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在双螺杆挤出过程中模拟无形固体分散的药物降解
1Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, 2409 University Avenue, A1920 Austin, TX 78712, USA.
概括
在双螺杆挤出过程中预测药物降解至关重要. 这项研究模拟了降解动力学和热史,成功预测了78%的准确性,减少了试错方法.
科学领域:
- 制药技术 制药技术 制药技术
- 化学工程是化学工程的重要组成部分.
- 材料科学 材料科学 材料科学
背景情况:
- 双螺杆挤出对于制药固体分散至关重要.
- 在挤出过程中由于热暴露而导致药物降解是一个重大挑战.
- 目前评估药物降解的方法耗时且资源密集.
研究的目的:
- 开发一种用于双螺杆挤出过程中药物降解的预测模型.
- 将药物降解动力学与热史模拟结合起来.
- 为了优化挤出过程,并尽量减少药物降解.
主要方法:
- 建立了一个模型系统,使用利托纳维尔 (RTV) 和可维进行固体分散.
- 在不同温度和时间下研究RTV降解动力学,将数据与第一阶动力学模型相匹配.
- 利用阿雷尼乌斯方程来确定降解速率常数和激活能量.
- 在挤出过程中模拟的热史,使用测量的融温度和停留时间.
- 使用实验设计 (DOE) 来分析挤出条件.
主要成果:
- 确定了水胺氨基醇作为主要的RTV降解剂.
- 在气氛中确定RTV降解动力学反映了挤出路径.
- 确定了降解速率常数,并将它们与阿雷尼乌斯方程相匹配 (Ea = 159.3 kJ/mol,A = 1.23 × 10^17).
- 通过将动力数据与模拟的热史相结合,在预测RTV退化方面实现了78%的回归.
结论:
- 整合药物降解动力学和热史模拟的预测模型可以准确地预测挤出过程中的药物降解.
- 这种方法为传统的试错方法提供了更有效的替代方案.
- 这些发现为优化挤出过程提供了基础,以提高固体分散中的药物稳定性.
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