[Optimize the preparation process of Erigeron breviscapus sustained-release pellets based on artificial neural network and particle swarm optimization algorithm].
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.


CONCLUSIONS
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.
Guangdong Pharmaceutical University, Guangzhou 510006, China. jxzh1998282@163.com
Ji-Xing
JX
Zhang
Yan-Zhong
YZ
Chen
Zhi-Nan
ZN
Wu
Wei-Rong
WR
Liao
D000465:Algorithms; D002626:Chemistry, Pharmaceutical; D003198:Computer Simulation; D003692:Delayed-Action Preparations / Q000737:chemistry; D004365:Drugs, Chinese Herbal / Q000737:chemistry* / Q000302:isolation & purification; D049919:Erigeron / Q000737:chemistry*; D005079:Excipients / Q000737:chemistry; D008863:Microspheres; D008954:Models, Biological; D016571:Neural Networks, Computer; D013678:Technology, Pharmaceutical / Q000379:methods
D003692:Delayed-Action Preparations; D004365:Drugs, Chinese Herbal; D005079:Excipients