What Do Digital Biomarkers Mean?

The spread of wearable digital technologies in healthcare generating big data entailed the appearance of a new type of medical information. They produce actionable insights into the biological state of individuals, just like “general” biomarkers, but are collected through digital tools.

Here’s our summary of what digital biomarkers mean and how they will be used in the near future.

The appearance of user-generated big data in healthcare

In the last couple of years, Fitbit, Jawbone, Apple Health, Withings, Garmin, Sleep as Android, WIWE, MocaCare, Skeeper – in other words, fitness trackers, step counters, health apps, sleep sensors, pocket ECG, blood pressure or other health parameter measuring devices appeared out of nowhere. By now, they are generating an astounding amount of data about patients and individuals not getting patient care. That’s what digital biomarkers are about.

According to Markets and Markets, the global market for medical wearable devices is projected to reach $30.1 billion by 2026, with the US being the largest market. Meanwhile, the global fitness wearable market (including smartwatches, fitness bands, smart glasses and smart clothing among others) is projected to grow to $114.36 billion in 2028. What is probably even more telling than the above figures is this: according to research from Insider Intelligence, more than 80% of US consumers are willing to wear fitness technology. No wonder over 530 million units were shipped in 2021 globally.

The exponential rise in data-generating devices naturally goes together with the growth of healthcare data. According to a White Paper by Cloud Angels, 2850 exabytes (one exabyte = one billion gigabytes) of health data were generated in 2021. Just to put this in context, the figure was 153 exabytes in 2013. The growth is… massive.

That data includes information from electronic medical records (medical imaging, patient history, etc.), genetic as well as patient-generated data. Even if looking only at the latter, the digital biomarkers themselves, that means an inconceivable amount of new information in the healthcare scene.

Digital biomarkers decoded

From the above statistics, the boundaries of digital biomarkers could also be determined.

X-rays or the results of a DNA test don’t belong to the area of digital biomarkers. On the other hand, Fitbit or Apple watch data does – fitness and wellness data constitutes a huge chunk of digital biomarkers, besides medical-grade information.

The second important factor is the digital nature of data collection. Although a traditional blood test could result in insightful biomarkers, they are not part of the digital universe.

Thus, the definition could be laid down as the following: digital biomarkers are data that consumers directly collect about health or disease management through digital health technologies to explain, influence and/or predict health-related outcomes.

RockHealth says that measured data only becomes a biomarker when it connects to a health-related outcome. If the blood pressure values are linked to cardiovascular risks, for example, that’s the point where it gets interesting for research.

digital biomarkers
Source: Brandon Bellinger: Continuous Digital Biomarkers from Wearable Devices

The application of digital biomarkers

When paired with analytical tools, these large volumes of data can be leveraged to track trends and patterns for both individuals and populations. Medical research has already recognised the tremendous potential of digital biomarkers, and there are plenty of studies underway to understand disease and health better.

For example, in February 2018, Evidation Health announced the launch of a 10,000-person chronic pain study. The research aimed to quantify chronic pain and develop digital biomarkers for chronic pain severity, flare-ups and quality of life by using activity trackers, health apps, and other more traditional data points. In the year-long study, participants used Apple Watches, Garmins, and Android Watches. The results can be found here.

Another interesting read is this article published in April 2022, discussing fitness tracker use in federally qualified health center patients.

Researchers started to look at elderly adults with dementia, and patients with Parkinson’s or Huntington’s through wearables, accelerometers, smartwatches, etc. Even the effect of digital pills was measured in a 2017 study, and it turned out that digital medicines indeed constitute efficient means to track medication intake.

The advancement of the past few years can be summarized in a single report: engineers at the University of California San Diego (UCSD) have developed a prototype of a wearable that can continuously monitor several health stats – glucose, alcohol, and lactate levels -simultaneously in real-time.

And we also have to mention one booming area: vocal biomarkers. Following the boost from the pandemic, today there are dozens of solutions that aim to diagnose the presence/severity of certain conditions based on audio clues (eg: from the voice, breathing patterns or cough of a patient). There are studies on determining speech biomarkers in Alzheimer’s, or detecting COVID from voice/cough and breathing patterns or using voice as a biomarker for chronic obstructive pulmonary disease.

What does the (near) future bring?

Digital biomarkers could significantly help in bringing healthcare from a reactive towards a more preventive approach, as researchers will not only be able to explain diseases better, but more and more data will be available to analyse what healthy, normal states signify and to predict future health outcomes. As a consequence, research into digital biomarkers will soar in the coming years.

However, there are several challenges to overcome in the near future.

  • Standardized solutions are needed to be able to compare studies carried out with digital biomarkers. When a clinical trial is conducted, the standardised procedure ensures that sampling means the same in every case, and thus results are comparable with other achievements. Regarding consumer-generated data, that’s not that evident. The framework in the case of measurements carried out with smartwatches or trackers could be completely different in each situation.
  • The reliability of some instruments is also questionable as not every wearable or health sensor is FDA- or CE-approved.
  • The details of the measurements could also be entirely different. An individual could measure ECG at home with five different tools. While the results will (should) be reasonably similar, the quality and details of the measurements differ significantly, which might be essential for the researcher.
  • Privacy and more generally, regulatory issues also constitute a matter of concern. While the consumer or patient measures digital biomarkers at home and sends the data to the researchers, how could anyone make sure that it doesn’t get to unauthorized persons? How will data protection and privacy look like?

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