"Particle Informatics": Advancing Our Understanding of Particle Properties through Digital Design
"Particle Informatics": Advancing Our Understanding of Particle Properties through Digital Design
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DOI：
10.1021/acs.cgd.9b00654
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发表时间：
2019-09-01
影响因子：
3.8
通讯作者：
Maloney, Andrew G. P.
中科院分区：
文献类型：
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作者：
Bryant, Mathew J.;Rosbottom, Ian;Maloney, Andrew G. P.
我们介绍了现有的和新的方法来评估和预测固有的药物的配方和制造的颗粒特性的组合。自然地，从建立固体形式的信息学方法，我们回到药物拉莫三嗪，重新评估其背景下的剑桥结构数据库（CSD）。然后，我们应用围绕CSD-System软件套件构建的预测数字设计工具，包括专注于分子间相互作用能的Synthonic Engineering方法，来分析和理解重要的颗粒特性及其对制药几个关键阶段的影响。我们提出了一个新的，强大的工作流程，将这些方法结合在一起，以建立在从每个步骤中获得的知识，并解释如何将这些知识结合起来，以提供在配方设计和生产过程中遇到的决策点的解决方案。
We introduce a combination of existing and novel approaches to the assessment and prediction of particle properties intrinsic to the formulation and manufacture of pharmaceuticals. Naturally following on from established solid form informatics methods, we return to the drug lamotrigine, re-evaluating its context in the Cambridge Structural Database (CSD). We then apply predictive digital design tools built around the CSD-System suite of software, including Synthonic Engineering methods that focus on intermolecular interaction energies, to analyze and understand important particle properties and their effects on several key stages of pharmaceutical manufacturing. We present a new, robust workflow that brings these approaches together to build on the knowledge gained from each step and explain how this knowledge can be combined to provide resolutions at decision points encountered during formulation design and manufacturing processes.