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Prediction of antibody production performance change in Chinese hamster ovary cells using morphological profiling.
Hisada, Takumi; Imai, Yuta; Takemoto, Yuto; Kanie, Kei; Kato, Ryuji.
Afiliación
  • Hisada T; Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Tokai National Higher Education and Research System, Furocho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan.
  • Imai Y; Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Tokai National Higher Education and Research System, Furocho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan.
  • Takemoto Y; Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Tokai National Higher Education and Research System, Furocho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan.
  • Kanie K; Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Tokai National Higher Education and Research System, Furocho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan; Department of Biotechnology and Chemistry, Faculty of Engineering, Kindai University, 1 Uman
  • Kato R; Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Tokai National Higher Education and Research System, Furocho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan; Institute of Nano-Life-Systems, Institute for Innovation for Future Society, Nagoya Universi
J Biosci Bioeng ; 137(6): 453-462, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38472072
ABSTRACT
Monoclonal antibodies (mAbs) represent a significant segment of biopharmaceuticals, with the market for mAb therapeutics expected to reach $200 billion in 2021. Chinese Hamster Ovary (CHO) cells are the industry standard for large-scale mAb production owing to their adaptability and genetic engineering capabilities. However, maintaining consistent product quality is challenging, primarily because of the inherent genetic instability of CHO cells. In this study, we address the need for advanced technologies for quality monitoring of host cells in biopharmaceuticals. We highlight the limitations of traditional cell assessment techniques such as flow cytometry and propose a noninvasive, label-free image-based analysis method. By utilizing advanced image processing and machine learning, this technique aims to non-invasively and quantitatively evaluate subtle quality changes in suspension cells. The research aims to investigate the use of morphological analysis for identifying subtle alterations in mAb productivity of CHO cells, employing cells stimulated by compounds as a model for this study. Our results show that the mAb productivity of CHO cells (day 8) can be predicted only from their early morphological profile (day 3). Our study also discusses the importance of strategic methods for forecasting host cell mAb productivity using morphological profiles, as inferred from our machine learning models specialized in predictive score prediction and anomaly prediction.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cricetulus / Anticuerpos Monoclonales Límite: Animals Idioma: En Revista: J Biosci Bioeng Asunto de la revista: ENGENHARIA BIOMEDICA / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cricetulus / Anticuerpos Monoclonales Límite: Animals Idioma: En Revista: J Biosci Bioeng Asunto de la revista: ENGENHARIA BIOMEDICA / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón