There could be a multitude of causes of chronic pain ranging from injury, surgery, musculoskeletal conditions, cancer or complications of diabetes, arthritis, and stroke. Irrespective of the root cause, chronic pain can have a debilitating effect. In addition, chronic pain also translates into decreased productivity, loss of wages, and increased dependence on the healthcare infrastructure. As a result, the burden of chronic pain falls both on the individual as well as the society. Therefore, good pain management practices are important since they help mitigate chronic pain and allow individuals to perform their day-to-day tasks smoothly.

The role of technology in chronic pain

While medication is an integral component of managing chronic pain, long-term management of chronic conditions also requires support to bring lifestyle changes through exercise therapy, nutrition advice etc. Technology can help doctors and healthcare professionals facilitate the right interventions for better long-term management of chronic pain conditions.

Equally important, it provides greater control to the patient by encouraging self-management. In turn, this can also encourage patients to share progress data voluntarily, which can provide valuable insights to develop pain management therapies.

There is ample scientific evidence to demonstrate the benefits of long-term exercise on conditions such as chronic low back pain, chronic neck pain, and neuropathic pain. Digital platforms can increase patient engagement by providing valuable information such as demonstration videos for exercises and tips for injury prevention, etc. This engagement is particularly valuable in the initial stages of exercise training when patients might experience a short-term exacerbation of pain. In the absence of close supervision at this stage, patients are more prone to abandoning the programs and reverting to their sedentary lifestyle that perpetuates a vicious cycle of increasing pain. Engagement and counselling can help alleviate long-term suffering.

Since direct supervision over pain management by a healthcare professional is often not practically possible, digital platforms play an increasingly vital role. While patients often seek support from their healthcare provider, the latter is limited by bandwidth as well as time. For instance, access to the provider might not be easily possible beyond traditional office hours. Digital platforms can help here since they allow patients to log their pain, mood, sleep, and activities and gain better insights into their own coping mechanisms. These records can also guide the development of a personalized treatment plan. Digital tools can be useful to set timelines to fulfil specific goals in a pain management plan.

Studies suggest that chronic pain patients and their families often seek knowledge about their condition and are keen to learn about lifestyle adjustments such as exercise, sleep, and nutrition. They also look for strategies and tips to cope with depressive and anxious thoughts, which are often associated with chronic pain. In fact, the lack of access to reliable information on their condition can be a source of distress, particularly in the initial stages. A digital platform can fulfill this requirement and eliminate the need to scour through the internet and dodge massive amounts of misinformation.

Given that chronic pain is a debilitating condition that can lead to physiological and psychological consequences, digital health platforms can provide crucial support in the form of on-demand guidance. Whether the platform acts as a virtual coach that assists patients with exercise therapy or as a digital diary for individuals to log their pain experience, the role of digital platforms can be valuable. For clinicians too, digital tools can generate useful insights to monitor patient progress and optimize pain management strategies.

Life sciences organizations must look to leverage digital technology for better patient outcomes when dealing with chronic pain. Apart from manufacturing compliant tools and devices, they should invest in integrated digital health platforms that will inform clinicians and doctors based on the data patients choose to share, the best pain management strategy for their needs.

By Subhro Mallik, EVP and Head of Life Sciences, Infosys

The post The Pivotal Role of Technology in Chronic Pain Management appeared first on .

The Labour government’s recently announced “AI Opportunities Action Plan’”sets out an ambitious roadmap to make the UK an “AI superpower”. The healthcare industry is positioned as a key beneficiary and the NHS is expected to play a central role, supported by initiatives such as a proposed national data library. While the plan holds real promise, it also raises significant concerns. The biggest among them: how will sensitive NHS data be handled, who gets access, and how do we ensure the public remains confident in a system increasingly shaped by a “hidden process” of AI?

Potential and pitfalls

There’s no doubt that AI can improve patient outcomes and operational efficiency. Initiatives by NHS England already use AI to identify patients at risk of frequent emergency visits, enabling earlier intervention. Nevertheless, scaling these solutions demands access to vast quantities of health data — a shift that risks undermining public trust and data security if not handled with the utmost care.

Unlike traditional healthcare improvements, AI demands a new kind of contract with the public — one where data is the critical input, and trust is the foundation. If people feel their data is being misused or commercialised without consent, they may withhold vital information, which could lead to undermining both diagnosis and care.

We’ve already seen how data misuse can damage trust. The now-defunct Care.data programme collapsed in 2016, joining a long lineage of NHS digital initiatives from the £12 billion abandoned National Programme for IT to the troubled NHS Digital Strategy—each faltering when reforms prioritized technical solutions over democratic engagement. We can’t afford to repeat these cyclical mistakes that have characterized NHS modernization efforts since the 1990s.

Ethical data use is non-negotiable

AI introduces new layers of complexity into healthcare decision-making. Lacking clear governance creates a danger that private firms might gain monopolistic advantages, using exclusive access to NHS data to train proprietary models. If there is no designated public service, appropriate level of government oversight, or direct benefit to the public, these systems can operate as black boxes making decisions without transparency or accountability.

This is particularly concerning as private investment in AI infrastructure ramps up. The recent £14 billion committed by companies such as Vantage Data Centres and Kyndryl echoes earlier watershed moments in NHS history—from the introduction of General Management under Roy Griffiths in 1983 to the Private Finance Initiative of the 1990s—where private sector logics reshaped public healthcare. These investments could profoundly shape the future of UK healthcare delivery, but only if guided by rigorous data ethics and transparency standards that learn from this complex history of public-private entanglement. Ethical, patient-centric data governance isn’t a barrier to innovation. It is the foundation that makes it sustainable.

