Mechanistic Computational Modeling of Implantable, Bioresorbable Drug Release Systems
Mechanistic Computational Modeling of Implantable, Bioresorbable Drug Release Systems
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DOI：
10.1002/adma.202301698
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发表时间：
2023-09-08
影响因子：
29.4
通讯作者：
Kinzer-Ursem，Tamara L.
中科院分区：
文献类型：
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作者：
Giolando，Patrick A.;Hopkins，Kelsey;Kinzer-Ursem，Tamara L.
可植入的、生物可吸收的药物输送系统为目前的药物管理技术提供了一种替代方案；允许患者定制的药物剂量，同时也增加了患者的依从性。机械数学建模允许加速释放系统的设计，并用于预测非直觉的物理异常，否则可能会逃避发现。本研究考察了在数小时至数天内，水介导的聚合物相转化为固体储库的短期药物释放，以及在接下来的几周内，水解介导的长期降解和种植体的侵蚀。有限差分方法用于模拟聚合物相变、凝固和水解的时空变化。模型揭示了不均匀的药物分布、H+离子的产生和运输以及局部聚合物降解对水、药物和水解聚合物副产物扩散的影响。与实验数据相比，计算模型准确地预测了植入物在几天内固化过程中的药物释放情况，以及微球和植入物在几周内的药物释放情况。这项工作为各种参数对药物释放谱的影响提供了新的见解，并且是加速释放系统设计过程以满足患者特定临床需求的新工具。
Implantable, bioresorbable drug delivery systems offer an alternative to current drug administration techniques; allowing for patient‐tailored drug dosage, while also increasing patient compliance. Mechanistic mathematical modeling allows for the acceleration of the design of the release systems, and for prediction of physical anomalies that are not intuitive and may otherwise elude discovery. This study investigates short‐term drug release as a function of water‐mediated polymer phase inversion into a solid depot within hours to days, as well as long‐term hydrolysis‐mediated degradation and erosion of the implant over the next few weeks. Finite difference methods are used to model spatial and temporal changes in polymer phase inversion, solidification, and hydrolysis. Modeling reveals the impact of non‐uniform drug distribution, production and transport of H+ions, and localized polymer degradation on the diffusion of water, drug, and hydrolyzed polymer byproducts. Compared to experimental data, the computational model accurately predicts the drug release during the solidification of implants over days and drug release profiles over weeks from microspheres and implants. This work offers new insight into the impact of various parameters on drug release profiles, and is a new tool to accelerate the design process for release systems to meet a patient specific clinical need.