一个用于自乳化药物输送系统的配方成分数据集
Jonathan Zaslavsky1, Christine Allen2,3,4
1Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2, Canada.
Scientific data
|December 20, 2023
概括
这项研究创建了自乳化药物输送系统 (SEDDS) 的综合数据集,以推进数据驱动的配方开发. 精选的数据旨在简化为溶解不良药物创建有效的SEDDS的过程.
科学领域:
- 制药科学 制药科学
- 药物运输 药物运输 药物运输
- 配方科学科学 配方科学
背景情况:
- 自乳化药物输送系统 (SEDDS) 提高了水溶性较差的药物的口服生物可用性.
- 传统的SEDDS开发依赖于经验方法来实现兼容性和优化.
- 在SEDDS的制定中存在数据驱动方法的需求.
研究的目的:
- 从现有文献中构建一个全面的SEDDS数据集.
- 为了实现数据驱动的洞察力和提前的配方开发.
- 为了简化SEDDS的制定过程.
主要方法:
- 策划了668种独特的SEDDS配方的数据集.
- 包括20种水溶性较差的药物的配方.
- 利用此前发布的SEDDS数据.
主要成果:
- 建立了一个大量的SEDDS数据集.
- 数据集包括各种配方和药物.
- 确定了数据增强的机会.
结论:
- 精心策划的数据集为数据驱动的SEDDS开发提供了基础.
- 这项工作为简化配方策略铺平了道路.
- 进一步收集数据可以提高数据集的实用性.
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