Gatifloxacin detection in the nanoscale: a review exploring current biosensing technologies and future opportunities

Abstract

Addressing the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (good health and well-being), SDG 6 (clean water and sanitation), SDG 9 (industry, innovation, and infrastructure), and SDG 15 (life on land) necessitates robust and accessible diagnostic tools for effective healthcare management and combating global health threats. Antimicrobial resistance (AMR) poses a formidable challenge to global health, with fluoroquinolones, a critical class of broad-spectrum antibiotics, facing increasing resistance. Gatifloxacin, a widely used fourth-generation fluoroquinolone, is a prime example of a drug whose efficacy is threatened by emerging resistance mechanisms. This review delves into the growing concern of gatifloxacin resistance and highlights the urgent need for innovative strategies to combat this escalating public health crisis. The necessity of rigorous healthcare monitoring for fluoroquinolones, including precise Therapeutic Drug Monitoring (TDM), is emphasized to optimize patient outcomes and mitigate the development of further resistance. Traditional monitoring techniques, such as chromatography and immunoassay, while effective, often suffer from limitations in terms of cost, complexity, and real-time applicability for routine clinical settings. This review provides a comprehensive overview of the current landscape of gatifloxacin detection, focusing on the significant advancements in electrochemical and optical sensor technologies at the nanoscale. We critically evaluate the underlying principles, performance characteristics, and limitations of existing sensor platforms. Furthermore, a detailed analysis of prevailing research gaps is presented, specifically highlighting the nascent exploration of advanced biosensing platforms like immunosensors, aptasensors, and FET-based devices for gatifloxacin. The absence of integrated Lab-on-Chip, microfluidic, and MEMS-based solutions, alongside the underutilization of next-generation materials such as MXenes, Transition Metal Dichalcogenides (TMDs), and rare earth metal oxides, is critically discussed. The untapped potential of Artificial Intelligence and Machine Learning (AI/ML) integration for enhanced sensor performance and the glaring lack of clinically validated point-of-care (POC) devices for TDM, particularly those adhering to USFDA Bioanalytical Device guidelines, are identified as critical avenues for future research. This review concludes by outlining the future prospects for developing cutting-edge, nanotechnological biosensors that are sensitive, selective, rapid, and cost-effective, ultimately contributing to better management of gatifloxacin therapy and bolstering global efforts against antimicrobial resistance.