Patient control and trust in AI is key

The success of AI in the NHS hinges not only on accuracy and efficiency but on public trust. Patients must be empowered to control their data at every step of the process to understand what information is collected, why, and who has access.

Europe is already moving in this direction through initiatives like the European Digital Identity Wallet (EUDI Wallet) under eIDAS 2.0, which puts data control back in the hands of individuals. The NHS has the potential to do the same, evolving the NHS App into a fully-fledged digital health wallet where patients can grant, and revoke, access based on need and explicit consent.

This is where decentralised technologies, like the W3C Solid protocol, come in. Developed by web inventor Sir Tim Berners-Lee, Solid enables individuals to store their personal data in secure “Agentic Wallets” retaining full control over how it’s accessed and by whom. It’s a technical model designed to resist the extraction-based data economy that has dominated the tech world for the last two decades.

Far from slowing progress, this approach enhances it — by improving data quality, reducing systemic risks, and increasing patient engagement. It mirrors what we already know about good healthcare: outcomes improve when patients feel informed, respected, and in control.

Proven success in the UK

This isn’t a theory. A data-sharing pilot in Greater Manchester that gave clinicians secure access to patient-held records has improved care for vulnerable groups, including people with dementia. This model of secure, patient-controlled data sharing should serve as a blueprint for national policy.

Brigitte West, Product Director at DrDoctor, rightly pointed out that Labour’s plan is “much-needed recognition that AI can be used for operational reasons – so that clinical staff can spend less time on admin and more time delivering care.”

But to fully realise this, AI systems must be designed not just for efficiency but for fairness, accountability, and trust.

Avoiding the trap of “Big Data” thinking

There’s a long-standing temptation in health tech to centralise everything — to build ever-larger repositories under the banner of efficiency. But in reality, centralisation can restrict access, increase security risks, and lead to long-term dependence on external vendors.

Decentralised, standards-based systems like Solid allow for more scalable, secure, and flexible data use. Each patient’s data lives in their own secure wallet, and clinicians access only what’s necessary with explicit consent and clear audit trails. This design dramatically reduces the risk of mass data breaches while increasing transparency and control.

It’s time to move past the idea that innovation means building bigger silos. Real innovation means rethinking the structure altogether by creating a system where data works for people, not the other way around.

A future built on trust

For AI to succeed in the NHS, it must be understandable, explainable, and accountable. Patients need to know how AI arrives at recommendations and be able to trust solutions. Clinicians need the ability to interrogate and challenge its decisions in real-time without negative impacts to patients. That’s how we ensure AI complements, rather than replaces, human expertise in healthcare.

Labour’s “Plan for Change” could indeed deliver a modernised healthcare system. But it must be built on a foundation of trust, not just technology. As we move forward, the term “national data library” must be more than a metaphor — it should reflect a distributed, accessible, user-controlled system where data is borrowed with permission and returned with respect.

Just as the NHS revolutionised access to care in the 1940s—emerging from the crucible of war and the Beveridge Report’s vision of combating the ‘five giants’ of Want, Disease, Ignorance, Squalor and Idleness—we now have a chance to revolutionise how data underpins that care while remaining faithful to those founding principles that have weathered decades of political contestation. If we get it right, we can unlock the full potential of AI in healthcare — while staying true to the NHS’s founding values of fairness, equality, and public good.

By Davi Ottenheimer, VP of Trust and Digital Ethics, Inrupt

The post NHS Data and AI: Building Innovation on Trust appeared first on .

The scaphoid bone has an avascular blood supply that means, depending on the location and size of the break, there is a real risk of bone death where blood supply is cut off. This leads to a loss of wrist function and dexterity, which can have significant financial implications for those who rely on their flexibility of wrist movement that the scaphoid supports.

This is why MRI and CT images have become the ‘gold standard’ for diagnosis. However, limited resources and long imaging waiting lists mean clinicians across the UK instead rely on X-rays in the first instance. If a scaphoid fracture is suspected, clinicians will typically request four X-ray views, versus two for other wrist injuries, but even that is not a guarantee that the fracture will show as the scaphoid bone can be easily hidden by other carpal bones in a 2D image.

It is easy to understand how scaphoid fractures can be easily missed then, particularly in overstretched A&E departments where there may not be sufficient scanner time or radiology cover to diagnose ‘minor injuries’ quickly. Clinical teams usually adopt a conservative approach therefore: Initially treating the injury as if the bone is fractured, with splinting recommended to protect it from further damage, and a follow-up appointment with the fracture clinic in 7-10 days’ time. By this point, if the patient is still experiencing pain, new X-rays will likely reveal initial bone healing more clearly than the original scaphoid break.

It is a sensible approach but one that ultimately causes several problems:

Firstly, where clinicians are concerned about the possibility of a scaphoid fracture but unable to confirm it during the initial visit, splinting the wrist while awaiting further imaging or specialist review means patients can find themselves unable to work unnecessarily, with significant financial implications due to lost earnings.

Scaphoid fractures are usually slow to heal because tiny blood vessels supplying nutrients to the site are often damaged at the time of injury. This means that even though the results of both surgical and non-surgical interventions are very good following diagnosis, both approaches require considerable time in plaster, with knock-on impacts for patients and their dependents, including inability to drive, work and earn normally. Should surgery ultimately be required, it is easy to see how treatment delays of just a couple of weeks can have a real impact on patients’ lives.

Finally, requiring all patients to attend follow-up appointments in fracture clinic has significant resource implications for a healthcare system already under pressure, not least in terms of clinician time and additional imaging requirements.

