[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.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.