News
Don’t get lost – How femtech can navigate the EU medical device and AI rules
By Xisca Borrás and Ellie Handy of the life sciences regulatory department at Bristows law firm
Femtech, short for female technology, is an important and fast growing sector. The EU is a key market for femtech, with five of the top 10 countries for femtech investment located in the EU.
Femtech products are developed for many areas of women’s health, such as menstrual health, pregnancy planning and monitoring, menopause and mental wellbeing.
As femtech is intrinsically linked to health needs, a key question for femtech products is whether they are regulated as medical devices or merely consumer products.
Additionally, many femtech products are embracing the use of artificial intelligence (“AI”). Therefore, another key question is whether products using AI will be regulated as “high-risk” AI systems under the EU’s new AI legal framework.
This article looks at when femtech apps and software qualify as medical devices in the EU and how the medical device and AI legal frameworks interact.
What is a software medical device?
The definition of “medical device” in the EU’s Medical Device Regulation 2017/745 (the “EU MDR”) includes software, used alone or in combination, that is intended by its legal manufacturer for a medical purpose. These medical purposes are listed in the EU MDR and include (amongst others):
- diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of disease;
- diagnosis, monitoring, treatment, alleviation of, or compensation for, an injury or disability; and
- control or support of conception.
The legal manufacturer is the person that puts their name/branding on the device, and takes responsibility for it.
Whether software is considered a medical device will depend on whether the manufacturer states it has a medical purpose in the relevant documentation/materials.
The EU MDR defines intended purpose as “the use for which a device is intended according to the data supplied by the manufacturer on the label, in the instructions for use or in promotional or sales materials or statements and as specified by the manufacturer in the clinical evaluation”.
What is the test for qualifying as a medical device in the EU?
There is a selection of guidance documents that can assist you in determining whether a product should qualify as a medical device. We summarise some of the key guidance below:
- MDCG 2019-11 rev.1
Under the EU MDR, the Medical Device Coordination Group (“MDCG”) has published guidance on the qualification and classification of software as a medical device. It sets out five decision steps to help determine if a piece of software is a medical device in the EU. The steps are:
- Step 1: Is the product software?
- Step 2: Is it standalone software (i.e., it is not an accessory nor driving/influencing the use of a hardware device) and does it not fall within Annex XVI?
- Step 3: Is it performing an action on data beyond storage, archival, communication, simple search or lossless compression?
- Step 4: Does it act for the benefit of an individual patient?
- Step 5: Does it have a medical purpose (as set out in the medical device definition)?
If the answer to all five questions is yes, it will qualify as a medical device. In this case, manufacturers will have to ensure they comply with the pre-market requirements set out in the EU MDR before they can place the software medical device on the market.
Notably, they will need to set up a qualify management system, compile a technical file, undergo the appropriate conformity assessment and affix a CE mark.
Importantly, the manufacturers would also need to consider post-market requirements, such as having a post-market surveillance system and undertaking post-market vigilance.
3. Other relevant guidance
The MDCG has also published a manual on borderline and classification of medical devices under the EU MDR.
Additional sources of guidance may also be available from national competent authorities. The legal manufacturer could also look at examples of other products already on the market to see how they are regulated (e.g. looking at EUDAMED). Although, we would caution anyone relying too heavily on the regulation of other products as there is no guarantee they are compliant.
What if you’re not a medical device?
If the software does not qualify as a medical device, the product will not have to comply with the EU MDR.
However, the manufacturer should be careful about how it promotes its product and the claims it makes about it because, as discussed above, a medical device is defined based on the manufacturer’s intended purpose.
Let’s take the example of a mere period app. Using it for logging period dates, tracking ovulation, and predicting future cycles has no medical purpose and is therefore not a medical device.
However, if its manufacturer recommends this piece of software for contraception and/or to support conception it will suddenly have a medical purpose and so, it would qualify as a medical device.
As such, the manufacturer would either have to bring the device into conformity with the EU MDR or take action to change the promotional materials to remove the medical claims.
Interaction between medical devices and AI legal frameworks
Under the EU MDR, devices are assigned risk classifications. For the lowest risk devices (Class I medical devices), the manufacturer can self-certify compliance with the EU MDR prior to the product being placed on the market or put into service in the EU.
