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A mechanistic model of erythroblast growth inhibition providing a framework for optimisation of cell therapy manufacturing
- Glen, Katie E., Cheeseman, Elizabeth A., Stacey, Adrian J., Thomas, Robert J.
- Biochemical engineering journal 2018 v.133 pp. 28-38
- autocrine signaling, bioreactors, culture media, cytokines, economic sustainability, engineering, erythroblasts, erythrocytes, growth retardation, interphase, manufacturing, mass transfer, mechanistic models, metabolites, phenotype, production costs, statistical analysis, therapeutics
- Manufacture of Red Blood Cell based products in vitro requires highly efficient erythroblast culture for economic viability. It has previously been shown that efficiency of erythroblast culture in scalable bioreactors is not primarily limited by mass transfer, availability of medium components, or commonly recognised inhibitory metabolites or cytokines. We have developed a dynamic mechanistic model that describes an autocrine feedback loop in which a cell-derived factor accumulates in culture medium resulting in reversible erythroblast growth inhibition. Cells exhibited two phases of growth: a relatively uninhibited followed by an inhibited phase. Cell cycle analysis during inhibition identified slight accumulation of cells in S phase, distinct from the G1 accumulation anticipated in growth factor or nutrient deprivation. Substantial donor to donor growth rate variability (mean 0.047 h−1, standard deviation 0.008 h−1) required the growth rate parameter to be refitted for different donors. The model could then be used to predict growth behaviour with full medium exchange, but showed some reduced predictive ability after partial medium exchange. The model could predict the growth inflexion point over a range of phenotypic maturities from early to late maturity erythroblasts; however the secondary phase of growth differed substantially with less inhibition observed in more mature cells. The model provided a framework to optimise culture economics based on cost of production time and input consumables. It also provided a framework to evaluate the benefits of biological process engineering in medium design or cell modification vs. operational optimisation depending on the specific cost scenario of a process developer.