Part IV: Comprehensive Market Analysis

Top applications and products reported

1. Oxford Medical Simulation (OMS) ^[28] was the most widely reported XR technology for health by the NHS and universities. It was reportedly used by 6 NHS Trusts and 15 universities for workforce education, predominantly for physical health conditions. For the NHS, OMS offers solutions for clinical training using immersion and performance analytics to expose staff to new scenarios, procedures and protocols while identifying skill gaps and competencies. Within universities, it is used similarly but for student nurses and doctors to learn and apply foundation skills and show readiness for practice. This technology relies on VR technology to develop these clinical and soft skills for the workforce.

2. Body Swaps ^[41] was the second most commonly reported XR technology, reported by 2 NHS Trusts and 12 universities. Also used for workforce training, Body Swaps uses VR and AI for skill development. Specifically, the technology builds on interpersonal communication, teamwork, conflict management and empathetic care to prepare students or healthcare workers using different scenarios and AI roleplay. This has reportedly increased confidence in being able to stay calm in hostile scenarios and in supporting patients’ self esteem and identity.

Some of the other most reported products and applications include:

• Smiley Scope - used by two NHS sites and one university, Smiley Scope is a medical-grade VR headset designed to reduce pain and anxiety in children during medical procedures like needle insertions, dressing changes, and MRI preparation.
• DR.VR by Rescape - used by five NHS sites, it is used for distraction, relaxation and pain management for stress reduction and during painful treatments, such as for burns patients.
• XR Therapeutics - used by four NHS for treating anxiety conditions and specific phobias using a large flat-screen in a therapy room. One site was also using it to enhance anxiety and psychosis research therapy applications. Read more in our case study.
• Anatomage - used by four universities, this product is a virtual dissection table for advanced real-human-based 3D anatomy designed to be a superior medical learning tool to transform medical education and training.
• Gener8 - used by four universities, Gener8 is an immersive interactive room designed to transport learners into fully interactive clinical scenarios. Using 360-degree projection and spatial audio, learners can simulate a wide range of healthcare and external environments, from emergency departments to shopping centres, and supports scenario customization enabling educators to tailor experiences to specific learning outcomes and clinical competencies.

XR Applications in Mental Health Provision

Overall, XR has a lot of potential in the following areas, as identified in the survey and FOI:

1. Enabling preventative care and self-management
2. Scaling access to support during early stages of mental health concern, although not accessible to some with disabilities
3. Supporting blended models of care beyond clinical settings

XR is able to simulate environments, enable practice and repeated exposure, and support learning through embodied interactions. This could help reduce waiting lists if it is used to support self-management, increase engagement with therapies, support staff training, and offer more personalised and adaptive experiences when integrated with AI and sensors. AI may be seen as a competitor but it is likely that the next iteration will be reliant on more embodied experiences, as seen with established AI models like Replika.

We simply do not have sufficient people and money to accommodate the large demand for mental healthcare. We should let XR play its role, most likely in hybrid or blended therapy formats.

- Remco Hoogendijk, XR4Rehab

There are still some significant gaps and research/evidence is needed in these areas. Although there is significant evidence in its use for exposure therapy, our survey of companies shows that this is not an area of growth within the UK. There are more XR tools available for anxiety and depression which remain the most common mental health conditions demonstrating that there is a link between market need and product development in this sector. However, other conditions such as dementia, psychotic disorders, neurodevelopmental conditions, and substance use disorders remain underrepresented.

In general, VR is the most used XR technology with little focusing on AR or MR despite their potential. Whilst other areas like haptics and AI are emerging, these are not yet in widespread adoption. Similarly, whilst XR is mainly used for training and education there are few technologies being used for diagnosis, monitoring or prevention – these are key pressures within the NHS. Opportunities are still being missed for its integration in social prescribing, early screening or digital triage.