However, high risk devices (Class IIa or above medical devices) must undergo a third party conformity assessment carried out by a notified body.
Notified body conformity assessments require a detailed review of the manufacturer’s quality management system, technical documentation, systems and procedures.
The process will often take more than a year to complete. Additionally, manufacturers have to grapple with ongoing burdens such as vigilance and post-market surveillance.
Under the EU MDR, most software as a medical device will be classified as a Class IIa or above.
Like the EU MDR, the EU’s Regulation (EU) 2024/1689 (the “AI Act”) also distinguishes between AI systems that pose different levels of risk.
The AI Act imposes onerous obligations on “high risk” AI systems, including in relation to accuracy, transparency, risk management, data quality and governance, and human oversight.
Although there is some overlap between the EU MDR and AI Act requirements, many are new AI-specific obligations. These pose a significant additional regulatory burden, increasing the complexity and cost of compliance for stakeholders.
Notably, the risk classification of an AI system that is itself, or is included in, a medical device is linked to the device’s classification under the EU MDR. Under the AI Act, AI systems are classified as “high risk” systems if:
(a) the AI system is a safety component of a medical device or the AI system itself is a medical device; and
(b) the medical device is required to undergo a third-party conformity assessment under the EU MDR.
Therefore, low risk medical devices (i.e., Class I medical devices) that are self-certified cannot be “high risk” AI systems.
Whereas, any device that requires a notified body to perform its conformity assessment will be a “high risk” AI system, and so will be subject to the additional AI Act requirements.
Unfortunately for those wishing to avoid the “high risk” AI system requirements, there are relatively few Class I devices under the EU MDR.
Therefore, the majority of medical devices that are an AI system or have an AI system as a safety component will qualify as a “high risk” AI system.
One notable example of a Class I device is software intended to support conception by calculating the user’s fertility status based on a validated statistical algorithm.
If this kind of software medical device is also an AI system, it would not be classed as a “high risk” AI system, so it would not be subject to the more onerous requirements in the AI Act.
However, the manufacturers of these devices would need to carefully consider any product developments that add additional functionality, as this can impact the risk classification of the product under both the EU MDR and AI Act.
For example, if the manufacturer added functionality to the Class I device so it could also be used as a means of contraception, it would become a Class IIb medical device and would need a third party conformity assessment.
In turn, as the software is also an AI system, this would mean the AI system would be considered “high-risk” and be subject to additional regulatory requirements under the AI Act.
Whilst AI has the potential to provide tremendous benefits for femtech, it also triggers additional complexity that can be time-consuming and costly to navigate.
It is important to get it right in terms of compliance in order to maintain consumer trust, avoid regulatory penalties, and pave the way for long-term success and viability.
By Xisca Borrás, Partner – Life sciences regulatory and Ellie Handy, Senior Associate – Life sciences regulatory at Bristows law firm.
Glaucoma drugs could potentially be repurposed to treat aggressive breast cancer after researchers identified markers linked to response.
Scientists found that several cancers, including breast cancer, melanoma and a type of blood cancer, rely on the same molecule to become aggressive and spread.
Drugs that block the molecule are already used to treat glaucoma and may therefore have potential as cancer treatments.
Researchers also identified markers that could help indicate which patients may respond well to the drugs.
Experts said the findings could help establish which patients may benefit from existing treatments.
Repurposing medicines already shown to be safe could also allow treatments to reach patients faster.
Lead author Victoria Sanz Moreno, professor of cancer cell and metastasis biology at The Institute of Cancer Research in London, said: “Some cancers are particularly aggressive, and once they spread they become very hard to treat.
“Catching these aggressive cancers and preventing their ability to move around the body is really crucial to our mission to keep more people living well with cancer.
“Our research has identified a shared weakness of aggressive cancer cells that could be targeted across many cancer types, wherever they originate in the body.
“We confirmed our findings in aggressive cancers such as breast cancer, melanoma, and a type of blood cancer called acute myeloid leukaemia, but we believe this molecular fingerprint of cancer cells likely to die after treatment applies to many more cancer types.
“It’s reassuring to know that a treatment already exists – a drug currently being used safely in some patients could be adapted to treat these cancers.”
