СOMPUTER AND MATHEMATICAL MODELING IN BIOTECHNOLOGY AND BIOENGINEERING: AN EDUCATIONAL ASPECT

Abstract

This paper analyzes the importance of mathematical and computer modeling in the training of specialists in the fields of biotechnology and bioengineering. Biotechnological processes require not only fundamental knowledge of chemistry, biology, and physics, but also the ability to apply modern digital tools to monitor and control the course of biochemical reactions. Computer modeling deepens the understanding of core biotechnological processes that underlie the synthesis of target products such as amino acids, enzymes, and antibiotics. The publication presents fundamental mathematical models used to describe these processes. Particular attention in biotechnology is paid to models of microbial population growth and interaction. These models allow for the evaluation of the effectiveness of antibacterial agents, planning of vaccination strategies, and forecasting epidemic spread. Practical examples are given using the Malthusian growth model, Verhulst’s logistic growth model, Gompertz model, Lotka–Volterra model for population interactions, the Monod equation for modeling microbial growth depending on substrate concentration, and the Michaelis – Menten model for enzymatic kinetics. Special focus is placed on the mathematical modeling of product biosynthesis in fermenters – closed bioreactors that are widely used in modern biotechnological production. The implementation of these mathematical models is demonstrated using the Mathcad computer algebra system and the Python programming language. All practical examples are supported by graphical representations of biotechnological processes. An analysis of the modeling results is provided, with conclusions about the applicability of each model to real-world biotechnological systems. The integration of mathematical and computer modeling into the educational process fosters the development of critical thinking, significantly enhances the digital competence of future specialists, and cultivates skills for making informed technological decisions. The synthesis of theoretical knowledge and hands-on modeling tasks confirms the effectiveness of an interdisciplinary approach to biotechnology education.