From population-based to personalized laboratory medicine: continuous monitoring of individual laboratory data with wearable biosensors

• Published in: Critical reviews in clinical laboratory sciences Vol. 62; no. 3; p. 198
• Main Authors: Coskun, Abdurrahman, Savas, Irem Nur, Can, Ozge, Lippi, Giuseppe
• Format: Journal Article
• Language: English
• Published: England 01.05.2025
• Subjects: Biosensing Techniques - instrumentation; Biosensing Techniques - methods; Humans; Monitoring, Physiologic - instrumentation; Monitoring, Physiologic - methods; Precision Medicine - methods; Wearable Electronic Devices; diagnosis; personalized laboratory medicine; body fluids; Biosensors; monitoring
• ISSN: 1549-781X
• DOI: 10.1080/10408363.2025.2453152

Monitoring individuals' laboratory data is essential for assessing their health status, evaluating the effectiveness of treatments, predicting disease prognosis and detecting subclinical conditions. Currently, monitoring is performed intermittently, measuring serum, plasma, whole blood, urine and occasionally other body fluids at predefined time intervals. The ideal monitoring approach entails continuous measurement of concentration and activity of biomolecules in all body fluids, including solid tissues. This can be achieved through the use of biosensors strategically placed at various locations on the human body where measurements are required for monitoring. High-tech wearable biosensors provide an ideal, noninvasive, and esthetically pleasing solution for monitoring individuals' laboratory data. However, despite significant advances in wearable biosensor technology, the measurement capacities and the number of different analytes that are continuously monitored in patients are not yet at the desired level. In this review, we conducted a literature search and examined: (i) an overview of the background of monitoring for personalized laboratory medicine, (ii) the body fluids and analytes used for monitoring individuals, (iii) the different types of biosensors and methods used for measuring the concentration and activity of biomolecules, and (iv) the statistical algorithms used for personalized data analysis and interpretation in monitoring and evaluation.