Researchers set out to find markers that could identify which cancers would respond well to drugs blocking ROCK, also known as Rho kinase.
Aggressive cancer cells rely on ROCK as they spread around the body and cause advanced disease that is harder to treat.
The molecule keeps the scaffolding inside cells tense, causing them to contract and become round and generating enough force for cancer cells to squeeze through tissue.
The team, working in the Breast Cancer Now Toby Robins Research Centre at The Institute of Cancer Research, examined data from a drug-sensitivity database to identify which cancer cells responded to ROCK inhibitors.
Breast cancer cells that responded to ROCK inhibitors had a particular gene called E-Cadherin that was not working properly.
In melanoma, responsive cells tended to have a more rounded shape and high activity in a signalling pathway called NFKB.
Acute myeloid leukaemia cells that responded well to ROCK inhibitors had a specific subset of genetic alterations.
Researchers then tested the findings in laboratory tumour samples and mouse studies.
They hope tumour biopsies showing these markers could eventually help identify patients who may respond well to ROCK inhibitors.
Dr Simon Vincent, chief scientific officer at Breast Cancer Now, said: “With around 11,500 women tragically dying from breast cancer every year in the UK, research like this is vital to finding more effective treatment options.
“This study helps to lay the foundation for understanding who among those with certain cancers, including breast cancer, might benefit most from existing drugs. Finding new uses for existing treatments, which we know people can safely take, is easier and faster than developing new cancer drugs from scratch.
“It’s encouraging that these drugs may be especially effective in targeting cancer cells that are more likely to spread and resist treatment.
“While this research is still at an early stage and clinical trials are needed, it’s an important step towards more personalised breast cancer treatments in the future.”
First author Jaume Barcelo, formerly a postdoctoral research fellow at The Institute of Cancer Research in London and now based at Barts Cancer Institute at Queen Mary University of London, said: “Our study has identified a specific pattern of features that is consistent across many cancer types, and that can be used to match the right patients to this treatment.
“The next stage for this research will be to test how these drugs that inhibit ROCK work in combination with other treatments, to maximise the benefit for patients.
“As ROCK inhibitors are already approved to treat glaucoma, I hope that our findings can be used to progress the drugs into clinical trials to treat cancer in the near future.”
The research was funded by The Institute of Cancer Research, Breast Cancer Now, Barts Cancer Charity, Cancer Research UK, Worldwide Cancer Research and UK Research and Innovation.
Susanna Daniels, chief executive officer of Melanoma Focus, said: “Despite major advances in melanoma treatment over the past decade, too many people still die from the disease each year, and not every patient responds to the treatments currently available.
“Every new discovery improves our understanding of how melanoma grows and survives, bringing us closer to treatments that are more effective, more targeted and have the potential to improve survival.
“While these findings are still at an early stage and will need to be tested in clinical trials, they offer an encouraging direction for future melanoma research and the development of more personalised treatments.”
Diagnosis
Where women live may influence ovarian cancer survival, especially among Black women – study
Women living in socially vulnerable neighbourhoods had a 20 per cent higher risk of death after an ovarian cancer diagnosis, a study found.
Black women also faced a 45 per cent higher risk of death than white women.
Researchers said the combination of being Black and living in a highly vulnerable neighbourhood was linked to a greater risk of death than would be expected from either factor alone.
Francesmary Modugno, professor in the Department of Obstetrics, Gynecology and Reproductive Sciences at the University of Pittsburgh and senior author, said: “We expected residential context to influence outcomes, but what surprised us was how much stronger the impact was for Black women.
“Our findings suggest that it’s not simply where someone lives. The interaction between a woman’s lived experience and her residential environment may be helping drive these persistent disparities.”
Modugno is part of the Women’s Cancer Research Center, a collaboration between UPMC Hillman Cancer Center and Magee-Womens Research Institute.
Epithelial ovarian cancer is the deadliest form of gynaecological cancer, with around half of patients surviving for five years after diagnosis.
Survival is lower among Black women, with fewer than 40 per cent alive five years after diagnosis.
Differences including age at diagnosis, cancer stage and tumour type explain some of the survival gap, but researchers said a substantial proportion remains unexplained.
