Integrated microfluidic devices for point-of-care detection of bio-analytes and disease

Abstract

Micro- and nanofluidics have enabled the possibility of miniaturized analytical systems, which are commonly known as lab-on-a-chip (LOC) devices. One of the clear benefits of these microfluidic devices is the ‘sample-in-answer-out’ system, in which the input is a whole/minimally processed biological sample, and the output is a qualitative or quantitative diagnosis of biomarkers of disease or bio-analyte of interest. All the clinical protocols could be integrated into a well-designed LOC device, such as sample pre-treatment, sample/reagent manipulation, separation, reaction, and detection. Microfluidics and nanofluidics interactions revolutionize lab-on-a-chip diagnostics, offering cost-effective alternatives to clinical setups. This article looks at bioanalysis that uses fully integrated microfluidic devices and optical and electrochemical methods like amperometry, potentiometry, cyclic voltammetry, and electrical impedance spectroscopy. These technologies diagnose autoimmune diseases (rheumatoid arthritis, multiple sclerosis, type 1 diabetes, and Addison's disease), acute nutritional deficiencies (iron, vitamin A, D, B12, C, and K), and pharmacological response biomarkers. The purpose of this review is to examine the utility of microfluidics in the detection of biomarkers. Our analysis highlights the potential of microfluidic technologies to transform diagnostics and personalized healthcare by addressing existing issues and proposing new solutions. These systems address sensitive, rapid, and sample volume limits with their sophisticated design and accuracy in managing micro fluid volumes. The present review thoroughly summarizes the qualitative and quantitative characteristics of the diagnostic assay, enabling the biomarker to be found at the appropriate sensitivity levels with a modest analysis time and cost. The study presents an interdisciplinary perspective on modern diagnostics, which could revolutionize healthcare by enabling precise disease identification and management. © 2023 RSC