Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design

Journal of Biotechnology
Suresh SelvarasuDong-Yup Lee

Abstract

We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in t...Continue Reading

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Citations

Apr 6, 2016·The AAPS Journal·Anurag S RathoreGaurav Pratap Singh Jadaun
Jun 19, 2012·Journal of Pharmaceutical and Biomedical Analysis·Tran Thi ThuyGunnar Thorsén
Jan 19, 2012·Biotechnology and Bioengineering·Suresh SelvarasuDong-Yup Lee

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