基于机器视觉的非破坏性溶解预测含有梅洛西卡姆的片剂的溶解
Lilla Alexandra Mészáros1, Lajos Madarász1, Szabina Kádár1
1Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary.
International journal of pharmaceutics
|March 19, 2024
概括
这项研究开发了一种UV/VIS成像系统,以非破坏性地预测药片溶解. 机器视觉方法准确预测溶解概况和API含量,支持制药质量控制.
科学领域:
- 制药技术 制药技术 制药技术
- 分析化学 分析化学
- 图像分析 图像分析
背景情况:
- 机器视觉系统对于药物固体剂型质量评估至关重要.
- 这些系统支持连续制造,工艺分析技术 (PAT),质量设计 (QbD) 和实时释放测试 (RTRT).
研究的目的:
- 开发一个数字紫外线/VIS成像系统,用于预测梅洛西卡姆片的体外溶解.
- 使用UV/VIS图像的多变量分析,非破坏性地预测影响溶解的关键过程参数.
主要方法:
- 使用紫外线/VIS成像来捕获平板电脑数据.
- 应用多变量分析和人工神经网络 (ANN) 用于溶解概况预测.
- 采用基于UV/VIS图像颜色组件的部分最小平方 (PLS) 模型来预测API内容.
主要成果:
- 在溶解配置点的预测误差 (RMSE) 低于5%.
- 预测的API含量的变化,相对误差小于10%.
- 证明API含量直接影响溶解过程中观察到的最大度.
结论:
- 介绍了一种新的,非破坏性的PAT解决方案,用于实时测试平板电脑溶解.
- 强调UV/VIS成像和机器学习在药品质量保证方面的潜力.
- 允许在平板电脑制造中增强过程理解和控制.
相关概念视频
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