Design and evaluate a novel enzyme-based biosensor for glucose detection

Thesis Abstract

The increasing prevalence of diabetes mellitus globally underscores the urgent need for accurate, rapid, and cost-effective methods for monitoring blood glucose levels, which remain critical for effective disease management. Conventional glucose measurement techniques, such as enzymatic assays and glucose oxidase-based sensors, often face limitations related to sensitivity, specificity, stability, and operational complexity, prompting ongoing research to develop improved detection systems. This study aims to design, fabricate, and evaluate a novel enzyme-based biosensor that employs immobilized glucose oxidase within a nanostructured electrode matrix to enhance detection accuracy and operational stability. The specific objectives include (1) synthesizing and characterizing a nanostructured electrode conducive to enzyme immobilization; (2) optimizing enzyme immobilization protocols to maximize bioactivity and stability; (3) assessing the electrochemical performance of the biosensor using cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy; (4) determining the sensor's sensitivity, selectivity, reproducibility, and response time; and (5) comparing the biosensor's efficacy with standard glucose detection methods. The methodology employs an experimental research design utilizing purposively sampled electrode materials and a sample size of 50 biosensor prototypes developed under controlled laboratory conditions. The study utilizes analytical techniques such as scanning electron microscopy for morphological characterization, Fourier-transform infrared spectroscopy to verify immobilization chemistry, and electrochemical analysis tools to evaluate sensor performance. The biosensor's calibration curves will be generated through glucose solutions ranging from 1 to 30 mM, with the data subjected to regression analysis to determine sensitivity and detection limits. Variance analysis (ANOVA) will be applied to compare performance metrics across different fabrication parameters, while reproducibility assessments will involve multiple sensor replicates tested under identical conditions. Expected findings include demonstrating that the nanostructured electrode morphology significantly enhances the immobilization efficiency and electron transfer rate of glucose oxidase, resulting in improved sensor sensitivity (anticipated to exceed 15 ?A/mM), a low detection limit (approximately 0.2 mM), and response times within 5 seconds. Furthermore, the biosensor is projected to exhibit high selectivity towards glucose with minimal interference from common interferents such as ascorbic acid and uric acid, and demonstrate acceptable reproducibility with relative standard deviations below 5%. The biosensor's performance will be benchmarked against conventional glucose oxidase-based sensors, highlighting advantages in stability, cost, and ease of fabrication. This research contributes to knowledge by advancing the design of enzyme-based biosensors through the integration of nanostructured electrode platforms, providing a viable pathway for developing portable, sensitive, and reliable glucose monitoring devices suitable for point-of-care applications. The theoretical framework is anchored on the Michaelis-Menten enzyme kinetics and the electrochemical theory of active electrode surfaces, which underpin the sensor's operational principles. The main conclusion indicates that the nanostructured enzyme immobilization strategy successfully enhances biosensor performance, offering a promising alternative to existing glucose detection technologies. The study recommends further exploration into integrating this biosensor with wireless data transmission components for remote health monitoring and suggests subsequent research to evaluate long-term stability and functionality in biological fluids, such as whole blood and interstitial fluid. Overall, this study bridges existing technological gaps, facilitating the development of affordable and accessible diabetes management tools.