To understand what a digital biomarker is, we first must define what a biomarker is. A joint task force from the Food and Drug Administration and the National Institutes of Health defined a biomarker as a ‘defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention’[cite]. Simply put, a biomarker is a marker used to explain, influence, and/or predict health-related outcomes [cite].
Digital Biomarkers, then, are biomarkers developed from digitally collected data. Specifically, digital biomarkers are digitally collected data (e.g. intraday glucose levels from a continuous glucose monitor) that are transformed into indicators of health outcomes (e.g. glucose variability). They can be used to provide biomedical insights or improve health decision-making (e.g. encourage healthy lifestyle changes) [cite]. Digital Biomarkers often rely on longitudinal data, which helps create a more comprehensive picture of a person’s health and wellness.
Digital biomarker development is a rapidly growing field: in the past decade, the number of digital biomarker studies indexed in PubMed has increased 325% [cite]. In this article, we will explore some of the exciting new digital biomarker research published in 2021.
A very recent, exciting new digital biomarker has been developed by researchers at the University of California San Diego for early detection of pregnancy [cite]. Using temperature data from the Oura ring wearable, the researchers developed an algorithm to detect pregnancy an average of 9 days before they received a positive at-home pregnancy test. Previous studies have shown that daytime temperature from a wearable can be used to track the menstrual cycle and ovulation[cite]. This new research uses both daytime and nighttime temperature to predict pregnancy, with high degrees of accuracy. Automated, early pregnancy detection could substantially improve maternal and fetal health.
Glucose monitoring (via continuous glucose monitors or finger-sticks) has always been an invasive process. Only 63% of people with diabetes report checking their glucose levels at least once per day, and glucose monitoring is significantly less common in those with prediabetes (which makes up a third of the US population!). This creates a significant unmet clinical need for noninvasive glucose monitoring tools [cite]. Using noninvasive wearables and food logs, researchers at Duke University have recently developed digital biomarkers of glycemic health [cite]. Features spanning stress, activity, and circadian rhythm were used to predict glucose levels and classify personalized glucose levels.
Wouldn’t it be nice to know you’re getting the flu before you start to feel sick? Well, now digital biomarkers from a wearable smartwatch are able to predict the flu and common cold 24 hours before you get symptoms! Researchers from Duke University, the University of Michigan, the University of Virginia, and Imperial College London have demonstrated that noninvasive, wrist-worn wearable devices can be used to detect acute viral respiratory infection and predict infection severity before symptom onset [cite]. The authors describe the impact of these digital biomarkers: “Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.”
A growing body of evidence indicates that cognitive, sensory and motor changes may precede clinical symptoms of Alzheimer’s disease by several years and sensory and motor (non-cognitive) changes can help detect a neurological or neurodegenerative disease 10 or 15 years prior to their diagnosis [cite]. At the American Academy of Neurology conference earlier this year, nQ Medical presented preliminary data on its development of digital biomarkers for Alzheimer’s cognitive assessment [cite]. Through a set of four typing and touchscreen tasks on a smart device and prediction algorithms, they have developed digital biomarkers that can be applied in clinical diagnosis and assessment of Alzheimer’s disease.
Research in digital biomarker development spans fields and disease states, from pregnancy to glycemic health to early flu detection to Alzheimer’s disease, and can conceivably be applied to any area of health, wellness, and medicine. While digital biomarkers may seem like science fiction, recent research innovations are demonstrating the potential to use digitally collected data to improve health outcomes.
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