Accepting all of the above, how then can we improve diagnosis for these patients? How can we prevent patients with sprained wrists taking unnecessary time off work, while supporting those with scaphoid fractures to access faster treatment and limit injury-related loss of earnings?

One potential solution lies in a new imaging technology – already proven in the veterinary industry – which promises to bring affordable, more-detailed 3D imaging to the point of care in hospitals and clinics around the world.

This next-generation technology builds on the foundations of digital tomosynthesis (DT) imaging, which is widely used for breast imaging across the NHS. With traditional DT, a conventional X-ray tube moves through a range of angles to derive 3D data – providing better diagnostic information than 2D X-ray but, restricted by its limited depth resolution capabilities, creating difficulties localising some structures and elements.

Adaptix’s unique 3D X-ray technology ‘sweeps’ in two dimensions, enhancing the Z resolution relative to conventional DT. Images are quickly reconstructed – in under 20 seconds – providing  slice-by-slice images that can be analysed extremely quickly. This allows for slice thickness adjustments over regions of interest – a particularly important feature when looking for ‘tricky’ fractures, such as those to the scaphoid bone.

The result? A high-resolution 3D image that provides far greater definition and clarity than 2D X-ray techniques, at a cost and radiation dose similar to traditional X-ray. What is more, the compact design of the technology and low-radiation dose, mean it can be brought directly to the point of patient care – reducing time spent moving between hospital departments and allowing clinicians to obtain imaging ‘in clinic’ if needed.

It is an exciting development that promises to improve both health outcomes and clinical management alike: Providing faster, more-accurate diagnosis; reducing the need for expensive MRI or CT imaging; supporting clinicians to plan workflows, clinics and surgeries more effectively; and helping patients get the treatment they need more quickly, without unnecessary time off work and speeding their return, mitigating any financial losses resulting from their injury.

By Mark Thomas, BSc (Hons), PgC, HCPC Reg. 

Mark spent the first 10 years of his career working as a Radiographer in human healthcare both in the UK and Australia. Later, he focused on CT, managing the Neuro CT Service in Oxford in his final position. In 2008, Mark joined Toshiba/Canon Medical as a CT Specialist, and spent the next 15 years initially providing training, before managing the UK Clinical CT Team. With a strong team Mark drove the adoption of new technologies pushing clinical boundaries, maintaining high clinical integrity and importantly customer satisfaction. Mark’s background gives him real clarity on the future and opportunity for inclusion of Digital Tomosynthesis Imaging in a modern, forward thinking Imaging Service.

The post Reducing Misdiagnosis and Helping Patients Back to Work appeared first on .

Following a four-month procurement, the five-year contract with Children’s Health Ireland (CHI) will enable an important part of the organisation’s digital transformation. Once deployed, technology provided in the agreement will equip professionals in Ireland’s forthcoming new children’s hospital with the ability to instantaneously access imaging and reports as they deliver care for patients.

For the first time Children’s Health Ireland will have a single secure repository for all non-radiology DICOM images, reports and other key diagnostic information. Medical images will no longer be restricted to storage on individual devices on which they are captured, but will be consolidated into an accessible vendor neutral archive (VNA) and integrated with CHI’s electronic health record. CHI estimates more than a petabyte of non-radiology imaging will be managed with the new system during the term of the contract.

A new picture archiving and communication system, or PACS, specifically for ophthalmology will also be deployed, and will be configured to address discipline specific needs, whilst creating new efficiencies and enhanced worklist visibility.

Dr Cliodhna Byrne O’Shea, applications programme manager in the Department of Digital Health at Children’s Health Ireland, said: “Once implemented in our future children’s hospital, imaging technology provided by Sectra will be revolutionary for our professionals as they support Ireland’s youngest patients, and will be a key enabler of continuity of care.

“The VNA will mean that all non-radiology imaging and key related information will be catalogued correctly going forward, and linked back to the patient record. New interoperability will be a game changer for clinicians, with connected imaging devices providing instantaneous access to imaging during clinics. This will save countless hours for our professionals, who will no longer need to walk across a hospital to find imaging stored on a device or hard drive.

“Additional specialist functionality will also help to move away from disparate systems in ways that will make life so much easier for our staff, allowing full control over worklists, ordering, and scheduling.”

Patients and families will also be able to more easily gain access to their own imaging. Whilst parents will be able to securely send images and videos to healthcare professionals – for example footage of stutters and communication issues for review by speech and language therapists.

Sectra is known widely in Europe and in geographies around the world for deploying enterprise imaging solutions that help healthcare organisations to enhance both clinical collaboration and patient access to in-demand diagnostic expertise.

Jane Rendall, Sectra’s managing director for the UK and Ireland, said: “Interoperable technology may be the requirement in this contract, but there will be a very human story to tell in its delivery. Healthcare professionals, patients, and their families will benefit from this initiative at Children’s Health Ireland – an exemplar in Ireland’s healthcare digital transformation. This is an exciting initiative that expands Sectra’s footprint in Ireland, and we look forward to working with teams to ensure technology delivers against their workflows and needs.”

The post Children’s Health Ireland to Transform Diagnostic Imaging Access with Sectra appeared first on .

Artificial intelligence (AI) has emerged as a potential solution for many of the issues encountered with COVID-19 pandemic. As research into this technology and its medical applications has increased, it now seems that AI could help prevent and manage the next pandemic. Here’s a closer look at how that might happen.

1. Outbreak Predictions

Any effective medical response hinges on early intervention. AI could facilitate such timely reactions by predicting disease outbreaks before they occur.

