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Discovery of compounds with viscosity-reducing effects on biopharmaceutical formulations with monoclonal antibodies.
Proj, Matic; Zidar, Mitja; Lebar, Blaz; Strasek, Nika; Milicic, Goran; Zula, Ales; Gobec, Stanislav.
Affiliation
  • Proj M; University of Ljubljana, Faculty of Pharmacy, Chair of Pharmaceutical Chemistry, Ljubljana, Slovenia.
  • Zidar M; Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Lek d.d., Slovenia.
  • Lebar B; University of Ljubljana, Faculty of Pharmacy, Chair of Pharmaceutical Chemistry, Ljubljana, Slovenia.
  • Strasek N; University of Ljubljana, Faculty of Pharmacy, Chair of Pharmaceutical Chemistry, Ljubljana, Slovenia.
  • Milicic G; Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Lek d.d., Slovenia.
  • Zula A; Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Lek d.d., Slovenia.
  • Gobec S; University of Ljubljana, Faculty of Pharmacy, Chair of Pharmaceutical Chemistry, Ljubljana, Slovenia.
Comput Struct Biotechnol J ; 20: 5420-5429, 2022.
Article in En | MEDLINE | ID: mdl-36212536
For the development of concentrated monoclonal antibody formulations for subcutaneous administration, 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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Comput Struct Biotechnol J Year: 2022 Document type: Article Affiliation country: Slovenia Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Comput Struct Biotechnol J Year: 2022 Document type: Article Affiliation country: Slovenia Country of publication: Netherlands