Parameter Study and Optimization of an Amperometric Biosensor for Pyruvate Determination Using Mathematical Modeling
DOI:
https://doi.org/10.20535/ibb.2025.9.4.347608Keywords:
pyruvate, amperometric biosensor, pyruvate oxidase, reaction-diffusion model, optimizationAbstract
Background. Pyruvate serves as an important diagnostic marker of mitochondrial dysfunctions, lactic acidosis, and certain oncological diseases. Traditional methods for pyruvate analysis have a number of significant limitations: they require complex equipment, are labor-intensive, involve time-consuming sample preparation. Therefore, the development of new, sensitive, and selective methods for determining pyruvate concentration is a highly relevant task.
Objective. The aim of this work was to develop a procedure for the determination and optimization of the parameters of a mathematical model of an amperometric biosensor based on immobilized pyruvate oxidase, employing mathematical modeling of diffusion–reaction processes.
Methods. The biosensor was fabricated using a photopolymer matrix. The analytical characteristics of the biosensor were investigated experimentally. Reaction–diffusion mathematical model was developed to analyze the sensitivity of the biosensor to the substrate (pyruvate) with respect to system parameters. Optimization of these parameters was performed using the gradient descent method.
Results. The study demonstrated that the pyruvate oxidase-based biosensor exhibited a stable amperometric response to pyruvate. Model analysis revealed a significant influence of the substrate diffusion coefficient and the thickness of the bioselective membrane on the biosensor’s sensitivity to pyruvate. The responses of the biosensors showed high signal reproducibility. The theoretically calculated response curves of the biosensor were in good agreement with the experimental data.
Conclusions. The biosensor is characterized by high sensitivity and reproducibility in pyruvate determination. Mathematical modeling enabled rational optimization of the biosensor parameters. The influence of all parameters on the biosensor sensitivity decreased in the following order: from the most influential enzymatic reaction rate constant (k), to the substrate diffusion coefficient (DS), to the membrane thickness (L), whereas the effect of the product diffusion coefficient (DP) was found to be minimal.
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