As of July 2025, a third of the NHS Trusts in England that responded to FOI requests reported having or using XR technologies, suggesting modest uptake. However, the adoption of XR technologies for healthcare in the NHS appears to have moved forward significantly in the last five years, suggesting more confidence in these technologies and the capacity of staff to implement them. By contrast, 62% of UK universities reported XR use and significantly earlier and more broadly within research. The private sector is starting to show strong engagement with immersive technologies and across most mental health conditions.

Challenges and Opportunities

Within the following sections, we provide an analysis of challenges and opportunities that have been highlighted by industry respondents to the survey.

The Technical Challenge

In the surveys, several highlighted how important the content, e.g., virtual environments, are and the need to ensure they are developing them to meet demand and at the required quality. The content needs to be engaging and evidence-based, providing the benefits required. Many felt that this led to a reliance on developers but where expertise was not always easy to access. Those who noted that they had few or even no technical challenges often identified their team as the reason for this.

”Creating enough 3D content in the metaverse“ ”making an engaging game for multiple platforms including VR“ ”and making sure it contains beneficial exercises.“

A significant challenge was the dependency and reliance on large technology companies or hardware providers which meant a lack of control when changes are made. This can further exacerbate other technical challenges such as integration and interoperability.

Also headset manufacturers are constantly updating headsets/operating systems which means that things that once worked no longer work.

Importantly, accessibility was highlighted by many. Several recognised the need to make both the software and hardware accessible, particularly for people with disabilities or cognitive impairments. They emphasised the need for co-design and to ensure that accessibility did not impact on affordability. Users were also considered a technical challenge, both because of their attitudes and digital literacy as well as the reliance on them to actually deliver the product, which meant ensuring they had sufficient training. Hardware can also still be difficult to use.

Our challenge technically is to create a product that is as accessible as possible with a limited budget – we are consulting on accessibility requirements from the very beginning.

Integration and implementation was a significant challenge, with the need to ensure there was integration technically with things like EHRs but also integration in different healthcare systems and infrastructures with aspects such as wifi and infection control needing to be considered. Additionally, requirements for interoperability place a significant burden on developers, especially when personalising their product. Deployment and scaling up can be limited by these challenges. Additionally, running the product across multiple sites and building the infrastructure needed can be very challenging when not wanting to sacrifice quality or security, particularly when considering international markets. Some felt this was linked to their position as content-providers and their dependency on platforms.

Most XR systems do not interact very easily with the larger hospital patient records, we need to fix the way we can prescribe and follow up digital interventions.

Technical Challenges

The Regulatory Challenge

​​Developers highlighted several regulatory hurdles they encounter when developing XR for mental health, including medical device classification or UKCA/CE marking, quality management systems, NHS procurement, and data protection. One key barrier for many was the uncertainty of what classified as a medical device, many felt that XR “falls in the cracks between health and wellness” meaning “companies need more clarity on where they sit” and that this could mean that “many don’t even realise” that they need to consider medical device regulations. Most felt that another barrier to compliance is the investment needed, both in terms of cost and time. This is particularly true for smaller organisations or start-ups, who struggle to ensure that they have capacity to complete the necessary documentation and processes.

We and many other XR startups aren’t prepared for the length and cost of this process.

Regulation is an area of significant complexity for industry to navigate. It requires an understanding of not just a single requirement but requirements of different stakeholders across the healthcare system and beyond, for example understanding NHS clinical standards as well as GDPR legislation. Evidence of effectiveness, cost savings, and interoperability/implementation is required for approval but to gather this evidence approval is often needed, creating a gap – “we want to gather evidence with the patient group to validate the product, however we need regulatory approval to do this”. Some discuss procurement models and how they have been designed in ways that do not account for emerging technologies. They also highlight issues whereby partners are concerned about regulations, meaning they are more wary about providing support for funding. Additionally, the area of mental health means more consideration of GDPR as not only is “mental health data… classed as special category personal data” but that “XR apps track biometric or emotional data, raising concerns over informed consent, data minimisation, and data storage”.

