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Publi_European-Pharma-Review_MVDA-for-cell-culture - 8 Pages

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Publi_European-Pharma-Review_MVDA-for-cell-culture

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How drug repositioning is finding its niche in drug discovery Raw material verification in the pharmaceutical industry Emma J. Shanks, Head of Screening, The Beatson Institute for Cancer Research Bülent Üstün, Senior Scientist, Merck Sharp & Dohme Solid form diversity of commonly used tableting excipients Paul E. Luner, Senior Principal Scientist, Boehringer Ingelheim Pharmaceuticals Inc

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sartoriusstedim biotech Bioprocess Monitoring and Control by BioPAT® SlMCA-online supports you in your daily work to mitigate risks and reduce production costs. - Visualize process performance to assure overall process and product quality - Detect and act on process deviations early - before exceptions occur - Fast Ft easy root cause analysis, which saves batches

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om rstock.c Shutte schen / © luch Implementing multivariate data analysis to monitor mammalian cell culture processes Payal Roychoudhury formerly AstraZeneca Ronan O’Kennedy Fujifilm Diosynth Biotechologies Brian McNeil and Linda M. Harvey University of Strathclyde Biopharmaceutical companies are constantly evaluating new methods for mammalian cell line development that offer benefits such as shorter time lines, improved consistency, higher monoclonal antibody (mAb) production, better genetic stability and increased flexibility. Each of these advantages extends a potentially large cost...

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CHEMOMETRICS was used to perform the multivariate analysis. The modelling approach followed here is that of observational level modelling, and involves unfolding of three-dimensional data as illustrated in Figure 1. This type of unfolding has previously been successfully used for detection of abnormal batches3,4. The PLS model was used to associate the process data to maturity-related Y-variable (days elapsed) to align batch data according to (chronological) absolute time of each batch (literally, the time from the start of the batch)5. In SIMCA, the maturity variable is smoothed within...

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CHEMOMETRICS reveals how the samples are related to each other in the given measurements8. The scores plot is useful in highlighting the pattern of the samples, and can help identify unusual or inconsistent patterns, which might indicate potential problems with the model/or samples. A visual summary of the process behaviour over time can be observed in scores plot, where the score vectors t1 and t2 are plotted against each other. Here, the Hotelling T2 plot has been used as it provides a confidence interval of 95 per cent and the observations situated outside ‘‘Loadings are used to...

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CHEMOMETRICS The input parameters dCO 2, dO 2, pH, glucose and lactate levels have a significant impact on the outcome of the cell culture process. pH, dCO2, dO2 have a broadly similar effect on the cell culture process, grouping in the same quadrant, whereas lactate has the reverse effect. In a cell culture process, lactate is a metabolic waste product and should be maintained at low levels as it is toxic to the producing cells and should be ensured that the cells are not growing at the expense of protein synthesis7. However, the input parameter, glucose appears to have a dominant effect...

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CHEMOMETRICS components, where PC1 explains the greatest variation in the model of 92 per cent and the subsequent components explains decreasing amount of variation. Figure 5 (page 18) shows the VIP plots from the CHO cell production batches using days elapsed as the Y-variable. Some interesting features can be observed from the VIP plot such as: mAb shows the strongest influence on the cell culture process, which is in accordance with the loadings plot where mAb shows the largest absolute values of w*c1 and w*c2 being situated far away from the origin, followed by glucose, VCC, %viability...

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CHEMOMETRICS Biographies Payal Roychoudhury is a former employee of AstraZeneca (AZ) where she has been working as Senior Cell culture Scientist at R&D Mölndal, Sweden. In 2009, Payal joined AZ and has extensive experience with near infrared spectroscopy (NIR) and bioprocessing. She has worked with microbial, mammalian, insect cells and Pichia cultures. She has recently joined the Cell Culture Development department at Lonza Biologics as Lead Scientist. Payal completed her PhD on ‘Infrared spectroscopy to monitor industrial bioprocesses’ from the University of Strathclyde, Glasgow, UK. She...

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