通过合作计算和实验探索,最大限度地降低多态风险
Christopher R Taylor1, Matthew T Mulvee2, Domonkos S Perenyi2
1Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton SO17 1NX, U.K.
Journal of the American Chemical Society
|September 8, 2020
概括
结合实验的计算晶体结构预测 (CSP) 成功识别了异化和异化的难以捉摸的多态,从而最大限度地降低了与固体药物形式相关的风险.
科学领域:
- 制药科学
- 材料科学
- 计算化学
背景情况:
- 药物中的多态性在药物开发和制造方面带来了挑战.
- 可以在发育晚期出现意想不到的多态,增加风险.
- 计算式晶体结构预测 (CSP) 为探索固态景观提供了一个潜在的解决方案.
研究的目的:
- 将最先进的CSP与实验方法相结合,以探索制药晶体结构.
- 合理化获得特定多态的困难,并最大限度地降低晚出现的形式的风险.
- 调查异化和异化的固体形态.
主要方法:
- 使用先进的计算晶体结构预测 (CSP) 技术.
- 采用了广泛的实验结晶方法,包括高压实验.
- 应用自由能量计算来合理化实验观测.
主要成果:
- CSP成功预测了前几十年未解决的异化物形式III的结构.
- CSP准确地预测了iproniazid多态性的风险.
- 通过实验获得并描述了第一批三种已知的非溶化晶体形式,所有这些都是CSP预测的.
结论:
- 协同计算-实验方法有效地消除了药物固体形式的风险.
- CSP是预测和理解多态的强大工具, 帮助药物开发.
- 高压实验成功地获得了难以捉摸的晶体形式,
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