چكيده به لاتين
Controlled drug delivery is a key topic in modern pharmacotherapy, where controlled drug delivery devices are required to prolong the period of release, maintain a constant release rate, or release the drug with a predetermined release profile. In the pharmaceutical industry, the development process of a controlled drug delivery device may be facilitated enormously by the mathematical modelling of drug release mechanisms, directly decreasing the number of necessary experiments. Such mathematical modelling is difficult because several mechanisms are involved during the drug release process. The main drug release mechanisms of a controlled release device are based on the device’s physiochemical properties, and include diffusion, swelling and erosion.
The present work is a mathematical modeling and simulation of drug release from a pH-sensitive (poly (NIPAAm-co-AAc) hydrogel system. In this model, the diffusion-mass transfer equations for a spherical, one-dimensional, radial system with moving boundaries are presented. The problem is mutual infiltration and the drug and solvent equations are solved simultaneously in pairs. The main purpose of the present work is to add the predictive ability of drug release at different pHs to the simulation by adding a new term to the drug diffusion coefficient function. After performing simulations on 4 samples from 6 laboratory samples (presented in Chapter 3) and optimizing parameters related to drug release kinetics as well as sensitivity analysis for the parameter selection that has the most impact on the maximum amount of drug release (parameter ), a relation for parameter versus pH is obtained that has been used in the results and validation.
The results of two optimization steps were such that the correlation coefficient R for both inflation and release processes was very close to one. In the swelling section, 30 laboratory points were used to estimate the swelling parameters. In the release kinetics section, 4 of 17 samples were selected from partial release graph data at pHs 2,3,5,12 and validation tests were performed at pHs 4 and 7. The fit of the curve to pH was estimated as a degree 3 polynomial function by MATLAB software that is able to predict the maximum amount of drug release as well as the partial drug release profile in the early times.
