Early mammalian process development has adopted efficient platform methods to minimize development times and to meet aggressive fast-to-clinic time lines. Generally, upstream process development is initiated with cell clones that are fully matured and adapted to medium, rendering them stable with respect to genetics, titer, growth pattern and metabolic profiles. As a result, during a given process in a defined environment, individual production cell clones exhibit relatively little biological variability. When inconsistent growth and metabolic profiles are observed in the larger scale bioreactors, generally the assumption holds that this is due to either the robustness of the process, scalability or process variability.<br/>The case study described here is based on the differences in seed expansion, production and metabolic profiles observed during the clinical manufacturing compared to the profiles in the development labs, while productivity remained unchanged. In an effort to assess the root cause of this variability, a statistical experiment is designed to compare cells from the Research Cell Bank (RCB) to cells coming from the Master Cell Bank (MCB) used for clinical manufacturing. These two cell banks differ only approximately 15 generations in age. While lot to lot medium variability was excluded as root cause, we show that the growth variability here is due to the age of the cells and that this difference can have an impact on the extent of biological variability within the cell clones. Younger cell clones such as younger RCBs displayed wider biological variability with respect to viable cell counts and viabilities within themselves as compared to the older cell clones such as MCBs. Older RCBs which went through the same number of generations as the MCB had very similar growth profiles. This highlights the need for an accurate cell line history when process development is initiated in the early space, so that process changes with predictable outcomes can be incorporated.

Influence of cell age on cell biological variability during early process development

251st National Meeting (2016)

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