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通过混合剂量模型预测药剂量转换在药品粉末中
Zijian Wang1, Changquan Calvin Sun1
1Pharmaceutical Materials Science and Engineering Laboratory, Department of Pharmaceutics, College of Pharmacy, University of Minnesota, MN 55455, USA.
International journal of pharmaceutics
|November 4, 2025
概括
一个新的模型准确地预测了可平板翻转现象 (TFP),其中较少固有的可平板的活性药物成分 (API) 与辅助剂的性能更好. 这有助于早期的药片配方开发和固体形式的选择.
科学领域:
- 制药科学 制药科学
- 材料科学 材料科学 材料科学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 药剂性翻转现象 (TFP) 复杂化了活性药物成分 (API) 固体形式的选择和配方.
- 现有的研究提供了洞察力,但缺乏用于早期药片配方开发的预测工具.
- 预测TFP的可靠方法对于在制药制造中实施设计质量 (QbD) 原则至关重要.
研究的目的:
- 评估新型混合物可表化模型对可表化翻转现象 (TFP) 的预测能力.
- 评估该模型作为早期药片配方开发中的诊断工具的可行性.
- 根据实验数据,确定模型改进的领域.
主要方法:
- 采用了最近开发的混合物可表化模型.
- 该模型的预测在两个不同的API助剂系统中进行了测试.
- 模型预测与实验表化数据进行了比较.
主要成果:
- 混合剂型模型成功预测了两种测试系统中TFP的存在或不存在.
- 该模型展示了在配方开发过程中识别TFP的诊断工具的潜力.
- 预测和实验结果之间的偏差表明粒子大小对模型准确性的影响.
结论:
- 开发的混合物可表化模型显示了预测TFP的前景,有助于固体形式的选择和配方设计.
- 通过进一步研究粒子大小特征的影响,可以提高模型的准确性.
- 这种预测方法支持QbD在平板电脑开发中的实施,通过早期识别潜在的配方挑战.
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