Shera Shailendra Singh, Sahu Shraddha, Banik Rathindra Mohan
Bioprocess Technology Laboratory, School of Biochemical Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, Lanka, Varanasi, Uttar Pradesh 221005 India.
Tissue Eng Regen Med. 2018 Jan 16;15(2):131-143. doi: 10.1007/s13770-017-0100-z. eCollection 2018 Apr.
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. 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.
研究了丝素蛋白/黄原胶复合材料作为一种适用于控释药物的生物医学材料，并通过响应面法（RSM）和人工神经网络（ANN）方法优化了丝素蛋白和黄原胶的混合比例。开发了一个非线性人工神经网络模型，以预测混合比例、复合材料的溶胀百分比和孔隙率对累积释放百分比的影响。将响应面法的效率与人工神经网络进行了评估，发现人工神经网络在复合材料制造的优化和建模研究中表现更好。负载药物氯霉素的释放研究表明，最佳复合支架能够将药物的突释降至最低，并随后进行5天的控释。释放机理研究表明，药物释放过程是扩散控制的。此外，在组织工程应用中，研究掺入的生物活性剂的释放模式有利于预测、控制和监测生长组织的细胞反应。这项工作还对使用各种药物释放模型预测材料性能提出了新的见解。基于模型的拟合优度，发现Korsmeyer-Peppas与实验药物释放曲线吻合良好，这表明所制备的材料具有可溶胀的性质。负载氯霉素（CHL）的支架对革兰氏阳性菌和革兰氏阴性菌显示出更好的疗效。负载CHL的SFX55（50:50）支架显示出在药物递送和组织工程应用方面有前景的生物复合材料。
