By Sanius
Healthcare has become remarkably sophisticated at measuring disease, yet the way we collect those measurements has changed surprisingly little.
Most clinical decisions are still informed by isolated moments in time: a blood test, an MRI scan, a clinic appointment or a patient recalling how they have felt over the previous few weeks.
These remain fundamental to modern medicine and always will be, but they inevitably offer a snapshot rather than a complete picture.
The reality is that disease does not begin when a patient walks into hospital, nor does recovery pause until the next consultation.
Our physiology, behaviour and symptoms are changing constantly, and increasingly we have the ability to understand those changes as they happen. This is where digital biomarkers have the potential to reshape healthcare.
The term “digital biomarker” is often associated with wearable technology, but the technology itself is only part of the story.
A smartwatch recording heart rate, a patient completing a symptom questionnaire or a connected device measuring blood oxygen saturation simply generates data. That data only becomes a digital biomarker when it reliably helps us monitor, explain or predict a meaningful health outcome.
Changes in activity that precede deterioration, sleep patterns that correlate with treatment toxicity, or fluctuations in symptom burden that predict disease progression are all examples of digital biomarkers because they provide clinically relevant insight rather than simply recording information. The distinction is important.
The future of healthcare will not be defined by the volume of data we collect, but by our ability to translate continuous patient-generated information into evidence that improves decision-making.
This shift represents a fundamental departure from episodic care towards continuous understanding.
For patients living with chronic illnesses, cancer or rare diseases, much of their experience takes place between appointments, often beyond the visibility of clinicians.
Fatigue develops gradually, pain fluctuates daily, medication adherence changes over time and physiological deterioration rarely begins the moment a patient arrives in hospital.
Historically, these changes have either gone unrecorded or relied entirely on retrospective recall. Digital biomarkers offer an opportunity to understand health as an ongoing journey rather than a series of disconnected events.
Instead of asking patients how they felt over the last month, we can begin to understand how symptoms, physiology and behaviour evolve together over weeks, months and years.
Across Sanius Health’s ecosystem, the company’s philosophy has underpinned our work long before digital biomarkers became a widely used term.
Their objective has never been to collect more data for the sake of it, but to build a richer understanding of patients living with complex conditions.
Across rare diseases, oncology and chronic illness, Sanius combines validated patient-reported outcomes with physiological measurements from FDA-cleared and CE-marked wearable technologies where appropriate, alongside medication adherence, quality of life, behavioural information, clinical pathway data, healthcare utilisation and long-term outcomes.
Individually, each of these datasets offers value.
Together, they begin to reveal patterns that would remain invisible if considered in isolation. It is within those patterns that clinically meaningful digital biomarkers emerge.
Traditionally, clinicians have relied upon scheduled reviews and patients’ recollection of how they have been feeling.
By combining symptom reporting with continuous information on activity, sleep, blood oxygen saturation and recovery, Sanius builds a much richer understanding of how patients respond to treatment between hospital visits.
A decline in activity alongside worsening fatigue and changes in physiological measurements may provide valuable context for clinicians long before those changes become obvious through routine follow-up alone.
The wearable data is not the biomarker; the relationship between those continuous signals and meaningful clinical outcomes is.
The same principle is perhaps even more compelling in sickle cell disease, where the burden of illness extends far beyond hospital admissions.
Vaso-occlusive crises remain one of the most recognised manifestations of the condition, yet many patients experience significant pain, fatigue and disruption to daily life without ever presenting to hospital.
Understanding disease purely through healthcare utilisation inevitably underestimates its true impact.
By combining patient-reported pain, medication adherence, sleep quality, activity, physiological measurements and quality-of-life data, it becomes possible to develop digital biomarkers that reflect the lived experience of sickle cell disease rather than simply the episodes captured within healthcare systems.
This has profound implications not only for patient care but also for research, service design and the way treatments are evaluated.
A similar opportunity exists across many rare and chronic conditions.
In myeloproliferative neoplasms, for example, fatigue, itching, cognitive impairment and reduced activity frequently have a greater impact on patients than laboratory results alone might suggest.
When these experiences are measured longitudinally alongside objective physiological information, they become more than subjective observations. They become measurable indicators of disease burden and treatment response.
This is particularly important in rare diseases, where patient populations are small, clinic visits are infrequent and disease progression varies considerably between individuals.
Every additional day of patient-generated information adds depth to our understanding, creating evidence that has historically been impossible to collect at scale.
The implications extend well beyond individual patient care.
Pharmaceutical companies are increasingly expected to demonstrate how treatments perform in the real world rather than only within controlled clinical trials.
Digital biomarkers strengthen real-world evidence by providing continuous, objective and longitudinal insight into treatment effectiveness, safety and quality of life. They help us understand not simply whether a therapy works, but how it influences people’s lives outside clinical environments.
They also create stronger foundations for artificial intelligence. AI is often presented as the solution to healthcare’s challenges, but algorithms are only ever as valuable as the data they learn from.
Continuous, high-quality patient-generated information allows AI to identify subtle patterns in treatment response, adherence, symptom progression and deterioration that would be almost impossible to detect using episodic healthcare data alone.
There are, of course, important challenges that must be addressed.
Digital biomarkers require robust clinical validation, standardisation and regulatory confidence if they are to become trusted components of routine care.
Interoperability between healthcare systems remains essential, as does ensuring that devices generate reliable, clinically meaningful information.
Equally important is maintaining patient trust through strong governance, transparency and responsible use of data. None of these challenges are insurmountable, but solving them will determine how quickly digital biomarkers move from promising innovation to accepted clinical practice.
The direction of travel is already clear.
Over the next decade, healthcare will increasingly move from reacting to illness towards anticipating it, from episodic assessment towards continuous understanding and from population-based treatment towards genuinely personalised care.
Digital biomarkers are not simply another category of health data; they represent a new way of understanding patients.
Organisations capable of responsibly combining patient-reported outcomes, wearable technology, physiological monitoring and longitudinal real-world evidence will not simply generate larger datasets; they will generate better insight.
Ultimately, that is what healthcare has always sought to achieve.
The next chapter of medicine will not be defined by measuring more, but by understanding more, and digital biomarkers will be one of the foundations upon which that future is built.
Learn more about Sanius at saniushealth.com
