Novel Core-Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools.

IF 4.9 3区 工程技术 Q1 POLYMER SCIENCE
Polymers Pub Date : 2025-07-11 DOI:10.3390/polym17141919
Carlos Illanes-Bordomás, Mariana Landin, Carlos A García-González
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引用次数: 0

Abstract

This study explores novel alginate-konjac glucomannan core-shell aerogel particles for drug delivery systems fabricated via air-assisted coaxial prilling. A systematic approach is needed for the optimization of this method due to the numerous processing variables involved. This study investigated the influence of six variables: alginate and konjac glucomannan concentrations, compressed airflow, liquid pump pressures, and nozzle configuration. A hybrid software using Artificial Neural Networks and genetic algorithms was used to model and optimize the hydrogel formation, achieving a 100% desirable solution. The optimal formulation identified resulted in particles displaying a log-normal size distribution (R2 = 0.967) with an average diameter of 1.57 mm. Supercritical CO2 drying yielded aerogels with macropores and mesopores and a high specific surface area (201 ± 10 m2/g). The loading of vancomycin hydrochloride (Van) or a dexamethasone base (DX) into the aerogel cores during the process was tested. The aerogels exhibited appropriate structural characteristics, and both drugs showed burst release profiles with ca. 80% release within 10 min for DX and medium-dependent release for Van. This study demonstrates the feasibility of producing konjac aerogel particles for delivery systems and the high potential of AI-driven optimization methods, highlighting the need for coating modifications to achieve the desired release profiles.

基于海藻酸盐和魔芋葡甘露聚糖的新型核壳给药气凝胶配方:利用人工智能工具进行合理设计。
本研究探索了一种新的海藻酸盐-魔芋葡甘露聚糖核壳气凝胶颗粒,通过空气辅助同轴造粒制备药物输送系统。由于涉及的加工变量众多,需要系统的方法对该方法进行优化。本研究考察了六个变量:海藻酸盐和魔芋葡甘露聚糖浓度、压缩气流、液体泵压力和喷嘴配置的影响。使用人工神经网络和遗传算法的混合软件对水凝胶地层进行建模和优化,获得了100%理想的解决方案。经优化后,颗粒粒径呈对数正态分布(R2 = 0.967),平均粒径为1.57 mm。超临界CO2干燥制得的气凝胶具有大孔和中孔,具有较高的比表面积(201±10 m2/g)。在此过程中,测试了盐酸万古霉素(Van)或地塞米松碱(DX)在气凝胶芯中的负载情况。两种药物均表现出爆发释放特征,DX在10 min内释放约80%,Van在10 min内释放中等依赖。这项研究证明了生产用于递送系统的魔芋气凝胶颗粒的可行性,以及人工智能驱动的优化方法的巨大潜力,强调了涂层修改的必要性,以实现所需的释放曲线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Polymers
Polymers POLYMER SCIENCE-
CiteScore
8.00
自引率
16.00%
发文量
4697
审稿时长
1.3 months
期刊介绍: Polymers (ISSN 2073-4360) is an international, open access journal of polymer science. It publishes research papers, short communications and review papers. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Polymers provides an interdisciplinary forum for publishing papers which advance the fields of (i) polymerization methods, (ii) theory, simulation, and modeling, (iii) understanding of new physical phenomena, (iv) advances in characterization techniques, and (v) harnessing of self-assembly and biological strategies for producing complex multifunctional structures.
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