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基于分子性质的配方指南树,用于稀溶性化合物的无形和超和半孔二氧化制剂
Dipy M Vasa1, Shih-Wen Wang1, Matthew F Dunn2
1Drug Product Design, Pfizer, Inc., Cambridge, MA, United States.
Journal of pharmaceutical sciences
|October 31, 2024
概括
配方科学家现在可以快速选新的药物化合物,使用一种新的无形API和HPMCAS-L共同装载的中等二氧化平台. 这种方法提高了溶解度,降低了沉风险,简化了药物发现工作.
科学领域:
- 制药科学 制药科学
- 材料科学 材料科学 材料科学
- 药物运输 药物运输 药物运输
背景情况:
- 许多新化学实体 (NCE) 具有较差的水溶性,阻碍了药物发现.
- 在时间和物质限制下制定有效的可溶性增强策略至关重要.
- 需要制定战略平台,以便快速选NCE进行早期研究.
研究的目的:
- 为提高溶解度提供一种节约材料,高产的配方平台.
- 评估这个平台对各种物理化学化合物的可用性.
- 为预测无形配方稳定性和超和提供一个指导树.
主要方法:
- 开发一种无形的API和HPMCAS-L联合加载的半孔二氧化配方.
- 评估使用11种不同化合物的配方策略.
- 利用计算和实验数据为基于分子属性的指导树.
主要成果:
- 该配方成功地稳定了半孔中的无形活性药物成分 (API).
- 基基甲基纤维素酸-L (HPMCAS-L) 在超和条件下显著降低了降水风险.
- 开发了一个指导树,以预测无形配方的稳定性和体外超和.
结论:
- 基于半孔的平台为具有挑战性的NCE的可溶性增强提供了可行的解决方案.
- 包括HPMCAS-L是有效的缓解药物沉.
- 开发的指导树有助于先验配方设计和药物发现配方器的NCE分类.
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