Recognizing the early signs of a disease and modeling how it might grow requires a complex understanding of multiple trends and how they interconnect. This kind of analysis is challenging for humans and conventional statistical models, but machine learning excels at it. Some AI applications have already achieved up to 95% accuracy in predicting outbreaks.

In addition to high accuracy, pandemic-predicting AI models work far faster than traditional means. Consequently, world health officials could monitor health reports in near real time with this technology to identify emerging epidemics before they spread. Professionals could then allocate resources to contain the disease before it reaches a tipping point.

2. Transmission Risk Identification

Similarly, machine learning algorithms can highlight areas or practices that may heighten transmission risks. Other models could identify potentially risky populations, such as frequent travelers or asymptomatic carriers. In both cases, AI reveals where change may be necessary to stop the spread of a disease.

A pre-COVID study found that AI monitoring stopped multiple outbreaks at hospitals by detecting possible pathogen transmission routes. During COVID-19, a different AI model nearly doubled the identification rate of asymptomatic travelers to inform safer border and travel policies. Similar applications in the future could help contain diseases before they become pandemics.

It’s not always outwardly clear what behaviors, environments or populations make pathogen transmission more likely until it’s too late. AI makes it easier to determine these risks ahead of time, informing healthier practices to minimize the spread of future infections.

3. Resource Distribution

While early recognition and preventive sanitation measures are crucial, effective interventions also require appropriate resource allocation. Health officials can only stop an outbreak if they know where to deliver which medicines, staff or technologies to enable the greatest possible help. AI clarifies these decisions.

Many health systems have already adapted to become remarkably effective in this regard. Health and Human Services was able to distribute nearly 200,000 monkeypox vaccines within weeks to stop the disease from becoming a COVID-level pandemic. AI can take things further by predicting high-risk areas to reveal which locations demand the most attention.

High-priority areas and treatments may vary between different diseases, making conventional practices fall short. AI can adapt its predictions according to new data, letting it inform health departments of the most up-to-date trends for more reliable triage and resource distribution.

4. Streamlined Vaccine Research

In cases like COVID-19, where there is no existing vaccine, AI can accelerate research and development to enable needed breakthroughs in minimal time. While this does not necessarily prevent pandemics, it does help medical professionals slow or even stop the spread faster.

The COVID-19 pandemic itself highlighted the potential of AI in this area. Pfizer and Moderna both used AI to help find and test potential drug candidates. As a result, they reduced vaccine development times from years to months without jeopardizing patient safety or regulatory assurance.

As more agencies and researchers employ these tools, machine learning will become increasingly reliable and efficient at aiding vaccine development. Other AI models could streamline clinical trials by facilitating data entry or highlighting ideal participant populations, further accelerating the process.

5. Staff Shortage Mitigation

Another barrier to effective pandemic responses that COVID-19 emphasized is the need for additional medical staff. AI can address this obstacle thanks to its ability to automate administrative tasks, enabling limited workforces to perform more work.

One health care system was able to handle 7% more surgical cases despite closing 20% of its operating rooms because of AI-driven efficiency improvements. When AI handles much of the nonmission-critical, data-heavy work, hospital staff can focus on direct patient care. Such a freeing of resources could prove vital in responding to an early outbreak.

Reducing workloads would enable even highly workforce-constrained areas to take on a greater patient volume. As a result, responses would be more ready to manage a sudden outbreak, helping control the issue before it spreads too dramatically.

AI Could Revolutionize Pandemic Preparedness

While many of these use cases are still in the early stages of development, AI’s potential in pandemic prevention is hard to ignore. This technology has already proved itself to some extent throughout the world’s COVID-19 response, and additional research could take the possibilities further.

As these five applications illustrate, AI has many uses in a pandemic outbreak preparedness and response. Health care systems may be able to stop future pandemics from happening by investing carefully in these areas.

By Zac Amos, ReHack

The post Can AI Help Prevent the Next Pandemic? appeared first on .

In today’s dynamic healthcare landscape, where scientific information evolves rapidly and access to medical experts is crucial, the need for highly trained MSLs is paramount. Yet, while the vast majority of MSLs want training, only two-thirds report that these opportunities are available to them, and almost 40% state that they lack time for professional upskilling.²

Current Pain Points in MSL Training

In addition to a lack of time, MSL training is plagued by a range of issues, including geographical barriers for global companies, which can make it challenging to deliver consistent training if opting for in-person delivery. Traditional in-person training also comes with substantial cost barriers and logistical hurdles, as well as the risk of information overload if delivered as multi-hour or multi-day live events. In turn, this can reduce MSL engagement and negatively impact knowledge retention.

Further, with rapidly evolving scientific information, data, and guidelines, there is a clear need for continuous learning and knowledge reinforcement. However, considering how busy MSLs are with other priorities, this can be challenging if opting for a traditional approach to training.

Finally, accurately measuring and demonstrating the effectiveness of training in terms of its impact on MSL performance and knowledge retention can prove a challenge.

Training Needs for MSLs in Today’s Evolving Landscape

For training to be effective, the Medical Affairs Professional Society (MAPS) identified that it needs to be:³

• Practical and able to be used immediately.
• Technology-based, flexible, and available whenever, wherever the trainee wants to access it.
• Available in multiple formats.
• Consumable as individual, low-commitment offerings but placed within a larger framework.
• Collaborative and engaging, with learning enhanced by mentoring, gamification, accountability partnering, collaborative case study reviews, and more.
• Relevant and streamlined to reduce the cognitive load and improve the learning experience.

With these points in mind, the importance of leveraging digital tools and cutting-edge technologies becomes evident.

