Abramov Yuriy A, Sun Guangxu, Zeng Qun
XtalPi, Inc., 245 Main St., Cambridge, Massachusetts 02142, United States.
Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599, United States.
J Chem Inf Model. 2022 Mar 14;62(5):1160-1171. doi: 10.1021/acs.jcim.1c01580. Epub 2022 Feb 28.
Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.
在过去35年中,计算化学应用已成为药物发现工作流程中不可或缺的一部分。然而,对于学术界和工业界的很大一部分而言,支持药物开发的计算建模仍是一个相对未知的领域。本综述探讨了药物临床前和临床开发三个关键组成部分的计算建模工作流程,即工艺化学、分析研发以及药品和制剂开发。文中概述了各自工作流程中每一步的计算支持。此外,在固体形式设计的背景下,特别关注基于现代物理学的虚拟筛选方法。这涵盖了用于多晶型物、共形成剂、抗衡离子和溶剂虚拟筛选的合理方法,以支持固体形式的选择和设计。