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首页> 外文期刊>Journal of Microencapsulation: Microcapsules Liposomes Nanoparticles Microcells Microspheres >Preparation of biodegradable nanoparticles of tri-block PLA-PEG-PLA copolymer and determination of factors controlling the particle size using artificial neural network
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Preparation of biodegradable nanoparticles of tri-block PLA-PEG-PLA copolymer and determination of factors controlling the particle size using artificial neural network

机译：三嵌段PLA-PEG-PLA共聚物可生物降解的纳米粒子的制备及控制粒径的人工神经网络确定

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摘要

The purpose of this study was to prepare nanoparticles made of tri-block poly(lactide)-poly(ethylene glycol)-poly (lactide) (PLA-PEG-PLA) with controlled size as drug carrier. Artificial neural networks (ANNs) were used to identify factors which influence particle size. In this way, PLA-PEG-PLA was synthesized and was made into nanoparticles by nanoprecipitation under different conditions. The copolymer and the resulting nanoparticles were characterized by various techniques such as proton nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, gel permeation chromatography, photon correlation spectroscopy and scanning electron microscopy. The developed model was assessed and found to be of high quality. The model was then used to survey the effects of processing factors including polymer concentration, amount of drug, solvent ratio and mixing rate on particle size of polymeric nanoparticles. It was observed that polymer concentration is the most affecting parameter on nano-particle size distribution. The results demonstrate the potential of ANNs in modelling and identification of critical parameters effective on final particle size.
机译：这项研究的目的是制备由三嵌段聚（丙交酯）-聚（乙二醇）-聚（丙交酯）（PLA-PEG-PLA）制成的纳米颗粒，其具有可控制的大小作为药物载体。人工神经网络（ANN）用于识别影响粒径的因素。以这种方式，合成了PLA-PEG-PLA，并在不同条件下通过纳米沉淀将其制成纳米颗粒。通过各种技术，例如质子核磁共振光谱，傅立叶变换红外光谱，凝胶渗透色谱，光子相关光谱和扫描电子显微镜，对共聚物和所得的纳米颗粒进行表征。对开发的模型进行了评估，发现它是高质量的。然后使用该模型调查加工因素的影响，包括聚合物浓度，药物量，溶剂比和混合速率对聚合物纳米粒子粒径的影响。观察到聚合物浓度是对纳米粒度分布影响最大的参数。结果证明了人工神经网络在建模和识别对最终粒径有效的关键参数方面的潜力。

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