实时基于组件的颗粒大小测量和溶解预测在连续粉末养过程中使用机器视觉和基于人工智能的物体检测
Áron Kálnai1, Máté Ficzere1, Brigitta Nagy1
1Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rakpart 3, Budapest H-1111, Hungary.
概括
一个新的机器视觉系统准确地测量了制药混合物中的颗粒大小分布. 这种由人工智能驱动的方法可以实时分析和预测药物溶解概况,提高质量控制.
科学领域:
- 制药科学 制药科学
- 图像分析 图像分析
- 人工智能的人工智能
背景情况:
- 精确的颗粒大小分布 (PSD) 对制药产品的性能至关重要.
- 传统的PSD测量方法可能耗时,可能不反映实时制造条件.
研究的目的:
- 开发和验证一种机器视觉系统,用于制药粉末混合物中基于组件的PSD测定.
- 评估系统能够进行实时分析和预测体外药物溶解的能力.
主要方法:
- 利用机器视觉与基于人工智能的图像分析,在连续养过程中捕获和分析粉末图像.
- 基于特定成分的PSD用于乙酸 (ASA) 和酸 (CHP) 混合物.
- 通过显微镜验证结果,并在人口平衡模型中使用ASA PSD来预测溶解.
主要成果:
- 机器视觉系统与基于显微镜的PSD测量结果有很好的相关性.
- 在混合物中的单个组件中实现了PSD的有效实时确定.
- 通过使用测量ASA PSD.成功预测了体外囊溶解概况.
结论:
- 开发的系统提供了一种新的,有效的方法,用于实时PSD分析药物混合物.
- 这项技术可以为制药质量控制和产品开发提供宝贵的见解.
- 这种方法可以根据粉末的特性来更好地预测药物产品的性能.
相关概念视频
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