摘要
目的:优化灯盏花缓释微丸处方工艺。方法:应用人工神经网络映射缓释微丸处方工艺过程变量与因变量之间的关系,并结合粒子群优化法筛选处方工艺参数。结果:依据优化处方工艺参数制备的微丸缓释效果明显,微丸中药物释放属扩散与骨架溶蚀协同作用机制。结论:人工神经网络建模结合粒子群优化法为解决制剂处方工艺涉及的多维复杂非线性系统的优化问题提供了有效的途径。
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.
出处
《中药材》
CAS
CSCD
北大核心
2012年第1期127-133,共7页
Journal of Chinese Medicinal Materials
基金
科技部科技型中小企业技术创新基金(09C26214412134)
关键词
人工神经网络
粒子群优化法
灯盏花
缓释微丸
工艺优化
Artificial neural networks
Particle swarm optimization algorithm
Erigeron breviscapus(Vant.)Hand.Mazz
Sustained-release pellets
Preparation process optimization