Digital Tools for MSL Training

Luckily, there is no shortage of digital tools available for MSL training. Some important examples include:

1. Asynchronous e-Learning Platforms
   These ‘over-time, anytime’ platforms offer versatile learning opportunities for MSLs: from hosting on-demand videos, podcasts, and written materials to interactive infographics and posters, digital journal clubs, quizzes, online case studies, and more. Adding a well-maintained resource center to serve as a knowledge repository/central information hub further helps ensure consistent and accurate information dissemination.

2. Mobile Learning and Microlearning

Mobile apps and micro modules—short, focused learning modules—are ideal for providing on-the-go knowledge reinforcement and just-in-time learning. Having this option available alongside other, more comprehensive tools enhances accessibility and convenience for busy MSLs.

3. Virtual Reality (VR), Augmented Reality (AR), and Holovision Technology

VR, AR, and Holovision technology represent novel tools that can be used to create a variety of immersive training experiences, both for MSL- and external healthcare provider (HCP) education. Examples include simulation of patient or HCP interactions, including objection-handling, as well as disease state, mechanism, and clinical data visualizations. These technologies are also ideal for case-based learning.

4. Artificial Intelligence (AI)-powered Tools

AI-powered learning paths can be used to tailor education to individual needs and preferences. For example, AI chatbots can provide instant answers to MSL queries, and AI avatars can be used to enhance case-based learning. While still in its infancy, there are vast opportunities for AI-based MSL training.

Benefits of Digital MSL Training

Leveraging digital technologies for MSL training comes with numerous benefits, including:

1. Increased Accessibility and Flexibility

Digital platforms eliminate geographical barriers, allowing MSLs to access the same high-quality training irrespective of location or time zone. This ensures consistency in knowledge and skills across global teams. The asynchronous nature of virtual training technologies means that MSLs can access training materials at their convenience, without the need to travel to a central location for training. This flexibility is crucial for MSLs—who often spend substantial time out in the field—to fit learning into their busy schedules.

2. Enhanced Engagement and Knowledge Retention

Interactive training modules that incorporate simulations, quizzes, and gamified learning experiences are known to increase engagement and improve knowledge retention compared to passive learning formats. The digital learning format also allows for the incorporation of videos, animations, and interactive visuals, which further enhances the learning experience and caters to different learning styles. In addition, by leveraging novel tools such as VR, AR, and holovision technology, MSLs can practice real-world scenarios, such as objection handling or presentations at medical conferences, in a safe and controlled environment, leading to enhanced learner confidence.

3. Improved Training Effectiveness and Performance

Digital platforms can track MSL progress over time and identify areas where they need additional support much easier than what can be done with traditional learning approaches, allowing for more personalized learning and continuous support. Likewise, data analytics can be used to assess the overall effectiveness of the training, enabling easy identification of potential areas for improvement.

4. Up-to-date, Consistent Information

Digital platforms and centralized knowledge hubs allow for the rapid dissemination of new scientific information, clinical trial data, and treatment guidelines, ensuring that MSLs are always up-to-date with the latest developments. The use of digital tools also ensures that all MSLs in a company receive the same consistent messaging, regardless of their location.

5. Enhanced Collaboration and Communication

Through the use of online forums and discussion boards, MSLs can seamlessly share best practices, ask questions, and collaborate with colleagues on their own schedules. Virtual meetings and webinars can be added as needed to enhance knowledge-sharing and collaboration further.

6. Reduced Training Costs

Lastly, digital training largely eliminates the need for physical training materials, travel, accommodation, and venue rentals, thereby significantly reducing training costs. Digital platforms can easily be scaled to accommodate large MSL teams, making them a cost-effective solution for global pharmaceutical companies.

Implementation Considerations

Before implementing a new digital training course, life science companies should first evaluate and select the appropriate digital training platform and technology based on their specific needs. Depending on the technology chosen, there may be a need to proactively promote user adoption and address potential resistance to digital training. After its launch, it will be key to conduct ongoing evaluations of the program and technology to optimize the training. Companies may also want to consider working with a single, one-stop provider for all training needs—technological, strategic, and content—to further streamline the process.

By Natalie Yeadon, President & CEO Impetus

References

1. http://themsls.org/what-is-an-msl/
2. http://www.onemsl.com/wp-content/uploads/2022/05/One-MSL-Global-Survey-2022-Findings-Report-MSLs.pdf
3. http://medicalaffairs.org/training-medical-science-liaisons-msl/

The post The Future of MSL Training – How Digital Technologies Are Shaping Success appeared first on .

Diagnostics delays in the UK

An ageing population is identified as the most significant driver of increased healthcare needs, since it is often accompanied by long-term conditions such as diabetes, breathing difficulties, or depression. It is estimated that by 2040, 9.1 million people in England will be living with major illness, an increase of 2.5 million people compared to 2019.^[ii]

Early and efficient diagnosis is critical to enable early treatment and reduce avoidable admissions. The Darzi report highlights that underinvestment in diagnostics extends the stay of patients in hospital, lamenting that, “Despite the first clinical use of MRI taking place in an NHS hospital, the health service has far fewer MRI and CT scanners than comparable countries. Moreover, many of the machines are old: this means that they are less powerful and so take longer for each scan and that more time is lost due to breakdown and maintenance.”

Why go mobile?

One solution to expand diagnostic capacity is to increase the use of mobile diagnostics services. Most imaging types now have mobile versions, including ultrasound, X-ray, MRI, CT and PET. These have multiple advantages. Hospitals that do not currently have the capacity to set up new diagnostic centres can immediately benefit from high-quality equipment by bringing a mobile unit on site. This also minimises transfer time between departments or even hospitals, meaning the patient receives a faster diagnosis. Mobile diagnostics services can be deployed according to demand and need, helping the NHS and private healthcare providers in the most pressurised hospital or in remote areas.

