Predicting Dissolution Kinetics for Active Pharmaceutical Ingredients on the Basis of Their Molecular Structures
Predicting Dissolution Kinetics for Active Pharmaceutical Ingredients on the Basis of Their Molecular Structures
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DOI：
10.1021/acs.cgd.6b00721
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发表时间：
2016-07-01
影响因子：
3.8
通讯作者：
Briesen, Heiko
中科院分区：
文献类型：
--
作者：
Elts, Ekaterina;Greiner, Maximilian;Briesen, Heiko
在这项工作中，提出了仅根据其相应的分子结构预测活性药物成分的绝对晶体溶出速率的可能性。为此，分子动力学（MD）和动力学蒙特卡罗（kMC）方法的组合使用。溶解过程首先在MD框架内进行了研究。因此，证明了应用三维晶体表示的益处。MD模拟用于参数化kMC模拟。提出了一种简单而通用的方法来定义马尔可夫状态和计算速率常数的kMC模拟。给定一组状态和速率常数，kMC方法提供了一个随机过程来产生一个状态到状态的轨迹，代表一个有效的实现状态到状态的动态，而在同一时间显着扩展的范围内的长度和时间尺度可访问的模拟。结合MD和kMC模拟的结果，阿司匹林晶体的溶解。与实验数据的比较表明了该方法的成功。
In this work, the possibility of predicting absolute crystal dissolution rates for active pharmaceutical ingredients on the basis of only their corresponding molecular structures is presented. Toward this end, a combination of molecular dynamics (MD) and kinetic Monte Carlo (kMC) approaches is used. The dissolution processes are first investigated within a MD framework. Thereby, the benefit of applying a three-dimensional crystal representation is demonstrated. MD simulations are used to parametrize kMC simulations. A simple and universal way to define Markovian states and calculate rate constants for kMC simulations is proposed. Given the set of states and rate constants, a kMC approach provides a stochastic procedure to produce a state-to-state trajectory, representing a valid realization of the state-to-state dynamics, while at the same time significantly extending the range of length and time scales accessible to simulation. The results of combined MD and kMC simulations are presented for the dissolution of an aspirin crystal. A comparison with experimental data demonstrates the success of the approach.