Optimized parameters for the preparation of silk fibroin drug‐loaded microspheres based on the response surface method and a genetic algorithm–backpropagation neural network model

Using silk fibroin as the base material, the drug‐loaded microspheres are prepared by an emulsification method. In order to determine the drug‐loading and drug‐release performance parameters of the microspheres, the central composite design method is used to design and investigate the effects of the...

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Bibliographic Details
Published in:	Journal of biomedical materials research. Part B, Applied biomaterials Vol. 109; no. 1; pp. 6 - 18
Main Authors:	Zhang, Xujing, Zhou, Jianping, Xu, Yan
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01.01.2021 Wiley Subscription Services, Inc
Subjects:	Algorithms Back propagation Back propagation networks Biomedical materials BP–GA neural network model central composite design method Drug Carriers - chemistry Drug Compounding Drug delivery systems Drug development Drug Liberation drug‐loaded microspheres Emulsification Fibroins - chemistry Genetic algorithms In Vitro Techniques Isoniazid - chemistry Isoniazid - pharmacology Load distribution Loading rate Materials research Materials science Mathematical models Microspheres Model accuracy Models, Chemical Neural networks Neural Networks, Computer Optimization Parameters Particle Size response surface method Response surface methodology Silk Silk fibroin Stirring Temperature response surface method central composite design method drug-loaded microspheres BP-GA neural network model silk fibroin
ISSN:	1552-4973, 1552-4981, 1552-4981
Online Access:	Get full text
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