Researchers examined whether social determinants of health, including conditions in the communities where patients live, could help explain the remaining difference in outcomes.
The study, carried out with researchers at the University of Alabama at Birmingham, analysed data from 2,544 women diagnosed with epithelial ovarian cancer and treated at the O’Neal Comprehensive Cancer Center.
The group included 509 Black women and 2,035 white women.
Researchers linked patients’ residential census tracts to the US Centers for Disease Control and Prevention’s Social Vulnerability Index.
The index measures neighbourhood factors including poverty, housing conditions, transport access, educational attainment and other socioeconomic challenges.
Black women in the study were more likely to live in highly vulnerable neighbourhoods.
However, where women lived did not fully explain the racial difference in survival.
Black women had poorer survival than white women even when they lived in similarly advantaged communities, while being Black and living in a highly vulnerable neighbourhood together was associated with a greater risk of death than expected from either factor alone.
Researchers said the findings could help health systems and cancer services identify women at greater risk and provide additional support.
Possible measures include patient navigation programmes, transport assistance, childcare support and survivorship services to help patients complete treatment and manage the challenges of cancer care.
Rebecca Arend, associate professor of gynaecology oncology at the University of Alabama at Birmingham, said: “Our findings reinforce that we must better understand and address the barriers patients face in their communities and ensure that every woman has equitable access to high-quality care.”
Arend, who is also associate director of clinical research at the O’Neal Comprehensive Cancer Center, added: “Translating research into meaningful improvements in cancer outcomes is only possible through strong collaborations among academic medical centres, researchers and community partners.”
The study builds on research published in 2025 led by Modugno and University of Pittsburgh colleagues using data from UPMC Hillman Cancer Center in western Pennsylvania.
That research also found an association between social vulnerability and ovarian cancer survival.
The latest analysis included a substantially larger group of Black women and examined more closely how residential conditions might contribute to racial inequalities in outcomes.
Researchers said the findings need to be replicated in other parts of the US and among additional racial and ethnic groups to determine how widely they apply.
Future work will examine other social and environmental factors that could affect ovarian cancer survival, including neighbourhood pollution, access to food and community resources.
Researchers hope the findings could lead health systems to develop more targeted support for patients at greatest risk of poor outcomes.
Adding neighbourhood measures such as the Social Vulnerability Index to cancer care planning could help health systems identify women facing barriers to care and connect them with support during treatment.
Women with endometriosis had a 46 per cent higher risk of developing type 2 diabetes than those without the condition in a recent study.
The study followed data from nearly 3m women over 25 years and was described as the largest to date examining the relationship between the two conditions.
Maggie Fuzak Nunziato, a doctoral student in epidemiology at George Mason, led the research with Anna Pollack, professor of global and community health.
Researchers found that diabetes risk varied across different forms of endometriosis, suggesting the condition may have broader long-term health implications than previously recognised.
They believe chronic inflammation associated with endometriosis may play a role in metabolic health, although more research is needed to understand the connection.
Fuzak Nunziato, the study’s lead author, said: “Previous studies largely evaluated endometriosis as a single condition and generally reported little or no overall association with type 2 diabetes.
“Our findings add to a growing understanding that endometriosis may affect more than reproductive health alone.”
The association was strongest among premenopausal women and women without obesity, groups not traditionally considered to be at the highest risk of type 2 diabetes.
Endometriosis affects around one in 10 women of reproductive age.
It occurs when tissue similar to the lining of the uterus grows outside the uterus and can cause chronic pelvic pain, infertility and other complications.
If the findings are confirmed by further research, they could help clinicians identify women with endometriosis who may be at higher risk of type 2 diabetes and could benefit from earlier screening or prevention efforts.
Researchers analysed health records from nearly 3m women in the Utah Population Database between 1996 and 2021, including almost 100,000 who had been diagnosed with endometriosis.
Some forms of endometriosis had a much stronger association with diabetes than others.
The strongest link was found among women with extra-pelvic endometriosis, meaning the condition is found outside the pelvis.
The researchers stressed that the findings show an association and do not prove that endometriosis causes type 2 diabetes.
They said further research is needed to understand the biological mechanisms connecting the two conditions and whether earlier metabolic screening could improve outcomes for women with endometriosis.
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