UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Smartphone Biosensors for Non-Invasive Drug Monitoring in Saliva

Awad, Atheer; Rodríguez-Pombo, Lucía; Simón, Paula Esteiro; Álvarez, André Campos; Alvarez-Lorenzo, Carmen; Basit, Abdul W; Goyanes, Alvaro; (2025) Smartphone Biosensors for Non-Invasive Drug Monitoring in Saliva. Biosensors , 15 (3) , Article 163. 10.3390/bios15030163. Green open access

[thumbnail of Smartphone Biosensors for Non-Invasive Drug Monitoring in Saliva.pdf]
Preview
Text
Smartphone Biosensors for Non-Invasive Drug Monitoring in Saliva.pdf - Published Version

Download (3MB) | Preview

Abstract

In recent years, biosensors have emerged as a promising solution for therapeutic drug monitoring (TDM), offering automated systems for rapid chemical analyses with minimal pre-treatment requirements. The use of saliva as a biological sample matrix offers distinct advantages, including non-invasiveness, cost-effectiveness, and reduced susceptibility to fluid intake fluctuations compared to alternative methods. The aim of this study was to explore and compare two types of low-cost biosensors, namely, the colourimetric and electrochemical methodologies, for quantifying paracetamol (acetaminophen) concentrations within artificial saliva using the MediMeter app, which has been specifically developed for this application. The research encompassed extensive optimisations and methodological refinements to ensure the results were robust and reliable. Material selection and parameter adjustments minimised external interferences, enhancing measurement accuracy. Both the colourimetric and electrochemical methods successfully determined paracetamol concentrations within the therapeutic range of 0.01–0.05 mg/mL (R2 = 0.939 for colourimetric and R2 = 0.988 for electrochemical). While both techniques offered different advantages, the electrochemical approach showed better precision (i.e., standard deviation of response = 0.1041 mg/mL) and speed (i.e., ~1 min). These findings highlight the potential use of biosensors in drug concentration determination, with the choice of technology dependent on specific application requirements. The development of an affordable, non-invasive and rapid biosensing system holds promise for remote drug concentration monitoring, reducing the need for invasive approaches and hospital visits. Future research could extend these methodologies to practical clinical applications, encouraging the use of TDM for enhanced precision, accessibility, and real-time patient-centric care.

Type: Article
Title: Smartphone Biosensors for Non-Invasive Drug Monitoring in Saliva
Location: Switzerland
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/bios15030163
Publisher version: https://doi.org/10.3390/bios15030163
Language: English
Additional information: Copyright © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: Colorimetric and electrochemical biosensing; RGB profiling; salivary excretions and biological fluids; patient-centric diagnostics; smartphone-driven analysis; mobile phone biosensor app; digital analysis; portable point-of-care diagnostics; digitised medication analysis; remote drug monitoring
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics
URI: https://discovery.ucl.ac.uk/id/eprint/10208051
Downloads since deposit
0Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item