代优化技术的开发:使用小规模的料框架模拟器选择纯组件光谱
Samuel Henson1, Adam J Rish1, Md Anik Alam2
1Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, USA.
International journal of pharmaceutics
|April 4, 2024
概括
代优化技术 (IOT) 为在制药制造中使用近红外 (NIR) 频谱预测API功效提供了较低的校准负担. 这项研究通过确保纯成分光谱条件代表混合物光谱来证明准确的预测.
科学领域:
- 制药制造业 制药制造业 制药制造业
- 光谱过程分析技术 (PAT)
- 化学测量 化学测量 化学测量
背景情况:
- 光谱PAT可在制药生产中进行线上数据收集.
- 部分最小平方 (PLS) 模型用于从PAT数据中预测API功率是常见的,但其校准负担很高.
- 纯组件方法,如代优化技术 (IOT),可以减少校准负担.
研究的目的:
- 为了解决IOT算法的假设,关于PAT应用的光谱收集条件.
- 为了评估IOT在预测API功效中的有效性,从线式NIR频谱中进行预测.
- 通过仔细选择纯成分光谱集来优化IOT模型性能.
主要方法:
- 利用代优化技术 (IOT) 来从近红外线 (NIR) 光谱中预测API功率.
- 采用了停滞和动态纯成分光谱的组合.
- 使用了一组混合样本的开发集来指导代表性纯成分光谱集的选择.
- 使用开发和测试集的指标评估模型性能.
主要成果:
- 通过将IOT与用于光谱选择的开发集相结合,可以实现准确的API功效预测.
- 通过开发集上的模型性能指标确定了最佳的纯成分光谱集.
- 该研究表明,纯成分光谱收集条件需要代表混合光谱,不一定是相同的.
结论:
- 物联网和开发集的结合有效地预测了制药制造中的API功效.
- 关于光谱收集条件的IOT假设应该被视为代表性要求,而不是严格协调.
- 这种方法增强了IOT在具有挑战性的制药制造环境中的应用.
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