[Optimize the preparation process of Erigeron breviscapus sustained-release pellets based on artificial neural
Ji-Xing Zhang1, Yan-Zhong Chen, Zhi-Nan Wu
1Guangdong Pharmaceutical University, Guangzhou 510006, China. jxzh1998282@163.com
Objective:
To optimize the preparation process of Erigeron breviscapus sustained-release pellets.
Methods:
A mathematical model of relationship between the independent variables and dependent variable of the preparation process of Erigeron breviscapus sustained-release pellets was established by using back-propagation (BP) artificial neural networks (ANN), and the preparation process parameters were optimized with particle swarm optimization (PSO) algorithm.
Results:
The pellets prepared according to the optimized preparation process parameters had significant effect of sustained-releasing. Drug release from the pellets was controlled by both diffusion and matrix corrosion.
Conclusion:
Combining BP ANN modeling with PSO algorithm provides an effective way to solve the multi-dimensional optimization problem of complicated nonlinear systems in pharmaceutical technology.