Minimal adoption, lack of adequate funding for general populations and as such market rollout as a result of production and validation blockers, lack of budget from end markets to actually adopt the technologies being funded for R&D, lack of new digital systems and procurement within healthcare for market adoption and rollout.

Support is required to traverse the complex spaces and understand regulations but even when this is provided, developers highlight that it is not always sufficient: “we have spoken to a number of experts on how to navigate this but so far have not been given a clear route through this process (regulation)”. Support can also cost, particularly when needing intermediaries to help navigate the complexities.

Many feel that innovation has been stifled, particularly due to the investment needed and the complexities highlighted. They feel uncertain which “suffocates rapid iteration and experimentation by enforcing strict rules too early in the process” and this “prevents anything but massive orgs from competing”. Most responses focused on the cost of regulating, particularly in relation to medical device regulations, recognising not just the financial requirements but also the time and complexity that required additional support. They especially highlighted this for early-stage products or for start-ups who wouldn’t have the resources needed. Many referred to the issue of qualification and classification, uncertain whether their product would be considered Software as a Medical Device.

One of the benefits of XR for healthcare is also a challenge to our understanding of its use; the adaptiveness of interventions allows for creative uses of applications that have not necessarily been designed for a healthcare purpose. Anecdotally, we often hear of how people are adapting existing applications for mental health-related purposes such as using Wander, which allows people to virtually visit different locations in the world, with people who are hospitalised to provide some respite. These types of secondary uses, while impactful, may fall outside the scope of this report’s focus which prioritises tools that have a primary healthcare purpose.

This raises an important distinction relevant to regulatory frameworks, particularly how the intended purpose of a technology is defined. Within the context of medical devices and software as a medical device, the intended purpose should be clearly defined by the manufacturer with details not only about the product’s functionality but also the clinical problem or unmet need it addresses. Appendix 1 provides the MHRA’s Digital Medical Health Technologies (DMHT) Device Characterisation Form, which supports developers in defining their product’s intended purpose ^[42]. This includes information on:

• functionality
• clinical problem or unmet need
• any medical purposes or claims
• whether it targets clinical symptoms or conditions
• who the population are and whether they are patients
• who the intended user is
• where in the healthcare pathway the product is intended to be used
• any contra-indications or potential harms

It is also important to note that a product’s intended use, how it is actually deployed in practice, can sometimes align with a medical purpose even if the original intended purpose was not explicitly medical. This creates a regulatory grey area, where applications designed for more general wellbeing can be repurposed for therapeutic contexts without consideration of regulatory compliance.

Regulatory Challenges

The Financial Challenge

The biggest financial challenge shared by developers was funding. Many felt that funders still failed to recognise the value of XR in healthcare and, even when they did, typically awarded universities rather than industry. One commented that this may be due to the language they use in grant writing and the need to consider support from bid writers. They felt that funding was often geared towards early-stage innovations rather than scaling or continued development, not recognising the high costs associated with development and deployment which requires specialist expertise. Additionally, very few highlighted the need for funding to generate evidence.

Grants are all or nothing which discourage phased and rapid iteration.

Those that did highlight the need for evidence focused on clinical trials and health economics, emphasising that without this kind of evidence there is little incentive for investors or procurers to adopt their products. Private investment was attractive to some but they questioned how confident investors are in XR for healthcare without sufficient evidence or use cases.

Nobody wants to buy your product till you’ve done clinical trials. And nobody wants to do clinical trials unless you have money.

Another challenge is the fit that funding has to ensure business sustainability, with long application processes and delays to securing funds, for example being paid in arrears, this can make relying on funding difficult.

Most public funding is reimbursed in arrears, so startups must front costs.