However, mobile diagnostics units require a significant capital commitment, and, in addition to the cost of obtaining the equipment in the first place, providers may need to upgrade the equipment periodically. This is where specialist financiers can support, enabling investment by spreading the cost over an agreed period, and in alignment with the expected benefits. Specialists bring in-depth understanding of the industry and the technology, so they can offer a solution that is a better fit than standard financing terms.

Custom solution for London cancer hospital

In one example, Fairford Medical Ltd deployed equipment and technology finance from Siemens Financial Services to provide mobile MRI scanning for a London cancer hospital.

Fairford Medical Ltd, a family-owned Managed Equipment Services provider, launched in 2016 and has since supplied rental contracts for medical imaging equipment in mobile and relocatable forms for NHS and private healthcare clients across the UK.

One customer, a prestigious cancer hospital in London, required a high-quality MRI mobile unit while rebuilding and replacing its onsite scanning centre over a 9-month period. Fairford did not yet have a unit suitable to the hospital’s technological or spatial requirements and therefore needed to custom-build the solution.

Matthew Bradfield, Managing Director, Fairford explains, “We recognised a growing market demand for these types of high-spec mobile imaging solutions, so we wanted to invest in upgrading our fleet.” At the time, Fairford was technically a new-starter and therefore wanted to preserve cash flow and avoid a significant capital outlay. The company turned to Siemens Financial Services (SFS) for a tailored leasing solution.

Affordable investment in mobile diagnostics

As Bradfield explains, “We wanted to use equipment from Siemens Healthineers and who better to understand the nature and purpose of a particular model than SFS. That integration was a huge benefit throughout the process.” As Fairford wanted to keep monthly payments manageable, SFS suggested a hire purchase arrangement. Under the agreement, Fairford paid the VAT upfront and had fixed low monthly instalments, enabling a transparent payment plan. At the end of the arrangement Fairford will automatically own the equipment outright.

The company built a relocatable trailer in Holland, equipped with a MAGNETOM Aera 1.5T MRI from Siemens Healthineers. The scanner enables a higher throughput of patients per day and accommodates a large variety of patient sizes, shapes, and conditions without compromising on image quality. “Since installing the unit, the hospital has been able to support patients during renovations,” adds Bradfield. “Not only do we have a happy customer, we already have multiple requests for the mobile scanning unit once this contract ends.”

Sally-Anne Whybrow, Sales Manager – Public Sector and Healthcare Finance at Siemens Financial Services comments, “The success of the mobile unit thus far demonstrates the growing demand for the solutions that Fairford offers. Finance from SFS helped the business to expand faster and we hope to continue to support Fairford’s expansion in the future.”

This is a story of how one business leveraged private finance to grow faster, but it also demonstrates the power of financing and of private healthcare providers in alleviating some of the burden on healthcare services. Mobile imaging centres can make a real difference and specialist finance providers are well placed to enable a broader rollout of mobile services.

By Sally-Anne Whybrow, Healthcare Business Development Manager, Siemens Financial Services

We’ll be at UKIO on 2-4 June at Stand A11, so if you’d like to connect in person and learn more about how we can help support investment in diagnostics, meet us there.

Learn more about the range of healthcare finance solutions here. SFS has also produced a Healthcare Leaders Briefing Series that explores the priority investment areas for transformative healthcare. Read the reports and sign up to receive updates here. 

[i] http://assets.publishing.service.gov.uk/media/66f42ae630536cb92748271f/Lord-Darzi-Independent-Investigation-of-the-National-Health-Service-in-England-Updated-25-September.pdf

[ii] http://www.health.org.uk/news-and-comment/news/25-million-more-people-in-england-projected-to-be-living-with-major-illness-by-2040

The post Extending the Reach of Mobile Diagnostics with Smart Finance appeared first on .

Across the modern pharma organisation, overstretched clinical, regulatory, quality, and pharmacovigilance teams are rapidly becoming overwhelmed by the multiplying digital processes and IT systems they are required to use. The systems are increasingly sophisticated and complex, too, reflecting the latest tech capabilities and the rapidly-evolving regulatory requirements they map onto.

For teams to fully harness the potential of these advanced systems (e.g. next-generation regulatory information management systems, quality management, or safety systems), they must first know how to use them correctly. More often than not now, that requires more than designated upfront training then habitual system use. That’s if teams are to use new capabilities confidently, reliably and in a compliant manner.

It is for this reason that digital adoption platforms (DAP) are gaining traction in a pharma GxP compliance context, guiding users for instance in exactly how to input data at each step of a process via a series of handy in-app prompts. These platforms sit on top of cloud/web-based IT systems. These online overlays to target applications help to steer users through tasks such as form-filling and data entry, nudging the desired action at each stage, such as how to format data correctly, or adhere to a particular naming convention. DAPs can halve the investment needed in regular training, or e-learning materials creation; the same with post-go-live helpdesk support, say the main vendors.

An asset many companies already have

DAPs are already proven in centralised business functions like HR, where they have been shown to significantly boost user adoption of important applications such as Workday (total DAP spend was worth $621.5 million in 2023, and is forecast to reach $3.86 billion by 2032[1]).

This existing enterprise use means that many companies will already possess DAP licences. Extending the reach of those platforms would simply involve developing suitable materials for each new respective application.

