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PMID: 36224707 Published · ppublish English Journal Article

Computational prediction of blend time in a large-scale viral inactivation process for monoclonal antibodies biomanufacturing.

Biotechnology and bioengineering ·Vol. 120 ·No. 1 ·2023-00-00 ·页码 169-183

Sirasitthichoke C, Hoang D, Phalak P, Armenante PM, Barnoon BI, Shandil I

Abstract

Viral inactivation (VI) is a process widely used across the pharmaceutical industry to eliminate the cytotoxicity resulting from trace levels of viruses introduced by adventitious agents. This process requires adding Triton X-100, a non-ionic detergent solution, to the protein solution and allowing sufficient time for this agent to inactivate the viruses. Differences in process parameters associated with vessel designs, aeration rate, and many other physical attributes can introduce variability in the process, thus making predicting the required blending time to achieve the desired homogeneity of Triton X-100 more critical and complex. In this study we utilized a CFD model based on the lattice Boltzmann method (LBM) to predict the blend time to homogenize a Triton X-100 solution added during a typical full-scale commercial VI process in a vessel equipped with an HE-3-impeller for different modalities of the Triton X-100 addition (batch vs. continuous). Although direct experimental progress of the blending process was not possible because of GMP restrictions, the degree of homogeneity measured at the end of the process confirmed that Triton X-100 was appropriately dispersed, as required, and as computationally predicted here. The results obtained in this study were used to support actual production at the biomanufacturing site.

Keywords
CFD analysis bioprocess blend time large scale manufacturing viral inactivation
MeSH 主题词
Virus Inactivation Octoxynol Antibodies, Monoclonal Drug Industry/methods Viruses
化学物质
Octoxynol Antibodies, Monoclonal
作者与单位
共 6 位作者,点击展开单位 / ORCID
Sirasitthichoke Chadakarn ORCID
Department of Manufacturing Science and Technology, Bristol Myers Squibb Company, Devens, Massachusetts, USA. | Otto H. York Department of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA.
Hoang Duc ORCID
Department of Manufacturing Science and Technology, Bristol Myers Squibb Company, Devens, Massachusetts, USA. | Department of Chemical Engineering, University of Massachusetts Lowell, Lowell, Massachusetts, USA.
Phalak Poonam
Department of Manufacturing Science and Technology, Bristol Myers Squibb Company, Devens, Massachusetts, USA.
Armenante Piero M
Otto H. York Department of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA.
Barnoon Barak I
Department of Manufacturing Science and Technology, Bristol Myers Squibb Company, Devens, Massachusetts, USA.
Shandil Ishaan
Department of Manufacturing Science and Technology, Bristol Myers Squibb Company, Devens, Massachusetts, USA.
Article Info
Journal
Biotechnology and bioengineering
Abbr.
Biotechnol Bioeng
ISSN
1097-0290
Published
2023-00-00
电子出版
2022-00-26
页码
169-183
Language
English
Country/Region
United States
NLM ID
7502021
基金资助
Bristol-Myers Squibb
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