RESUMEN
Within the last decade, fully disposable centrifuge technologies, fluidized-bed centrifuges (FBC), have been introduced to the biologics industry. The FBC has found a niche in cell therapy where it is used to collect, concentrate, and then wash mammalian cell product while continuously discarding centrate. The goal of this research was to determine optimum FBC conditions for recovery of live cells, and to develop a mathematical model that can assist with process scaleup. Cell losses can occur during bed formation via flow channels within the bed. Experimental results with the kSep400 centrifuge indicate that, for a given volume processed: the bed height (a bed compactness indicator) is affected by RPM and flowrate, and dead cells are selectively removed during operation. To explain these results, two modeling approaches were used: (i) equating the centrifugal and inertial forces on the cells (i.e., a force balance model or FBM) and (ii) a two-phase computational fluid dynamics (CFD) model to predict liquid flow patterns and cell retention in the bowl. Both models predicted bed height vs. time reasonably well, though the CFD model proved more accurate. The flow patterns predicted by CFD indicate a Coriolis-driven flow that enhances uniformity of cells in the bed and may lead to cell losses in the outflow over time. The CFD-predicted loss of viable cells and selective removal of the dead cells generally agreed with experimental trends, but did over-predict dead cell loss by up to 3-fold for some of the conditions. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1520-1530, 2016.
Asunto(s)
Reactores Biológicos , Separación Celular , Centrifugación , Línea Celular , HumanosRESUMEN
The pre-Bötzinger complex (preBötc) in the mammalian brainstem has an important role in generating respiratory rhythms. An influential differential equation model for the activity of individual neurons in the preBötc yields transitions from quiescence to bursting to tonic spiking as a parameter is varied. Further, past work has established that bursting dynamics can arise from a pair of tonic model cells coupled with synaptic excitation. In this paper, we analytically derive one- and two-dimensional maps from the differential equations for a self-coupled neuron and a two-neuron network, respectively. Using a combination of analysis and simulations of these maps, we explore the possible forms of dynamics that the model networks can produce as well as which transitions between dynamic regimes are mathematically possible.