Preparation of Drug Eluting Natural Composite Scaffold Using Response Surface Methodology and Artificial Neural Network Approach

利用响应面法和人工神经网络方法制备载药天然复合支架

阅读:1

Abstract

Silk fibroin/xanthan composite was investigated as a suitable biomedical material for controlled drug delivery, and blending ratios of silk fibroin and xanthan were optimized by response surface methodology (RSM) and artificial neural network (ANN) approach. A non-linear ANN model was developed to predict the effect of blending ratios, percentage swelling and porosity of composite material on cumulative percentage release. The efficiency of RSM was assessed against ANN and it was found that ANN is better in optimizing and modeling studies for the fabrication of the composite material. In-vitro release studies of the loaded drug chloramphenicol showed that the optimum composite scaffold was able to minimize burst release of drug and was followed by controlled release for 5 days. Mechanistic study of release revealed that the drug release process is diffusion controlled. Moreover, during tissue engineering application, investigation of release pattern of incorporated bioactive agent is beneficial to predict, control and monitor cellular response of growing tissues. This work also presented a novel insight into usage of various drug release model to predict material properties. Based on the goodness of fit of the model, Korsmeyer-Peppas was found to agree well with experimental drug release profile, which indicated that the fabricated material has swellable nature. The chloramphenicol (CHL) loaded scaffold showed better efficacy against gram positive and gram negative bacteria. CHL loaded SFX55 (50:50) scaffold shows promising biocomposite for drug delivery and tissue engineering applications.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。