期刊
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
卷 20, 期 -, 页码 5420-5429出版社
ELSEVIER
DOI: 10.1016/j.csbj.2022.09.035
关键词
Viscosity; Protein formulations; Biopharmaceuticals; Viscosity-reducing agents; Computational screening
资金
- Slovenian Research Agency
- Lek Pharmaceuticals d.d.
- [P1-0208]
- [L1-3160]
This study utilized computational chemistry approaches to discover 44 new viscosity-reducing agents for the development of concentrated monoclonal antibody formulations for subcutaneous administration.
For the development of concentrated monoclonal antibody formulations for subcutaneous administra-tion, the main challenge is the high viscosity of the solutions. To compensate for this, viscosity reducing agents are commonly used as excipients. Here, we applied two computational chemistry approaches to discover new viscosity-reducing agents: fingerprint similarity searching, and physicochemical property filtering. In total, 94 compounds were selected and experimentally evaluated on two model monoclonal antibodies, which led to the discovery of 44 new viscosity-reducing agents. Analysis of the results showed that using a simple filter that selects only compounds with three or more charge groups is a good 'rule of thumb' for selecting potential viscosity-reducing agents for two model monoclonal antibody formulations.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
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