Advances in Electrochemical Urea Biosensors: Trends and Future Prospects

Research output: Contribution to journalReview articlepeer-review

Abstract

Urea, a nitrogenous organic compound resulting from protein metabolism, is excreted as a waste product in urine. Elevated blood urea levels are associated with severe health conditions, including chronic kidney disease (CKD) and liver failure. Thus, monitoring urea levels is essential for CKD patients and individuals with metabolic disorders that heighten the risk of CKD. While existing diagnostic technologies offer high sensitivity and specificity, they are often expensive, require skilled operators, involve lengthy processing times, and are typically invasive and discontinuous. To address these challenges, researchers have developed various biosensor systems for rapid and cost-effective urea detection. This review provides a comprehensive overview of recent advancements in urea biosensing technologies, highlighting key challenges and potential solutions in biosensor design. It examines enzymatic and non-enzymatic urea biosensors, focusing on electrochemical detection techniques such as amperometry and potentiometry for enzymatic sensors and cyclic voltammetry for non-enzymatic sensors. Additionally, it explores material innovations, technological advancements, and strategies to enhance sensitivity, selectivity, portability, and stability. The integration of biosensors with IoT for real-time monitoring and their applications in medical diagnostics are also discussed.

Original languageEnglish
Number of pages25
JournalAdvanced Sensor Research
Early online dateDec 2025
DOIs
Publication statusPublished - 3 Dec 2025

Keywords

  • Amperometric sensing
  • Electrochemical biosensors
  • Enzymatic sensors
  • Non-enzymatic sensors
  • Potentiometric sensing
  • Urea detection
  • Urease-based sensors
  • Wearable biosensors

Fingerprint

Dive into the research topics of 'Advances in Electrochemical Urea Biosensors: Trends and Future Prospects'. Together they form a unique fingerprint.

Cite this