Blood pressure, body temperature, hemoglobin A1c levels and other biomarkers have been used to detect disease for decades. While this information is essential for the management of chronic conditions, these and many other physiological measurements are typically recorded only periodically, making it difficult to reliably detect early meaningful changes.
In addition, biomarkers extracted from blood require inconvenient blood draws, can be expensive to analyze, and don’t always arrive at the right time.
Historically, continuously monitoring a person’s vital signs meant being in a hospital. But that is no longer true. Digital biomarkers, collected from wearable sensors or through a device, provide healthcare providers with a wealth of traditional and new data to accurately track and even predict a patient’s disease trajectory.
With cloud-based servers and advanced yet inexpensive sensors, both on the body and outside, patients can be monitored more effectively at home than in a hospital, especially when the sensor data is analyzed with artificial intelligence (AI) and machine learning technology.
Opportunities for digital biomarkers
A major opportunity for digital biomarkers lies in tackling neurodegenerative diseases such as mild cognitive impairment, Alzheimer’s disease and Parkinson’s disease.
Neurodegenerative disease is an important target for digital biomarker development due to a lack of easily accessible indicators that can help health care providers diagnose and manage these conditions. For example, a definitive diagnosis of Alzheimer’s disease today generally requires positron emission tomography (PET), magnetic resonance imaging (MRI) or other imaging studies, which are often expensive and not always accurate or reliable†
Cost savings and other benefits
Digital biomarkers can unlock significant value for healthcare providers, companies and, most importantly, patients and families, by detecting and delaying the development of these diseases.