Digital technology has made a mark on just about every part of our lives, and more recently, in healthcare. For years, we relied solely on arm cuffs to check blood pressure and thermometers to measure body temperature. Now, these measurements can be taken from wearable devices, such as smartwatches and smart rings. Similarly, neurologists have historically relied on invasive and expensive procedures, such as lumbar punctures and positron emission tomography scans, to indicate the presence of neurological diseases, but new digital approaches may enable a whole new paradigm for detecting, assessing, and monitoring these diseases.
The digitization of healthcare is beginning to revolutionize the way we prevent, diagnose, monitor, treat, and manage health conditions. Digital biomarkers can both enhance the health measurements we have today and pioneer new measurements tomorrow. They may enable healthcare to move from a reactive to a preventive approach.
What are digital biomarkers? Below we detail everything you need to know about digital biomarkers, from important terminology to their significance in healthcare.
Before we jump into the significance of digital biomarkers, let’s introduce some important terminology to help you understand what digital biomarkers are.
Term |
Definition |
Traditional Biomarker |
Traditional biomarkers, or biological markers, are an integral part of clinical practice as well as biomedical research. A traditional biomarker refers to something that can be measured to reliably and accurately indicate the presence and severity of a disease or condition. Examples:
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Digital Biomarker |
Digital biomarkers are objective and quantifiable physiological and behavioral data that are collected and measured via digital devices, such as portables, wearables, implantables, and digestibles. Examples:
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Passive Digital Biomarker |
Passive digital biomarkers are simple digital biomarkers that are collected via unnoticed actions. Passive data from sensors integrated into wearable devices is generated when a user wears the device. Examples:
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Active Digital Biomarker |
Active digital biomarkers are digital biomarkers collected via prompted actions. Digital biomarker data can be generated and captured from smart devices, such as smartphones and tablets, when a user interacts with the device in response to an active prompt. Examples:
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There is an ever-growing wealth of health data as more individuals embrace digital health technologies, like Fitbits, Apple Watches, and Oura rings, among many others. As healthcare continues to undergo its technological transformation, more health data from diverse populations becomes available.
Large quantities of data can be paired with strong analytical tools, such as machine learning and other forms of artificial intelligence, to track trends and patterns within individuals and across populations. Artificial intelligence can then build models that weigh large data sets of digital biomarkers to detect diseases and disorders. Similarly, tracking granular, intra-individual changes of health longitudinally can help determine an individual’s risk for developing a disease or disorder.
Altoida is developing the world’s first Precision Neurology platform and app-based medical device to provide easily accessible assessment and monitoring of brain health as accurately and effectively as possible. Our device measures and analyzes nearly 800 active cognitive and functional digital biomarkers proven to be clinically significant through over 20 years of rigorous scientific research.
By completing a series of highly immersive and interactive augmented reality and motor activities on a smartphone or tablet, Altoida’s device provides robust measurements of brain health across 13 unique neurocognitive domains:
When paired with our innovative artificial intelligence, this method for collecting and analyzing active digital biomarkers will pioneer fully digital predictive neurological disease diagnosis. After our recent Breakthrough Device designation by the FDA, Altoida’s technology will provide individuals with a predictive score that will enable a highly accurate prediction of whether an individual aged 55 and older will or will not convert from Mild Cognitive Impairment to Alzheimer’s disease within 12 months.
To learn more about Altoida's Precision Neurology platform and device and what digital biomarkers are, contact us today.