Research Article | DOI: https://doi.org/BRCA-25-RA-23
Analysis and Control of a Drug Delivery Model
Abstract
Many chronic diseases require continuous treatment, and the interaction between drug exposure and pharmacological response is very complex and nonlinear. It is important to understand the nonlinear complexity and use this nonlinearity effectively to obtain the best advantage. Several factors must be considered, and multiple objectives must be achieved simultaneously. Bifurcation analysis and multi-objective nonlinear model predictive control (MNLMPC) calculations are performed on a dynamic model involving drug delivery. The MATLAB program MATCONT was used to perform the bifurcation analysis. The MNLMPC calculations were carried out using the optimization language PYOMO in conjunction with the advanced global optimization solvers IPOPT and BARON. The bifurcation analysis revealed the existence of a branch point in the system. These branch point (which causes multiple steady-state solutions from a single point) is beneficial because it enables the multi-objective nonlinear model predictive control calculations to converge to the Utopia point, which is the best possible solution. It has been demonstrated (with computational validation) that the branch point results from the presence of two distinct separable functions in one of the equations of the dynamic model. A theorem was developed to prove this fact for any dynamic model..
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