Electrochemical Chemically Based Sensors and Emerging Enzymatic Biosensors for Antidepressant Drug Detection: A Review

Int J Mol Sci. 2023 May 9;24(10):8480. doi: 10.3390/ijms24108480.

Abstract

Major depressive disorder is a widespread condition with antidepressants as the main pharmacological treatment. However, some patients experience concerning adverse reactions or have an inadequate response to treatment. Analytical chromatographic techniques, among other techniques, are valuable tools for investigating medication complications, including those associated with antidepressants. Nevertheless, there is a growing need to address the limitations associated with these techniques. In recent years, electrochemical (bio)sensors have garnered significant attention due to their lower cost, portability, and precision. Electrochemical (bio)sensors can be used for various applications related to depression, such as monitoring the levels of antidepressants in biological and in environmental samples. They can provide accurate and rapid results, which could facilitate personalized treatment and improve patient outcomes. This state-of-the-art literature review aims to explore the latest advancements in the electrochemical detection of antidepressants. The review focuses on two types of electrochemical sensors: Chemically modified sensors and enzyme-based biosensors. The referred papers are carefully categorized according to their respective sensor type. The review examines the differences between the two sensing methods, highlights their unique features and limitations, and provides an in-depth analysis of each sensor.

Keywords: antidepressants; chemically modified electrodes; electrochemical biosensor; enzyme-based electrochemical biosensors.

Publication types

  • Review

MeSH terms

  • Antidepressive Agents / therapeutic use
  • Biosensing Techniques* / methods
  • Depressive Disorder, Major* / drug therapy
  • Electrochemical Techniques / methods
  • Humans

Substances

  • Antidepressive Agents

Grants and funding

This research was funded by the Ibero-American Program on Science and Technology (CYTED—GENOPSYSEN, P223RT0141), by European Cooperation in Science and Technology (COST, ENOTTA-CA21147), and was also financially supported by Portuguese national funds through projects UIDB/50006/2020, UIDP/50006/2020, LA/P/0008/2020 and PTDC/QUI-QAN/3899/2021 from the Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES). Fatima Barroso (2020.03107.CEECIND) and João Pacheco (SFRH/BPD/101419/2014) are grateful to Fundação para a Ciência e a Tecnologia (FCT) and European Union (EU) for their grants, financed by POPH-QREN-Tipologia 4.1-Formação Avançada, funded by Fundo Social Europeu (FSE) and Ministério da Ciência, Tecnologia e Ensino Superior (MCTES).