Women with an early precursor to Parkinson’s disease show much less brain shrinkage than men, despite similar disease severity, new research shows.

The discovery could help scientists explore how hormones might one day be used to treat the neurodegenerative condition.

The findings are based on data from nearly 700 participants across nine international research centres.

The study focused on isolated REM sleep behaviour disorder — a condition in which people physically act out their dreams.

It is considered the most reliable early warning sign of diseases caused by toxic protein build-up in the brain.

More than 70 per cent of those affected later develop Parkinson’s disease, Lewy body dementia or multiple system atrophy, which affects several body systems.

Researchers from Université de Montréal analysed 888 brain scans from centres in Canada, the Czech Republic, the UK, France, Australia, Denmark and Italy.

After quality checks, 687 participants were included: 343 patients with the sleep disorder and 344 healthy controls.

The results revealed clear sex-based differences.

While 37 per cent of the cortical areas — the brain’s outer layer responsible for higher functions — showed thinning in men, only one per cent of regions were affected in women.

This difference remained even though participants were of similar age (around 67) and had comparable clinical profiles.

Marie Filiatrault is first author of the study and a doctoral student at Université de Montréal.

The researcher said: “Men show much more extensive and severe cortical thinning — the outer layer of the brain that controls our higher functions — than women, particularly in areas linked to movement, sensation, vision and spatial orientation.”

To understand the protective effect, researchers compared brain images with gene activity in different regions, measured in healthy brains after death.

They found that the less-affected areas in women showed higher expression of genes related to oestrogen function, particularly ESRRG and ESRRA, which produce oestrogen-related hormone receptors.

The ESRRG gene was especially notable, showing greater activity in brain tissue than elsewhere in the body.

These receptors play key roles in mitochondrial function — the cell’s energy production system — and in the survival of dopamine-producing neurons, the cells that die in Parkinson’s disease.

Shady Rahayel is professor at Université de Montréal’s Faculty of Medicine and lead author of the study.

Rahayel said: “This sleep disorder offers a unique window of opportunity to study the mechanisms of neurodegeneration before major motor or cognitive symptoms appear.

“Our results suggest that certain brain areas in women with isolated REM sleep behaviour disorder are better protected than those in men, likely through the action of oestrogens.”

The team chose to study this precursor condition because it allows observation of brain protection mechanisms before major motor symptoms develop.

Although only 25 to 40 per cent of people with Parkinson’s experience REM sleep behaviour disorder, studying this early stage gives insight into how the brain resists damage when it is still limited.

Previous studies have shown that women with established Parkinson’s disease tend to experience slower progression than men, pointing to similar protective effects.

The findings could shape future research and treatment development.

The authors recommend separating men and women in clinical trials, which could improve statistical accuracy and reduce the number of participants required.

The biological mechanisms identified — particularly those linked to the ESRRG gene — could also become potential therapeutic targets.

Early laboratory research suggests that increasing ESRRG activity may protect dopamine-producing neurons from the toxic effects of alpha-synuclein, a protein that builds up abnormally in the brains of people with Parkinson’s.

“This study brings us closer to precision medicine, where treatments could be tailored not only to the disease but also to individual biological characteristics, including sex,” said Rahayel.

The flagship women’s health summit brought together over 400 visionary founders, funders and innovators, with a shared mission of transforming women’s health worldwide.

This year’s Women’s Health Week, which took place at the Barbican, London from 14-17 October, showcased a sector once considered by funders to be too much of a ‘niche’, meeting a crucial unmet need with huge market demand.

Investments are outperforming their value, regulators want to speed up the route to market, and clinical validation is cutting through the noise and demonstrating real results.

There is a buzz about the femtech sector – or at least there was in the Barbican last week – but experts have urged founders should move forward responsibility, building ethics and equity into their innovations.

Here’s our takeaways from the key conversations at Women’s Health Week.

1. Women’s health is outperforming – but angels and influencers are crucial for raising capital

Investment in women’s health is outperforming, and this trend is expected to continue, according to the panel at Women’s Health Week on Thursday 16th, where fund managers and founders highlighted significant returns, growing institutional interest, and the critical role of early-stage backers.

Sanji Chotai, a senior investment manager at British Business Bank, says she is seeing “really encouraging data” and anticipates more “outperformance”, particularly in medtech, which is drawing interest thanks to “shorter timelines to regulatory approval” and rapid commercialisation.

Series A and B activity is also picking up, but the panel agreed that early-stage capital and angel investors remain essential.

“My first angel investment in a women’s health company, I think on Series A, is going to be 20x on multiple and for our fund, it’s going to be around 9x,” said Trin Linamagi, founding partner at Sie Ventures.

“We need to take bigger bets and double down – and actually put the capital behind these businesses early on.”

Having driven successful campaigns for Soulcycle and Barry’s Bootcamp, Tatum Getty, now a founding general partner at THENA, also highlighted the importance of influencers – and not just on Instagram.

“Who is that person who believes in what we’re building and will tell their friends,” she said.

“Women have not been traditional investors they are more risk averse, smaller investment but bigger impact. They add so much more value than the amount of capital that they contribute.”

2. NICE and new pathways for health technologies

During a discussion on mastering Europe’s regulatory process, a representative from the National Institute for Health and Care Excellence (NICE) outlined how new rules-based approval routes, now being introduced for health technologies, are designed to speed access to innovation.

