Extraordinary advances in digital technology are allowing us to reimagine health and social care models to help confront the primary challenge of our times – an ageing global population with greater levels of chronic disease. The objective of this digitally enabled revolution is to provide better quality healthcare for more people, which is why I always consider connected health chiefly from the perspective of patient empowerment.
People are increasingly ready to accept the democratisation of their own care, as the proliferation of smartphones, health apps and wearable wellbeing devices proves. It is now up to industry to respond by shaping proactive connected health models that empower people with the information they need to take better care of their own health. The rate of adoption will vary by disease, but ultimately very few – if any – therapy areas will be off limits.
My role as Head of Intelligent Health at Cambridge Consultants (CC) involves helping companies get to grips with potentially transformative technology innovation. So, my colleagues and I are often asked by biopharma executives to share the state of play in digital health development. To deepen our insight, I joined up with CC’s parent Capgemini for a research initiative to explore connected health and its current benefits and limitations.
The resulting Capgemini Research Institute report1 confirms that the time is right for companies to accelerate their connected health commitment. We interviewed 523 executives from 166 biopharma companies across seven countries in North America, Europe, and Asia. 84% indicated that the market opportunity for connected health exceeds that of their traditional pharma business and will represent 13% of total revenue in five years’ time. Investment funding in digital health start-ups hit $57.2 billion in 2021, up 79% from 2020.
There’s no doubt in my mind that companies will be pushing at an open door. Earlier 2020 findings by the Capgemini Research Institute revealed that 46% of consumers – and 56% of those in the 23–38 age range – were comfortable using technology to manage their health. They will be able to benefit from connected health in a variety of ways. In an ideal future, improved centralised coordination will allow patient data to be automatically sent to physicians and added instantly to medical histories. And as well as being able to make their own healthcare decisions and take more responsibility for their own care, patients will benefit from better remote care and improved access at times and locations convenient to them.
“To successfully manage a disease or condition, we have to be able to measure it”
Measuring it to manage it
Let me dip into my day-to-day work at CC to reveal a little more detail about the innovation that is enabling this increasingly connected future. Right now, we’re helping clients to develop the technology that sits at the heart of a number of smart products and systems, including implantable devices, wearables and surgical systems. The deep technical and scientific understanding of our development teams is core to everything – including fundamental components such as novel sensors.
To successfully manage a disease or condition, we have to be able to measure it. We do this with digital biomarkers – essentially any physiological or biological signal that is captured digitally. They range from general measurements such as glucose levels or blood pressure to something very specific like a genetic marker.
Clinically, these biomarkers can be applied in different ways during the patient care pathway. At the early stage sits susceptibility or risk biomarkers, which indicate the potential for an individual to develope a disease. Cognitive changes in healthy subjects could denote a risk of developing Alzheimer’s, for example. Then there are diagnostic biomarkers that are already in common use to detect the presence of conditions such as asthma. Further up the pathway are pharmacodynamic response biomarkers used to show that a biological response has occurred after a patient has taken a medical product.
We’re working with companies both large and small to develop not just the sensing and reporting technology involved, but also the strategic approach. This can include defining key biomarkers and identifying small providers with unique information or sensing capabilities that might help provide objective data outputs in challenging conditions such as in mental health.
With the advent of new sensors, it’s now possible to provide continuous monitoring of a wider range of diseases. Advances across analytics, artificial intelligence (AI) and smart algorithms means it’s also possible to automate data analysis and present information to the user in a way that allows them to act. A good example of this is diabetes. Abbott’s FreeStyle Libre allows patients to take control of their condition in a more engaged way. The system automatically calculates the percentage time the user spends with their glucose level in their target range. This ‘time in range’ approach replaces the traditional HbA1c metric and reduces the number of harmful hypos and hypers.
We’re seeing similar progress with inhalers. Many pharma companies have added sensing, initially to measure how devices are being used. But now companies such as Teva have demonstrated (in the lab at least) that they can use the sensing data to predict exacerbations – asthma attacks – before they happen. This potentially allows intervention that prevents hospital visits.
As I’ve already mentioned, much of the current focus is on developing and identifying the key sensing technologies that can measure accurately enough to be medically useful – but slip seamlessly into people’s lives. A promising emerging technology here is integrated photonics, which allows skin sensing of biomarkers such as glucose and lactate via a wrist-worn device. A prime example of players in this space is Rockley Photonics, who recently announced partnerships with consumer and healthcare companies for their ‘clinic on the wrist’2.
As ever with healthcare, the issue of risk is top of mind, and perhaps explains why the adoption of connected technologies appears slow. If a device is going to be trusted, a huge amount of time and effort must go into the design of the sensors, software, and human use validation to ensure that the information provided is accurate and readily interpretable by the end user.
That said, we’re beginning to see approved medical devices in what would have traditionally been thought of as a consumer market. For example, at least three major consumer technology manufacturers have Food and Drug Administration (FDA) approved heart health alerts in their consumer wearables, and these data can be made available to their doctors via connected platforms. Where expert users are available and ready for their skills to be augmented, adoption can afford to be much faster. Robotic surgery, for example, has been available for nearly 40 years and we’ve used fluorescence-guided real-time biomarker sensing in keyhole surgery for about a decade.
If there is a sense within the industry that adoption is slower than it could be, I don’t think this is universally true. Even within the same organisation, the adoption of connected technologies can vary wildly because applicability is very disease specific. However, acceleration of adoption is well under way; a number of companies are pushing the envelope of what’s possible and will be releasing advanced AI and biomarker-based features in the next two to five years. Both the healthcare professional and consumer spaces will be subjected to significant disruption