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Assessing plasmid bioprocess reproducibility and C‐source uptake stage through multivariate analysis of offline and online data

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BACKGROUND: A considerable effort has been put forth by the biopharmaceutical industry to guarantee high-quality products and patient safety. Ensuring the reproducibility of microbial cultures is essential to achieve such high standards. Reproducibility is usually assessed by offline, costly and time-consuming analyses of the final product, disregarding the culture behavior along time, which affects the final product. Online data provided in real time by the bioreactor unit control (e.g., temperature, pH, dissolved oxygen concentration), unlike offline data acquired along the culture, implies no extra cost or contamination risks, thus holding the promise of playing an important role in assessing culture reproducibility. RESULTS: Eleven batch recombinant Escherichia coli DH5-α cultures producing the plasmid model pVAX-LacZ were analyzed by Multivariate Data Analysis (MVDA) of online and offline data. Similarities between the cultures were inspected by Principal Component Analysis (PCA) and the significance of the differences determined by Multivariate Analysis of Variance (MANOVA) based on offline data. Linear Discriminant Analysis (LDA) based on the online bioreactor data was also successful in predicting the cell growth stage at each time point regarding the C-source under consumption. CONCLUSION: Multivariate data analysis based on offline and online data has proved to be a valuable tool in assessing the cultures’ reproducibility and the metabolic stage regarding the C-source consumption phase at a given time. These results may certainly impact the biopharmaceutical industry, by drawing attention to the usefulness of combining MVDA and bioprocess data, particularly online data, never used for these purposes.

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Biopharmaceuticals PAT Multivariate data analysis Plasmid Reproducibility

Citation

LOPES, Marta B.; CALADO, Cecília R. C. – Assessing plasmid bioprocess reproducibility and C‐source uptake stage through multivariate analysis of offline and online data. Journal of Chemical Technology and Biotechnology. ISSN 0268-2575. Vol. 93, N.º 10 (2018), pp. 3056-3066

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Wiley

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