Next-Generation Digital Biomarkers for Tuberculosis and Antibiotic Stewardship: Perspective on Novel Molecular Digital Biomarkers in Sweat, Saliva, and Exhaled Breath.
Noe Karl BrasierMichael OsthoffFiorangelo De IesoJens EcksteinPublished in: Journal of medical Internet research (2021)
The internet of health care things enables a remote connection between health care professionals and patients wearing smart biosensors. Wearable smart devices are potentially affordable, sensitive, specific, user-friendly, rapid, robust, lab-independent, and deliverable to the end user for point-of-care testing. The datasets derived from these devices are known as digital biomarkers. They represent a novel patient-centered approach to collecting longitudinal, context-derived health insights. Adding automated, analytical smartphone applications will enable their use in high-, middle-, and low-income countries. So far, digital biomarkers have been focused primarily on accelerometer data and heart rate due to well-established sensors originating from the consumer market. Novel emerging smart biosensors will detect biomarkers (or compounds) independent of a lab and noninvasively in sweat, saliva, and exhaled breath. These molecular digital biomarkers are a promising novel approach to reduce the burden from 2 major infectious diseases with urgent unmet needs: tuberculosis and infections with multidrug resistant pathogens. Active tuberculosis (aTbc) is one of the deadliest diseases from an infectious agent. However, a simple and reliable test for its detection is still missing. Furthermore, inappropriate antimicrobial use leads to the development of antimicrobial resistance, which is associated with high mortality and health care costs. From this perspective, we discuss the innovative approach of a noninvasive and lab-independent collection of novel biomarkers to detect aTbc, which at the same time may additionally serve as a scalable therapeutic drug monitoring approach for antibiotics. These molecular digital biomarkers are next-generation digital biomarkers and have the potential to shape the future of infectious diseases.
Keyphrases
- healthcare
- heart rate
- infectious diseases
- multidrug resistant
- mycobacterium tuberculosis
- blood pressure
- type diabetes
- health information
- cardiovascular disease
- heart rate variability
- emergency department
- pulmonary tuberculosis
- end stage renal disease
- risk factors
- public health
- mental health
- machine learning
- chronic kidney disease
- high throughput
- newly diagnosed
- drug resistant
- deep learning
- pseudomonas aeruginosa
- escherichia coli
- mass spectrometry
- human health
- big data
- loop mediated isothermal amplification
- sensitive detection
- single molecule
- liquid chromatography
- current status
- patient reported outcomes
- peritoneal dialysis
- label free
- social media
- human immunodeficiency virus
- adverse drug
- ejection fraction