集成过和洗建模:优化污染排斥用于过和洗的活性药物成分
Bhavik A Mehta1,2, Ekaterina Gramadnikova1, Cameron J Brown1
1EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, c/o Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K.
概括
一个新的数字工具集成了制药生产的过和洗,通过预测和减少杂质来优化活性药物成分 (API) 隔离,从而提高产品质量.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 制药制造业 制药制造业 制药制造业
- 过程建模过程建模
背景情况:
- 综合制药制造需要无的单元操作,以高效地隔离活性药物成分 (API).
- 当前的工艺往往缺乏可靠的方法来预测和控制过和洗过程中的杂质水平.
- 将上游结晶数据与下游隔离联系起来,对于端到端的过程优化至关重要.
研究的目的:
- 开发一个数字设计工具,用于API隔离的集成过和洗操作.
- 通过传输材料属性信息来预测产品属性和优化净化过程.
- 通过基于机械模型的工作流程来减少隔离蛋糕中的杂质.
主要方法:
- 从上游结晶的预测和实验数据的合.
- 使用一种机械模型,将卡曼-科泽尼过模型与定制的洗模型 (扩散和轴向分散) 结合起来.
- 将模型应用于含有各种溶剂和杂质的美胺酸和胺系统.
主要成果:
- 定制的洗模型准确地模拟了洗曲线的三个阶段 (常速,中速,扩散).
- 模型验证估计了关键蛋糕属性,包括特定的蛋糕阻力,体积和洗后的成分.
- 全球系统分析确定了最佳的设计空间和决定变量,以减少杂质.
结论:
- 开发的数字工具和工作流允许模拟API净化最佳隔离条件.
- 这种方法通过增强过和洗过程,促进了端到端的综合制药制造.
- 该模型提供了在洗过程中物种度演变的详细理解,有助于杂质控制.
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