限制
药物输送
自愈水凝胶
统计力学
计算机科学
数学模型
生化工程
统计物理学
纳米技术
数学
材料科学
工程类
物理
统计
机械工程
化学工程
标识
DOI:10.1016/j.ijpharm.2019.01.076
摘要
Hydrogels-based systems (HBSs) for drug delivery are nowadays extensively used and the interest in modeling their behavior is dramatically increasing. In this review a critical overview on the modeling approaches is given, quantitatively and qualitatively analyzing the publications on the subject, the trend of the publications per year and the type of modeling approaches. It was found that, despite the drug release fitting models (i.e. Higuchi’s equation) are the most abundant, their use for HBSs is decreasing in the last years and luckily, considering the limiting assumption on which they were built, they will be confined to simple mathematical fitting equations. Within the mechanistic models the “multi-component” with the swelling approximation (mass transport only) and with the mechanics (fully coupled) are experiencing the highest growth rate, with much more interest toward the last one that, in the next years could be able to provide a first principles model. Statistical models, especially based on the response surface methodology, are rapidly spreading in the scientific community mainly thanks to their ability to be predictive, regardless of the phenomenology, in the analyzed design space with very low efforts. Neural Networks models for HBSs, in countertrend with their use in the pharmaceutical industry, have never take off preferring less data demanding statistical models.
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