Emerging Landscape of Computational Modeling in Pharmaceutical Development

被引:21
作者
Abramov, Yuriy A. [2 ,3 ]
Sun, Guangxu [1 ]
Zeng, Qun [1 ]
机构
[1] Shenzhen Jingtai Technol Co Ltd, XtalPi Inc, Shenzhen 518100, Peoples R China
[2] XtalPi Inc, Cambridge, MA 02142 USA
[3] Univ N Carolina, Eshelman Sch Pharm, Chapel Hill, NC 27599 USA
关键词
quantum mechanics; artificial intelligence; crystal structure prediction; computational chemistry; preclinical and clinical development; process chemistry; MOLECULAR-DYNAMICS SIMULATION; CRYSTAL-STRUCTURE PREDICTION; SOLID-FORM; NEURAL-NETWORK; SOLUBILITY PREDICTION; ACCURATE PREDICTION; SOLVENT SELECTION; ORGANIC-MOLECULES; LEAD OPTIMIZATION; REDOX POTENTIALS;
D O I
10.1021/acs.jcim.1c01580
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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.
引用
收藏
页码:1160 / 1171
页数:12
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