مدل‌سازي و بهينه‌سازي استراتژي دوزدهي دارو با هدف بيشينه‌سازي اثربخشي درمان و كمينه‌سازي عوارض جانبي در درمان تومور مغزي

In the contemporary world, the effective identification an‎d treatment of brain tumors represent one of the most critical challenges in medical science an‎d biomedical engineering. Owing to the structural complexity of the brain, tissue heterogeneity, an‎d biological viability constraints, the development of predictive an‎d optimization based models for drug behavior within tumoral tissues has gained increasing importance. The principal objective of this research is to propose an accurate numerical framework for modeling tumor growth an‎d optimizing drug administration based on the Phase Field Method. The proposed model is capable of simultaneously simulating the kinematic an‎d dynamic behavior of therapeutic agents within a complex biological environment an‎d serves as a computational tool for recommending personalized treatment protocols. In this study, tumor growth was first modeled in a two dimensional domain using the Allen-Cahn an‎d Cahn-Hilliard phase field equations. Subsequently, drug transport was formulated through a reaction-diffusion-degradation equation, an‎d the effects of key parameters such as the diffusion coefficient, uptake rate, an‎d tissue structure were thoroughly investigated. To determine the optimal injection pattern in terms of location, timing, an‎d dosage, the Particle Swarm Optimization (PSO) algorithm was employed. Moreover, the Taguchi design of experiments was utilized to tune the PSO parameters, thereby enhancing the robustness an‎d stability of the optimization process. All simulations were implemented in the MATLAB environment, an‎d the results were analyzed both numerically an‎d graphically. The simulation outcomes revealed that adaptive an‎d multi site dosing strategies constitute the most effective approaches for achieving uniform reduction of the phase field variable an‎d preventing tumor regrowth. PSO based optimization successfully selec‎ted injection sites within semi active boundary regions, leading to improved drug penetration an‎d minimization of total drug consumption. Furthermore, the optimized decreasing dosage profile over time followed the clinical paradigm of “strong initial attack an‎d maintenance control.” The developed numerical model not only demonstrated high accuracy in capturing the complex dynamics of tumor progression an‎d drug transport, but also exhibited strong potential for designing personalized therapeutic protocols for future clinical applications.

احمدرضا پيشه وراصفهاني

مهدي نيلي احمدآبادي , مجيد رضائي