DAPs can have a particular impact where users are faced with sophisticated systems, or those with complex features. In pharma clinical, regulatory, quality, and pharmacovigilance functions, their potential is significant. The current transition from document-based operations and health authority exchanges to data-driven decision-making, and the need to conform with comprehensive new and expanding standards such as ISO IDMP, compound the need to use new or updated systems correctly and to input good data reliably and consistently. Upfront training alone won’t ensure that individuals consistently conform to agreed naming conventions or data structures when inputting critical information. Use of DAPs/in-app prompts can drive a minimum 20% improvement in data accuracy[2].

Administrative considerations

DAPs do not touch or interact with a system’s data, which means they don’t present a new risk to security or data protection. Because the platforms are an overlay, they are infinitely agile and adaptable too. Where traditional e-learning materials often rely on liberal use of screenshots to highlight what to do where (soon rendered out of date as systems, fields, or data requirements are updated), DAPs can be readily amended on the fly. Given how frequently cloud applications can be refreshed, even within a year, this is a consideration worth keeping in mind.

DAP guides will ideally be tailored to particular roles, so that users are presented only with relevant prompts as they interact with a system. Individuals can opt to turn off the guides once they understand what’s required and are using the software routinely. Where issues remain, and help continues to prove of value, built-in HEART analytics (tracking Happiness, Engagement, Adoption, Retention, and Task Success) offer a useful source of feedback about specific points of difficulty in a system (handy for refining the system, or for improving initial training).

Optimising DAP for compliance impact

The value of each DAP guide depends on the quality and relevance of its content, so this should be created and honed for each user group or role, and refreshed as required. A popular feature of all DAPs is that they can be used very effectively to make system-related announcements to users as they log in, e.g. about changes to the system, or to data input requirements (rather than hoping a blanket email will reach all of those affected).

The platforms are also coming into their own as AI is introduced to a whole range of operational software. In common with any new technology, AI needs to be used carefully and correctly to ensure compliance and elicit reliable results. DAPs are ideal as a mechanism for this, to provide essential, step-by-step, in-app guidance.

Budget-wise, DAPs can boost the value of traditional training, allowing more of this to be elevated to more of a strategic role around the purpose of a new system, for example. This creates scope for companies to allocate their budgets and materials expenditure more efficiently. It is for all of these reasons and more that 2025 is expected to be a pivotal year for DAP in a pharma GxP compliance context.

More than anything, this is about bringing a more intuitive experience to users that complex systems may lack (but which is necessary to ensure consistency and compliance). If automatic, timely intervention saves guesswork, or avoids a delay as assistance is sought, the payback is self-evident.

Finally, DAP support is likely to become increasingly predictive, anticipating what users are trying to do – e.g. “It looks like you’re entering new drug substance and product information, do you need help?”; further ensuring they do what’s required. Interventions like these will be invaluable in the modern pursuit of consistent data of the highest quality.

About the author

Sabine Gölden is eLearning & training lead at MAIN5, a European consulting firm delivering digitally-enabled change in Life Sciences. Gölden can be reached via email at sabine.goelden@main5.de.

References

[1] Digital Adoption Platform Market Size, Share, Industry Analysis, Trends, Growth, 2032, Zion Market Research: http://www.zionmarketresearch.com/report/digital-adoption-platform-market

[2] Value of a DAP, white paper, Whatfix: http://whatfix.com/resources/whitepapers/value-of-a-digital-adoption-platform/

The post A New Tool for Fostering GxP System Compliance – Introducing the ‘DAP’ appeared first on .

The Highland Marketing advisory board has welcomed a new member – Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation.

Dr Broch brings a wealth of experience to the board, which debates issues in digital health and advises the specialist health tech agency and its clients on policy, procurement and implementation.

He is a GP partner at the Oakwood Lane Medical Practice in Leeds and medical director and chief clinical innovation and information officer at Leeds Health and Care Partnership, which unites organisations from across the city to improve health and wellbeing.

“What drives me is trying to make the experience of the NHS better for staff and for patients,” he says. “Most of what we do is communication, whether that is consulting with patients or with colleagues.

“Digital has a huge role to play in bringing together fragmented services, removing duplication during handovers, and improving the experience of care for patients. I’m also interested in using data for quality improvement and for population health management.

“And also in how we can be clear about what we are trying to achieve, collectively, and how we can deliver maximum value for patients with the resources available to us.”

Dr Broch is joining the Highland Marketing advisory board at a difficult but potentially exciting inflexion point for health tech.

The NHS is facing huge demand and financial pressure, and the government has embarked on a rapid reorganisation of its central and commissioning bodies, which have important roles in delivering infrastructure, national systems, and data collection and analysis.

Yet the government is also committed to a shift from analogue to digital as part of its 10 Year Plan for Health, which will also seek to shift care from hospital to community, and from treatment to prevention.

Dr Broch says: “I am optimistic. Yes, we have had the pandemic, and there are questions about funding and capacity, and we need to address inequalities. But there are things that put us in a good position for the future.

“We have electronic health records in place, we have more data than ever before, so we can start measuring the things that really matter to people, and there is a lot of new technology coming on stream.

“There are still issues that we need to address around infrastructure, and integration, and taking people with us, but I think we are on the cusp of real change.”

Highland Marketing is an established research, PR, marketing and sales acceleration agency with more than 20 years’ experience in digital health. Its advisory board is comprised of experts working in NHS health tech and leading suppliers.

“I think the best way to learn and to challenge yourself is to be part of conversations,” Dr Broch adds. “When you look around the table, there are lots of people with different expertise, so being part of that feels like a huge opportunity.”

Mark Venables, chief executive of Highland Marketing, said: “We are very pleased that Dr Broch has agreed to join our advisory board. Primary care is a critical sector of the NHS. It is also one that digitised early and has continued to innovate.

