Your browser doesn't support javascript.
loading
Modeling the behavior of monoclonal antibodies on hydrophobic interaction chromatography resins.
Nolan, Douglas; Chin, Thomas R; Eamsureya, Mick; Oppenheim, Sheldon; Paley, Olga; Alves, Christina; Parks, George.
Afiliação
  • Nolan D; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA. Douglas.Nolan@takeda.com.
  • Chin TR; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA.
  • Eamsureya M; Eurofins Lancaster Laboratories Professional Scientific Services, LLC, Lancaster, PA, 17601, USA.
  • Oppenheim S; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA.
  • Paley O; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA.
  • Alves C; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA.
  • Parks G; Takeda Pharmaceuticals America Inc, Lexington, MA, 02421, USA.
Bioresour Bioprocess ; 11(1): 25, 2024 Feb 15.
Article em En | MEDLINE | ID: mdl-38647931
ABSTRACT
Monoclonal antibodies (mAbs) require a high level of purity for regulatory approval and safe administration. High-molecular weight (HMW) species are a common impurity associated with mAb therapies. Hydrophobic interaction chromatography (HIC) resins are often used to remove these HMW impurities. Determination of a suitable HIC resin can be a time and resource-intensive process. In this study, we modeled the chromatographic behavior of seven mAbs across 13 HIC resins using measurements of surface hydrophobicity, surface charge, and thermal stability for mAbs, and hydrophobicity and zeta-potential for HIC resins with high fit quality (adjusted R2 > 0.80). We identified zeta-potential as a novel key modeling parameter. When using these models to select a HIC resin for HMW clearance of a test mAb, we were able to achieve 60% HMW clearance and 89% recovery. These models can be used to expedite the downstream process development for mAbs in an industry setting.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article