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Mathematical Modeling for Pharmaco-Kinetic and -Dynamic Predictions from Controlled Drug Release NanoSystems: A Comparative Parametric Study

机译:控制药物释放纳米系统的药代动力学和动态预测的数学模型:比较参数研究

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摘要

Predicting pharmacokinetics, based on the theory of dynamic systems, for an administered drug (whether intravenously, orally, intramuscularly, etc.), is an industrial and clinical challenge. Often, mathematical modeling of pharmacokinetics is preformed using only a measured concentration time profile of a drug administered in plasma and/or in blood. Yet, in dynamic systems, mathematical modeling (linear) uses both a mathematically described drug administration and a mathematically described body response to the administered drug. In the present work, we compare several mathematical models well known in the literature for simulating controlled drug release kinetics using available experimental data sets obtained in real systems with different drugs and nanosized carriers. We employed the χ2 minimization method and concluded that the Korsmeyer–Peppas model (or power-law model) provides the best fit, in all cases (the minimum value of χ2 per degree of freedom; χmin2/d.o.f. = 1.4183, with 2 free parameters or m = 2). Hence, (i) better understanding of the exact mass transport mechanisms involved in drugs release and (ii) quantitative prediction of drugs release can be computed and simulated. We anticipate that this work will help devise optimal pharmacokinetic and dynamic release systems, with measured variable properties, at nanoscale, characterized to target specific diseases and conditions.
机译:基于动力系统理论来预测所施用药物(无论是静脉内,口服,肌肉内等)的药代动力学是一项工业和临床挑战。通常,仅使用在血浆和/或血液中施用的药物的测量的浓度时间曲线来进行药代动力学的数学建模。然而,在动态系统中,数学建模(线性)既使用数学上描述的药物给药,也使用数学上描述的对给药药物的身体反应。在目前的工作中,我们使用在不同药物和纳米载体的真实系统中获得的可用实验数据集,比较了一些文献中用于模拟受控药物释放动力学的数学模型。我们采用χ 2 最小化方法得出的结论是,在所有情况下(χ 2 每个自由度;χmin 2 / dof = 1.4183,带有2个自由参数或m = 2)。因此,可以计算和模拟(i)更好地了解药物释放所涉及的确切质量传输机制,以及(ii)药物释放的定量预测。我们预计这项工作将有助于设计最佳的药代动力学和动态释放系统,该系统具有可测量的可变性质,在纳米范围内具有针对特定疾病和条件的特征。

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