No abstract

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed-batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off-line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale.

A Monod kinetic model, logistic equation model, and statistical regression model were developed for a Chinese hamster ovary cell bioprocess operated under three different modes of operation (batch, bolus fed-batch, and continuous fed-batch) and grown on two different bioreactor scales (3 L bench-top and 15 L pilot-scale). The Monod kinetic model was developed for all modes of operation under study and predicted cell density, glucose glutamine, lactate, and ammonia concentrations well for the bioprocess. However, it was computationally demanding due to the large number of parameters necessary to produce a good model fit. The transferability of the Monod kinetic model structure and parameter set across bioreactor scales and modes of operation was investigated and a parameter sensitivity analysis performed. The experimentally determined parameters had the greatest influence on model performance. They changed with scale and mode of operation, but were easily calculated. The remaining parameters, which were fitted using a differential evolutionary algorithm, were not as crucial. Logistic equation and statistical regression models were investigated as alternatives to the Monod kinetic model. They were less computationally intensive to develop due to the absence of a large parameter set. However, modeling of the nutrient and metabolite concentrations proved to be troublesome due to the logistic equation model structure and the inability of both models to incorporate a feed. The complexity, computational load, and effort required for model development has to be balanced with the necessary level of model sophistication when choosing which model type to develop for a particular application.

Across most of their range in Europe, mountain hares are usually restricted to upland areas with poor food quality. In these areas they generally feed on browse species such as heather or twigs and barks of trees. On lowland areas in Europe, with better food quality, the mountain hare is replaced by the brown hare (Lepus europaeus) which feeds predominantly on greasses. This khas led some authors to conclude that mountain hares are primarily adapted for browsing. In the absence of brown hares in Ireland, mountain hares are found on a wide variety of habitats including grassland. On grassland, their diet consists almost exclusively of grasses, up to 94% of their annual diet, which is more than has been reported for brown hares on similar habitat. Based on this evidence, and other work, it is proposed that the mountain hare in primarily a grazing animal and competitive exclusion by brown hares may underlie much of their present distribution in Europe.

The paper re-evaluates Verhulst and Monod models. It has been claimed that standard logistic equation cannot describe the decline phase of mammalian cells in batch and fed-batch cultures and in some cases it fails to fit somatic growth data. In the present work Verhulst, population-based mechanistic growth model was revisited to describe successfully viable cell density (VCD) in exponential and decline phases of batch and fed-batch cultures of three different CHO cell lines. Verhulst model constants, K, carrying capacity (VCD/ml or lg/ml) and r, intrinsic growth factor (h -1 ) have physical meaning and they are of biological significance. These two parameters together define the course of growth and productivity and therefore, they are valuable in optimisation of culture media, developing feeding strategies and selection of cell lines for productivity. The Verhulst growth model approach was extended to develop productivity models for batch and fed-batch cultures. All Verhulst models were validated against blind data (R 2 [ 0.95). Critical examination of theoretical approaches concluded that Monod parameters have no physical meaning. Monodhybrid (pseudo-mechanistic) batch models were validated against specific growth rates of respective bolus and continuous fed-batch cultures (R 2 & 0.90). Thedescribes specific growth rate during metabolic shift (R 2 & 0.95). Verhulst substrate-based growth models compared favourably with Monod-hybrid models. Thus, experimental evidence implies that the constants in the Monod-hybrid model may not have physical meaning but they behave similarly to the biological constants in Michaelis-Menten enzyme kinetics, the basis of the Monod growth model.List of symbols K Carrying capacity for VCD K V-PB Carrying capacity, Verhust-population based for VCD K V-SB Carrying capacity, Verhust-substrate eased for VCD K V-MAb Carrying capacity, Verhust for MAb r Intrinsic growth factor r X Intrinsic productivity factor r V-PB Intrinsic growth factor, Verhulst population based for VCD r V-SB Intrinsic growth factor, Verhulst substrate based for VCD r V-MAb