder of pregnancy, we are putting them on a better trajectory, away from cardiovascular disease and toward more optimal cardiovascular health.”
The study was published online on June 10.
A second study, published online on May 27, looked more closely at the ratio and type of sedentary behaviour and light physical activity linked to a lower risk of hypertensive disorders of pregnancy.
Whitaker is a lead co-author on that study.
Co-authors in the June 10 study include Alex Crisp, Jaemyung Kim, Karina Smith, Donna Santillan, Mark Santillan and Bridget Zimmerman, from Iowa; Jacob Gallagher, from Iowa State University; Melissa Jones, from Oakland University in Michigan; Bethany Barone Gibbs, Katrina Wilhite, Alexis Thrower and Iqra Sheikh, from West Virginia University; and Sabera Rahman, Janet Catov, Christopher Kline and Maisa Feghali, from the University of Pittsburgh.
The National Institutes of Health, the University of Iowa Institute for Clinical and Translational Science, the University of Pittsburgh Clinical and Translational Science Institute and the West Virginia Clinical and Translational Science Institute funded the research.
We are excited to reveal the winners of the third annual Femtech World Awards.
The winners were announced at a virtual event this afternoon attended by shortlisted companies, along with sponsors and judges.
The event welcomed guests from the UK, Europe, Asia, Africa and North America.
Thank you to all 174 entries, as well as the sponsors for making the event possible.
See you in 2027!
Femtech World Awards 2026 Winners
Winner:
Shortlisted:
IVI RMA x Juno Genetics
Natural Cycles
Winner:
Highly commended:
U-Ploid
Shortlisted:
Hello Inside
Winner:
WISE HF, led by Prof. Mary Ryder
Highly commended:
Cardiac College for Women
Shortlisted:
Hyvelle Ferguson-Davis
CognitiveCare
Winner:
Highly commended:
Youterus
Shortlisted:
ŌURA
Winner:
Shortlisted:
LeanShield by ParrotPal Group
Perigen
Winner:
Shortlisted:
Body Moody
Looop
Winner:
Shortlisted:
Owning Your Menopause
Womeno
Winner:
Shortlisted:
The Blue Box
Celbrea
Winner:
Shortlisted:
HealCycle
Mor
Winner:
Shortlisted:
HRC Fertility
Mira
Pregnant women’s expectations about postpartum sleep may predict sleep quality after birth, outweighing prior sleep and psychiatric history, a study suggests.
The findings suggest attitudes and beliefs about sleep during pregnancy could be a modifiable risk factor for postpartum sleep concerns.
They also indicate that, among women expecting the poorest sleep, higher postpartum anxiety may further worsen sleep quality.
Sammy Dhaliwal, lead author is clinical health psychologist and research fellow in the department of obstetrics and gynaecology at the Perelman School of Medicine at the University of Pennsylvania.
Dhaliwal said: “Most pregnant women in our sample anticipated poor postpartum sleep before it occurred, and it was striking that those expectations predicted worse sleep outcomes even after accounting for factors such as prior sleep disorders, psychiatric history, and number of previous births.
“This suggests that attitudes and beliefs about sleep during pregnancy may represent a modifiable target for early intervention before postpartum sleep problems emerge.”
Sleep disturbance affects an estimated 60 to 80 per cent of postpartum women and is linked to a higher risk of depression and anxiety.
Researchers said it is often regarded as an expected part of life after childbirth rather than a health issue that may be addressed earlier.
The study enrolled 432 pregnant women at about 24 weeks of gestation, meaning around 24 weeks into pregnancy.
Participants completed measures of their expectations about postpartum sleep, current sleep quality using the Pittsburgh Sleep Quality Index, and mood using validated depression and anxiety scales.
Assessments were repeated at six, 12 and 24 weeks postpartum.
A subset of 49 women also wore wrist actigraphy devices at six to eight weeks postpartum.
Actigraphy uses a wearable device, similar to a watch, to estimate sleep and wake patterns based on movement.
The results showed that 70 per cent of pregnant women, or 301 of 432 participants, expected poor sleep in the postpartum period.
Researchers found that predicted sleep disruption during pregnancy was a significant predictor of postpartum sleep concerns.
Among first-time pregnant women without prior health concerns, those who expected greater sleep disturbance had significantly more disrupted sleep after birth, measured by both actigraphy and self-report.
Among women who expected the worst sleep quality, higher postpartum anxiety significantly worsened both measured sleep and self-reported sleep, independent of anxiety levels during pregnancy.
Dhaliwal said the findings point to two possible areas for intervention: addressing sleep-related beliefs during pregnancy and treating postpartum anxiety.
Dhaliwal said: “Postpartum sleep disruption is often treated only after problems develop, but our findings suggest there may be an opportunity to intervene earlier during pregnancy.
“Addressing sleep-related beliefs and postpartum anxiety during prenatal and postpartum care may help improve sleep and emotional well-being in new mothers.”
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