The body is also better aligning processes with the Medicines and Healthcare products Regulatory Agency (MHRA) to reduce the time it takes to regulatory approval.

“We’re taking forward the rules-based pathway for health tech,” said Kendall Gilmore, a senior advisor at NICE.

“Developing a model more similar to the medicines pathway, where, for some products, it goes through the MHRA, through NICE and then comes with a recommendation that has a funding mandate attached.”

The pathway, currently being developed will see health technologies assessed in a similar way to medicines with the first products approved from April next year.

NICE currently evaluates only a fraction of the 500,000 technologies used daily in the NHS. While a NICE recommendation is “not mandatory”, it can be a “powerful signal” to the NHS.

NICE is constantly “horizon scanning” for “disruptive products” further down the pipeline and is engaging more directly with innovators, industry associations and international partners to identify promising technologies earlier, and a new early value assessment route is giving promising products a faster track.

“If it meets an unmet need, it should be used with further evidence generation,” Gilmore explained.

“This is particularly relevant for digital health and diagnostics.”

3. Scientific validation is the most effective way to ‘cut through the noise’ 

In a panel exploring how to “cut through the noise” in femtech, founders were urged to bake credibility into product design from day one, with scientific proof and clinical validation the sharpest differentiator, according to Soun Rakshit, of MV Health.

“You have to spend probably two years going through the R&D process,” said Rakshit.

“That is the best and probably the only way to do it, so that by the time you get regulatory approval, you have already had significant patient feedback and iteration.”

Earning trust also means collaborating with experts who understand the problem, as Helen O’Neil, founder of Hertility, explained.

When in the development stage, O’Neil reached out to professionals, including obstetricians and gynaecologists to understand the right questions to ask based on their “clinical intuition and personal experience”.

Rakshit added: “If we can show true clinical evidence, and it does take time, it is the best way to cut through the noise.”

4. Bias in AI is ‘real and harmful’ – and founders need to know how to address it

Experts discussed the role of AI and its potential to both help and harm women’s health, urging proactive testing and human oversight to avoid the risk of decades of a “male default model” being implemented into new solutions.

“AI that’s trained on that skewed data can really fail women,” said Sarah Montgomery Taylor, clinical lead of GenAI evaluation and scaled services at Google, highlighting familiar examples such as heart-attack presentation.

“Biases are real, and they are really harmful, and so being aware of them is so crucial.”

Panellists also flagged “measurement bias” and the “historical dismissal of women’s pain,” where systems trained on those records “can learn to deprioritise” certain signals.

Beyond bias in diagnostics, Marinos Ionnides, head of software and AI medical devices regulation at the MHRA, highlighted the risks of implementing AI in areas where there may be hidden bias.

“I’m quite worried about the deployment of software AI in places where we aren’t we didn’t know we would be finding bias [such as] appointment booking,” he said, adding that in these “unknown unknowns,” “the regulator has their greatest role”.

Founders were urged to be responsible when scaling AI, introducing guardrails such as building in equity and collecting data from the very beginning for “rigorous real-world validation”.

Clinicians need to be able to test the product and understand it to build trust, while regulatory processes should be “adaptive”, offering “clarity on what the path is to market”.

Chen Davies, founder at Anya, shared a real-world example of how products and content tailored for underserved groups drove measurable change, including a “10% population-wise” rise in breastfeeding rates in a deprived area of Blackpool after six months.

“AI should gradually complement human support without replacing it,” said Davies.

5. Consumer data can play a critical role in building the clinical evidence-base 

During the final panel, participants argued that continuous real-world data, paired with clinical benchmarks, is the fastest way to fix women’s health’s “male baseline” problem and turn lived experience into evidence.

Dr Chris Curry, clinical director for women’s health at Oura, argued that wearables are “one of the big unlocks” by collecting data that gives the “whole picture of the human”.

But tracking can – should – meet clinical standards, with the panel pushing for globally representative consumer datasets.

“I see consumer data if it’s truly representative, if it’s truly globally representative, being critical,” said Micah Gellman, a senior strategist for women’s health innovation at the Gates Foundation.

“It helps us calibrate and link consumer insights and lived experience to clinical anchors and value outcomes… this kind of consumer data is one avenue that we have to really change investor appetite.”

Rhiannon White, CEO of Clue, which has a long-running research collaboration with Oura, including collecting symptom tracking data on perimenopause and pain, added that women’s spending power can actually steer where future R&D should be focused.

“We are able to shape and direct where people will put their research and put their development with our spending power,” she said.

6. The crisis in government support can be an opportunity for more innovative funding pathways 

With the Gates Foundation recently committing an additional US$2.5bn for research in women’s health, Gellman also reframed the reduction in government funding for women’s health – such as that seen under the Trump administration in the US – as an opportunity for more innovate financing.

“There is a real opportunity for European and Asian government funding to step up and fill some of those gaps,” said Gellman.

“An opportunity for government funding and philanthropic funding to take new forms and to be partnering in new ways to catalyse innovation and to work with academics and industry players.”

Rather than a binary between grants and VC, the panel highlighted “blended financing mechanisms, venture philanthropy… different kinds of outcome-based financing” with public and philanthropic dollars used “to de risk, early-stage investment”.

Gellman added: “This crisis that we’re in, in terms of government funding is also an opportunity for innovative financing.”

The comments brought the conference full circle, reminiscent of those made earlier in the day, by Tatum Getty, who highlighted: “Women and small amounts of capital, can make a big difference.”

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.

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.