Some with experience of NHS contracts highlighted how laborious these could be and that even within place, they were often short-term and uncertain. Others discussed potential reimbursement models, with some having experience in other health systems such as the US, highlighting some early successes. However, the software aspect was highlighted as a barrier where “Standard models for software – i.e. monthly/annual licence fees – do not appear to have been accepted in healthcare.”. Overall, many felt there was a disconnect between what was needed to support XR and the existing funding streams, which do not account for the iterative, creative development cycles needed and which can guarantee a higher quality product.

Financial Challenges

Organisational

There is somewhat of a postcode lottery for XR companies seeking support from e.g., Health Innovation Networks where certain regions have more expertise than others. This highlights the lack of a central XR strategy and the fragmentation that exists within the NHS. This means that it can be a slow process to procurement, with contracts and other requirements needing to be met individually for each Trust.

NHS procurement favours established providers.

There is, however, a clear interest in XR within the UK and it compares favourably to other markets. XR is already widely accepted for training and simulation so this could also be a potential pathway for intervention-based deployment. Companies have seen a shift towards digital tools since COVID, including within the NHS, and feel that this could lead to the wider adoption of XR.

The Clinical Challenge

Developers share that they face high costs to generate clinical evidence, for example through clinical trials, which is needed to secure investment. Many draw on clinical expertise but share that it can also be expensive, with clinical experts difficult to access and often with limited availability.

To build effective mental health tools, you need input from qualified clinicians … These professionals typically have limited time and high day rates.

Many felt that there was a reluctance amongst clinicians to engage with new technologies, perhaps due to less experience. This also impacted on implementation, with less access to patients and services for real world testing. Integration and implementation into clinical environments faced several barriers – infrastructure, interoperability with care systems, existing workflows. They also highlighted the demand for Trusts for local evidence before adoption despite the need to transition away from pilots. Even when access is provided, developers felt there was a clarity about what evidence was needed for adoption, particularly when making the case for the products. For example, some felt it was difficult to demonstrate value because their products offered solutions in areas where there were no other interventions to compare against or were preventative.

Our product does not neatly replace an existing process or treatment … it is not clear how this can be captured for evidence/efficacy.

This was further complicated by the lack of existing evidence, limiting what is known about longitudinal use, comorbidities or variability in users and its impact, and risks and harms.

We need funding… to generate evidence and complete our health economics work. But we need evidence and health economics in order to secure paid opportunities.

Clinical Challenges

Offering Solutions for Evidence Generation, Regulation and MDR Compliance

• Context: Currently companies reportedly spend 1-2 years going through Medical Device Registration (MDR) processes with MHRA/UKCA and circa £1million per year waiting for a class IIa medical device license to be able to be used in the NHS covering costs of compliance, the data team and a team of developers and clinicians to further develop the product without being able to sell it. This cost and timescale is known as the ‘valley of death’ after initial product efficacy is demonstrated in small scale trials. This is the stage where many innovations do not make it to market, companies fail and what was innovation, becomes outdated by the time it receives the necessary licence to sell within the NHS
• Proposed Innovation: Governments outside Europe and the US (who are not governed by MHRA and the FDA) are looking to new models of AI enabled, rapid regulatory and MDR compliance tools that can take regulatory timescales down from years to weeks and millions to thousands of pounds/dollars.

We propose a new approach: develop a platform that radically accelerates compliance, evidence generation, and commercialisation. Offer tools and processes that provide instant gap analysis against any regulatory or compliance standard, showing innovators exactly what’s missing and how to address it. Help teams create the required documentation and evidence, tailored to the relevant standards, reducing the need for expensive consultants or academic staff. Automate the design, execution, and reporting of randomised controlled trials, following HRA guidelines and producing regulator-ready evidence at a fraction of the time and cost.

From this approach we will see benefits including the cutting of time-to-market by 12-24 months, companies saving up to £2 million per product for Class IIa MDR and above. Enabling Liverpool to become a global leader in rapid, responsible health tech innovation and attract investment, create jobs, and deliver real impact for patients and the local economy.