ArticleJournal of industrial microbiology & biotechnology2020
A novel method based on nonparametric regression with a Gaussian kernel algorithm identifies the critical components in CHO media and feed optimization.
Article in Journal of industrial microbiology & biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrating real-time OUR monitoring with adaptive feeding for enhanced antibody production.Bioresources and bioprocessing · 2025Article
- Progress in fed-batch culture for recombinant protein production in CHO cells.Applied microbiology and biotechnology · 2023Review
- A review of algorithmic approaches for cell culture media optimization.Frontiers in bioengineering and biotechnology · 2023Review
- Review
- Serum-Free Medium for Recombinant Protein Expression in Chinese Hamster Ovary Cells.Frontiers in bioengineering and biotechnology · 2021Review
- Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.mAbsReview
- Recent advances in culture medium design for enhanced production of monoclonal antibodies in CHO cells: A comparative study of machine learning and systems biology approaches.Biotechnology advancesReview
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
As the composition of animal cell culture medium becomes more complex, the identification of key variables is important for simplifying and guiding the subsequent medium optimization. However, the traditional experimental design methods are impractical and limited in their ability to explore such large feature spaces. Therefore, in this work, we developed a NRGK (nonparametric regression with Gaussian kernel) method, which aimed to identify the critical components that affect product titres during the development of cell culture media. With this nonparametric model, we successfully identified the important components that were neglected by the conventional PLS (partial least squares regression) method. The superiority of the NRGK method was further verified by ANOVA (analysis of variance). Additionally, it was proven that the selection accuracy was increased with the NRGK method because of its ability to model both the nonlinear and linear relationships between the medium components and titres. The application of this NRGK method provides new perspectives for the more precise identification of the critical components that further enable the optimization of media in a shorter timeframe.
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Registered trials
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