使用Pyomo和PharmaPy进行药品工艺数字设计的模拟优化框架
Daniel Laky1, Daniel Casas-Orozco1, Carl D Laird2
1Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47906, USA.
Industrial & engineering chemistry research
|January 5, 2024
概括
这项研究引入了制药工艺设计和优化的新框架. 它通过在优化中直接使用过程模拟器来实现更快,更准确的解决方案,从而简化了复杂模型的实现.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 工艺系统工程 工艺系统工程
- 制药制造业 制药制造业 制药制造业
背景情况:
- 制药行业的基于模型的流程设计和优化在计算和实施方面面临着重大挑战.
- 现有的优化框架通常需要在将机械模型 (ODEs和PDEs) 翻译成离散的代数公式方面拥有广泛的专业知识.
- 这种复杂性阻碍了药品制造的高效和准确的流程优化.
研究的目的:
- 介绍一种新的框架,用于在基于衍生品的优化中直接使用过程模拟器.
- 为了使具有有限经验的用户能够执行强大的流程优化.
- 为了实现具有竞争力的计算效率的数学保证的最佳.
主要方法:
- 开发了一个框架,允许在基于衍生品的优化过程中通过回调直接使用过程模拟器.
- 该框架绕过了机械常规微分方程 (ODE) 和部分微分方程 (PDE) 的手动翻译成代数公式的需求.
- 实施了以方程为导向的同时优化技术.
主要成果:
- 该框架成功地获得了数学上保证的最佳解决方案.
- 与现有的无衍生品和基于衍生品的优化框架相比,证明了具有竞争力的计算效率.
- 在两个制药过程案例研究中验证了准确性和效率:一种抗癌API合成列车和一种合成-净化-隔离列车.
结论:
- 提出的框架简化了对制药过程的基于模型的优化实施.
- 它提供了一种计算效率高,准确的方法来找到最佳解决方案.
- 该框架使具有较少专业化建模经验的用户能够实现强大的流程设计和优化.
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