“That means it is vital that the primary care perspective is considered when further digital developments are being discussed, planned, and implemented.

“Dr Broch will bring that perspective to the advisory board’s discussions and provide vital insight for our clients, who work in all areas of health tech and med tech.”

The post Dr Jason Broch joins the Highland Marketing Advisory Board appeared first on .

Within just 2.5 years, Generative AI has disrupted entire industries. For a time, its potential was constrained by the materials the technology was exposed to; then the ability to understand this in context. But with escalating momentum those limitations are being overcome. This is presenting a challenging duality: a future that is already here, yet still largely unknown. In life sciences, where an advantage lost could mean patients missing out, companies are wondering how on earth they move forwards?

The unstoppable force of AI

GenAI is the branch of artificial intelligence that uses everything that is known already to create something new. From early conversational capabilities, through reasoning, the technology is already delivering ‘agentic’ capabilities (goal-driven abilities to act independently and make decisions with human intervention only where needed).

There are early signs too that “innovating AI” is emerging. That’s as AI becomes capable of creating novel frameworks, generate fresh hypotheses, and pioneer new approaches. This creative potential pushes AI from merely processing information to actively shaping the future of scientific discovery, applying it to problems yet to be solved.

At the core of the latest GenAI advances is the accelerated pace of large language model (LLM) development. These deep learning models, trained on extensive data sets, are capable of performing a range of natural language processing (NLP) and analysis tasks, including identifying complex data patterns, risks and anomalies. A growing movement towards open-source GenAI models, meantime, is making the technology more accessible and customisable (alongside proprietary models).

Reimagining scientific discovery and deep research

In life sciences, there are persuasive reasons to keep pace with and harness latest developments as they evolve. GenAI is poised to become a gamechanger in scientific discovery and new knowledge generation – at speed and at scale.

In human intelligence terms, we have already reached and surpassed human expertise levels[1]. Recent advancements in Agentic AI models have even led to the need for a new benchmark[2].

The advanced reasoning promise, a highlighted benefit of DeepSeek’s latest AI model, has enormous scope in science (enabling logical inferences and advanced decision-making). Google and OpenAI both have Deep Research agents that go off and perform their own searches, combining reasoning and agentic capabilities. As reasoning capabilities continue to improve, and as the technology becomes more context-aware, the potential to accelerate scientific discovery becomes real through the creation of new knowledge. The ability to project forward, and consider “What if?” and “What next?”.

Already OpenAI’s Deep Research is optimised for intelligence gathering, data analysis and multi-step reasoning. It employs end-to-end reinforcement learning for complex search and synthesis tasks, effectively combining LLM reasoning with real-time internet browsing.

Meanwhile Google has recently introduced its AI co-scientist[3], a multi-agent AI system built with Gemini 2.0 as a “virtual scientific collaborator”. Give it a research goal, and off it will go – suggesting novel hypotheses, novel research and novel research plans.

Which way now?

With all of this potential, the strategic question for biopharma R&D becomes one of how to keep pace with all of these technology developments and build them into the business-as-usual; how to prepare for a future that is simultaneously already here yet continuously changing shape?

Up to now, most established companies have experimented with GenAI to see how it might address everyday pain points in Safety/Pharmacovigilance, Regulatory, Quality and some Clinical and Pre-Clinical processes. These activities been largely about becoming familiar with the technology, and assessing its trustworthiness and value. Others have gone further, creating lab-like constructs for experimentation.

Yet the hastening pace of technology development, and the intangibility around what’s coming, means that the industry now needs to embed AI more intrinsically within its infrastructure and culture. This is about proactively becoming AI-ready rather than simply “receptive to” what the technology can do.

Being discerning as “experts” hover

In the past, a popular approach to a hyped new technology or business change lever has been to “pepper” associated champions across the business. In this case, some organisations are taking a venture-capital like approach of bringing in non-native AI talent to key roles – visionaries and master-crafters from other industries. But AI is moving so quickly, and its likely impact is so fundamental to life sciences, that experts need to be “neck deep” in it to be of strategic value.

One of the biggest challenges now is the duality companies are now grappling with: the simultaneous need to be ready for and get moving with deeper AI use today, while gearing up for a tomorrow that is likely to look very different. This has widespread “change” implications: at a mindset and method level; and from a technical and cultural perspective – both today and tomorrow.

For this reason, strategic partnerships are proving a safer route – with tech companies that are fully up to speed with the latest developments, are enmeshed in it and its expanding application, and are actively building sector-specific solutions. Even so, companies will need to choose their AI advocates wisely, as “AI washing” is commonplace among consultants and service providers now, as new converts to the technology inflate their credentials in the field.

The good news is that internal IT and data teams are well versed in AI technology today, and have high ambitions for it. The challenge is bringing the technology’s potential to fruition where it could make a difference strategically. This is likely to require involve sitting with an organisation’s real problem areas, and understanding if and how emerging iterations of AI might offer a solution.

About the author

Jason Bryant is Vice President, Product Management for AI & Data at ArisGlobal, based in London, UK. A Data Science Actuary, he has built his career in fintech and healthtech, and specialises in AI-powered, data-driven, yet human-centric product innovation.

[1] Measuring Massive Multitask Language Understanding, Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt (ICLR 2021): http://arxiv.org/pdf/2009.03300

[2] Humanity’s Last Exam, November 2024, http://agi.safe.ai/

[3] Accelerating scientific breakthroughs with an AI co-scientist, Google Research blog, February 2025: http://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/

The post Preparing for the Unfathomable: Staying ahead of AI appeared first on .