Abstract
Background/Objectives: Advancements in personalized medicine have revolutionized drug delivery, enabling tailored treatments based on genetic and molecular profiles. Non-viral vectors, such as polyurethane (PU)-based systems, offer promising alternatives for gene therapy. This study develops mathematical models to analyze PU degradation, DNA/RNA release kinetics, and cellular interactions, optimizing their application in personalized therapy. Methods: This theoretical study utilized mathematical modeling and numerical simulations to analyze PU-based gene delivery, focusing on diffusion, degradation, and cellular uptake. Implemented in Python 3.9, it employed differential equation solvers and adsorption/internalization models to predict vector behavior and optimize delivery efficiency. Results: This study demonstrated that PU degrades in biological environments following first-order kinetics, ensuring a controlled and predictable release of genetic material. The Higuchi diffusion model confirmed a gradual, sustained DNA/RNA release, essential for efficient gene delivery. Simulations of PU adsorption onto cellular membranes using the Langmuir model showed saturation-dependent binding, while the endocytosis model revealed a balance between uptake and degradation. These findings highlight PU’s potential as a versatile gene delivery vector, offering controlled biodegradability, optimized release profiles, and effective cellular interaction. Conclusions: Our results confirm that PU-based vectors enable controlled biodegradability, sustained DNA/RNA release, and efficient cellular uptake. Mathematical modeling provides a framework for improving PU’s properties, enhancing transport efficiency and therapeutic potential in personalized medicine and gene therapy applications.