论文标题

pH响应性纳米核心剂的药物输送的数学建模

Mathematical modelling of drug delivery from pH-responsive nanocontainers

论文作者

Pontrelli, G., Toniolo, G., McGinty, S., Peri, D., Succi, S., Chatgilialoglu, C.

论文摘要

药物输送系统是治疗癌症和克服化学疗法副作用的有前途的策略。特别是,聚合物纳米结构剂引起了主要的兴趣,因为它们具有结构和形态学的优势以及可以使用的各种聚合物,从而允许合成能够响应肿瘤微环境生化变化的材料。尽管实验方法可以提供很多见识,但在广泛的参数空间中的实验数据通常非常耗时和/或昂贵。为了更好地了解不同设计参数对涉及药物释放概况和药物动力学的影响,适当设计的数学模型具有很大的好处。在这里,我们开发了一种新型的数学模型,以描述由核心和pH响应性聚合物壳组成的空心纳米核心内部的药物传输。两层数学模型充分说明了药物溶解,扩散和与聚合物的相互作用。我们使用daunorubicin和[Cu(TPMA)(苯烷)](Clo_4)_2作为模型药物生成了实验性药物释放谱,为此,纳米结构剂具有出色的封装能力。在不同的条件下研究了体外药物释放行为,该系统被证明能够通过在酸性中释放大量药物来对所选的pH刺激做出反应,而不是在生理环境中。通过将数学模型的结果与我们的实验数据进行比较,我们能够确定最适合数据的模型参数值并证明该模型能够描述手头现象。所提出的方法可用于描述和预测各种药物输送系统的释放曲线。

Drug delivery systems represent a promising strategy to treat cancer and to overcome the side effects of chemotherapy. In particular, polymeric nanocontainers have attracted major interest because of their structural and morphological advantages and the variety of polymers that can be used, allowing the synthesis of materials capable of responding to the biochemical alterations of the tumour microenvironment. While experimental methodologies can provide much insight, the generation of experimental data across a wide parameter space is usually prohibitively time consuming and/or expensive. To better understand the influence of varying design parameters on the drug release profile and drug kinetics involved, appropriately-designed mathematical models are of great benefit. Here, we developed a novel mathematical model to describe drug transport within, and release from, a hollow nanocontainer consisting of a core and a pH-responsive polymeric shell. The two-layer mathematical model fully accounts for drug dissolution, diffusion and interaction with polymer. We generated experimental drug release profiles using daunorubicin and [Cu(TPMA)(Phenantroline)](ClO_4)_2 as model drugs, for which the nanocontainers exhibited excellent encapsulation ability. The in vitro drug release behaviour was studied under different conditions, where the system proved capable of responding to the selected pH stimuli by releasing a larger amount of drug in an acidic than in the physiological environments. By comparing the results of the mathematical model with our experimental data, we were able to identify the model parameter values that best-fit the data and demonstrate that the model is capable of describing the phenomena at hand. The proposed methodology can be used to describe and predict the release profiles for a variety of drug delivery systems.

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