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相关概念视频

Typical Model Studies01:30

Typical Model Studies

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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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概率设计空间探索和优化通过贝叶斯的方法用于流体床干燥过程.

Qingbo Meng1, David Bogle1, Vassilis M Charitopoulos1

  • 1Department of Chemical Engineering, Sargent Centre for Process Systems Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
|May 5, 2025
PubMed
概括

本研究引入了贝叶斯方法来定义制药制造的概率设计空间 (DS). 这种方法通过考虑不确定性来提高过程可靠性和产品质量保证.

关键词:
人工神经网络的人工神经网络贝叶斯的方法是贝叶斯的方法.连续制药制造业 连续制药制造业液体床干燥机 液体床干燥机可能设计空间空间的概率设计.

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科学领域:

  • 制药制造业 制药制造业 制药制造业
  • 工艺工程是过程工程.
  • 贝叶斯统计学贝叶斯统计学

背景情况:

  • 国际协调会议 (ICH) Q8引入了设计空间 (DS) 作为制药开发的框架,以确保产品质量.
  • 由于制药生产过程的复杂性和不确定性,探索可靠和强大的DS具有挑战性.

研究的目的:

  • 调查流体床干燥过程的概率设计空间 (DS).
  • 用贝叶斯方法解释过程可操作性和性能可靠性.
  • 确定一个概率DS,以保证产品质量在所需的可靠性水平,考虑到材料和工艺的不确定性.

主要方法:

  • 开发一个贝叶斯模型,整合一个基于代理的预测模型,并对物质可变性的不确定性量化.
  • 使用网格搜索技术对操作变量域进行分离,以探索概率DS.
  • 应用优化技术来最大限度地利用DS区域并提高操作性.

主要成果:

  • 贝叶斯的方法有效地确定了一个概率设计空间 (DS).
  • 该方法可确保产品质量达到所需的可靠性水平.
  • 它成功地解释了流体床干燥中的材料和工艺不确定性.

结论:

  • 贝叶斯方法是药品制造中定义概率设计空间 (DS) 的强大工具.
  • 这种方法提高了制药过程的可靠性和稳定性.
  • 它为在不确定性条件下保证产品质量提供了一个框架.