智能配方:使用KNIME优化和稳定性预测的人工智能驱动的网络平台
Artur Grigoryan1, Stefan Helfrich2, Valentin Lequeux1
1Fripharm®, Pharmacy Department, Groupe Hospitalier Centre Edouard Herriot, Hospices Civils de Lyon, 5, Place d'Arsonval, F-69437 Lyon, France.
Pharmaceuticals (Basel, Switzerland)
|August 28, 2025
概括
智能配方,一个人工智能平台,预测复合药物的超出使用日期. 它帮助药剂师通过考虑分子,配方和环境因素来优化药物的稳定性,从而改善患者的护理.
科学领域:
- 计算机制药
- 药物制剂中的人工智能
- 药物稳定性的预测建模
背景情况:
- 复合口服固体剂型需要准确的超出使用日期 (BUD).
- 目前用于确定BUD的方法可能耗时且昂贵.
- 优化即时制剂的稳定性对于患者的安全至关重要.
研究的目的:
- 开发一个基于人工智能的决策支持工具,智能配方,用于预测BUD.
- 整合分子,配方和环境参数进行稳定性预测.
- 帮助药剂师优化复合药物的稳定性
主要方法:
- 在55个实验BUD值上训练了一种树集回归模型.
- 配方被编码为分子描述符,辅助剂成分,包装和储存条件.
- 该模型使用KNIME化学信息学和机器学习集成平台实现.
主要成果:
- 辅助剂的类型,数量和环境条件显著影响API的稳定性.
- 较低的LogP值和单独的辅助物质 (例如纤维素,二氧化,糖,曼尼醇) 与更高的稳定性相关.
- 使用两种辅助剂往往会减少BUDs.
结论:
- 智能配方为制药提供了有价值的计算工具,将配方设计与配方需求联系起来.
- 该平台为传统的稳定性测试提供了一个可扩展,具有成本效益的替代方案.
- 实施可以缓解药物短缺,标准化配方,并提高患者护理.
相关概念视频
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