一个经验预测模型,用于确定BCS IV类药物的水溶性,在无形固体分散中
Sridivya Raparla1, Charina Lampa1, Xiaoling Li1
1Department of Medicinal chemistry and pharmaceutics, Thomas J. long School of Pharmacy, University of the Pacific, Stockton, CA, USA.
Drug development and industrial pharmacy
|February 6, 2024
概括
开发无形固体分散 (ASD) 的预测模型可以加速口服药物开发. 这项研究创建了一个强大的模型,以超过80%的准确度预测ASD中的药物溶解度,简化了该过程.
科学领域:
- 制药科学 制药科学
- 药物运输 药物运输 药物运输
- 物理化学 物理化学
背景情况:
- 确定药物溶解度至关重要,但往往是费力的.
- 无形固体分散 (ASD) 是提高药物溶解性的关键技术.
- 预测模型可以显著加速口服药物开发.
研究的目的:
- 开发一种预测模型,用于估计无形固体分散 (ASD) 中的药物溶解度.
- 用药物和聚合物的分子描述符来预测溶解度.
- 验证预测模型的准确性和稳定性.
主要方法:
- 用各种聚合物和表面活性剂制备的模型药物的ASD,使用热过程.
- 使用差分扫描热量计 (DSC),富里埃变形红外光谱 (FTIR) 和X射线衍射 (XRD) 进行特征化ASD.
- 使用多重线性回归和Leave-One-Out交叉验证来开发和验证预测模型.
主要成果:
- 自闭症患者通过DSC和XRD证实了无形药物状态,通过FTIR没有显著的药物聚合物相互作用.
- 与纯药物相比,在自闭症患者中观察到显著的可溶性改善 (3倍至118倍).
- 开发的模型准确地预测了自闭症患者的药物溶解度,准确度>80%.
结论:
- 开发的经验模型可靠地预测了无形固体分散中的药物的水溶性.
- 该模型表现出稳定性和>80%的准确性,促进更快的口服药物开发.
- 这种预测方法简化了口服药物候选物的溶解性评估.
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