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How femtech can navigate the EU medical device and AI rules

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By Xisca Borrás, Partner – Life sciences regulatory and Ellie Handy, Senior Associate – Life sciences regulatory, Bristows

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” [emphasis added].

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:

  1. 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 (e.,it is not an accessory nor driving/influencing the use of a hardware device) and does it not fall within Annex XVI[1]?
  • 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.

  1. 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.

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Early PET scan could chemo response in aggressive breast cancer – study

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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.

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Femtech World reveals startup of the year shortlist

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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.

OvartiX is doing something that has never been done before: building a drug discovery engine purpose-built for women’s health.
Its lead programme, OVX001, targets medically induced menopause – a condition affecting young female cancer patients who undergo chemotherapy or radiotherapy.
These women are cured of cancer but enter menopause overnight.
There is currently no approved drug to prevent it. OVX001 is designed to change that, preserving 80–95 per cent of ovarian follicles during treatment without compromising anti-tumour efficacy.
Behind the science is the OmiXX platform: the first ML-driven drug discovery tool built specifically for female physiology, using proprietary ovarian cellular models and human multi-omics data.

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.

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Gestational diabetes increases risk of type 2 diabetes – even at normal weight, study finds

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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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