Avoiding overfeeding in high cell density fed-batch cultures of E. coli during the production of heterologous proteins.

Heterologous protein production often causes a significant metabolic burden in Escherichia coli cells which manifests itself in a substantial decrease in their physiological characteristics such as the maximal specific growth rate on a given substrate, the maximal substrate uptake rate as well as the maximal specific oxygen uptake rate. In high-cell-density cultures, the substrate feed rate must be adapted to this changing capabilities of the cells in order to avoid overfeeding and thus the formation of by-products that inhibit the cell performance further. This requires the precise knowledge about the changes in these specific rates, particularly during the product formation phase. In order to precisely investigate the time profile of the critical specific substrate uptake rate σcrit of microorganisms, i.e. the maximal rate at which the cells can fully oxidize their substrate, a new online tracking technique is presented. The feed rate F is modulated in such a way that the specific substrate uptake rate σ is linearly raised towards its critical value σcrit. When this is reached the feed rate is automatically reduced and the procedure is repeated. In this way the method automatically follows the changing time profile of σcrit during the entire cultivation and avoids significant acetate formation rates. This procedure considerably increases the identifiability of σcrit. The high precision of the technique also results from replacing the pO2 measurements that seem to suggest themselves for monitoring maximal oxygen uptake rate, by measuring the total oxygen consumption rate tOUR, which is available at a much higher signal-to-noise ratio and is not as prone to distortions. An important advantage of measuring tOUR is that it allows keeping pO2 controlled at its optimal value. The applicability of the new tracking technology is demonstrated at E. coli cultures. The resulting σcrit(t) profile allows determining the substrate feed rate profile and other key variables that can be used for advanced feedback control in protein production processes. The technique can be considered a PAT tool and is well suited to industrial fermentations.

kLa of stirred tank bioreactors revisited.

By means of improved feedback control kLa measurements become possible at a precision and reproducibility that now allow a closer look at the influences of power input and aeration rate on the oxygen mass transfer. These measurements are performed online during running fermentations without a notable impact on the biochemical conversion processes. A closer inspection of the mass transfer during cultivations showed that at least the number of impellers influences mass transfer and mixing: On the laboratory scale, two hollow blade impellers clearly showed a larger kLa than the usually employed three impeller versions when operated at the same agitation power and aeration rate. Hollow blade impellers are preferable under most operational conditions because of their perfect gas handling capacity. Mixing time studies showed that these two impeller systems are also preferable with respect to mixing. Furthermore the widths of the baffle bars depict a significant influence on the kLa. All this clearly supports the fact that it is not only the integral power density that finally determines kLa.

Improving cultivation processes for recombinant protein production.

An new cascade control system is presented that reproducibly keeps the cultivation part of recombinant protein production processes on its predetermined track. While the system directly controls carbon dioxide production mass and carbon dioxide production rates along their setpoint profiles in fed-batch cultivation, it simultaneously keeps the specific biomass growth rates and the biomass profiles on their desired paths. The control scheme was designed and tuned using a virtual plant environment based on the industrial process control system SIMATIC PCS 7 (Siemens AG). It is shown by means of validation experiments that the simulations in this straightforward approach directly reflect the experimentally observed controller behaviour. Within the virtual plant environment, it was shown that the cascade control is considerably better than previously used control approaches. The controller significantly improved the batch-to-batch reproducibility of the fermentations. Experimental tests confirmed that it is particularly suited for cultivation processes suffering from long response times and delays. The performance of the new controller is demonstrated during its application in Escherichia coli fed-batch cultivations as well as in animal cell cultures with CHO cells. The technique is a simple and reliable alternative to more sophisticate model-supported controllers.

Simple and efficient control of CHO cell cultures.

Cell cultures must tightly be kept under control in order to guarantee a sufficiently small variability in the protein product quality. A simple and efficient technique for CHO-cell cultures is presented that allows keeping the viable cell count X(v) and the specific growth rate µ of the cells on predefined trajectories. As X(v) and µ cannot directly be measured online, they are controlled indirectly via the total mass of oxygen consumed. Online values of the latter can precisely be estimated from off gas analysis, i.e. from the O2 volume ratio measured in the vent line and air flow rate measurements. In glutamine-limited fed-batch cultivations, the glutamine feed rate can be manipulated in such a way that the viable cell density and the specific growth rate are kept on predefined profiles for nearly the entire cultivation time. The viability of the cells is not affected by the closed loop control actions. The technique was validated with CHO-cells cultured in a 2.5-L fully instrumented stirred tank bioreactor. It is shown that the controller is able to run the process exactly on predefined tracks with a high batch-to-batch reproducibility. By means of six fed-batch cultivations of CHO cells it was shown that a remarkable reproducibility of viable cell concentration could be achieved throughout 140 h cultivation time.

Increasing batch-to-batch reproducibility of CHO cultures by robust open-loop control.

In order to guarantee the quality of recombinant therapeutic proteins produced in mammalian cell systems, the straightforward approach in industry is to run the processes as reproducible as possible. It is first shown that considerable distortions in the currently operated processes appear when the initial cell density deviates from its nominal value. Small deviations in the initial cell mass may lead to severe deviations from the desired biomass trajectory. Next, it is shown how to design a fed-batch production process in such a way that it is robust with respect to variations in the viable cell density. A simple open loop strategy is proposed for that purpose. Here we show for the first time at animal cell cultures (CHO cells) that by means of an appropriate glutamine feed rate profile F(t), which keeps the specific growth rate of the cells on a predefined value below its maximal value while maintaining the viabilities on a high level, the diverging viable cell count profiles change over into a robust converging set of profiles. The CHO cells used to validate the procedure could be focused to any specific growth rates below µ(max).

Comparison of viable cell concentration estimation methods for a mammalian cell cultivation process.

Various mechanistic and black-box models were applied for on-line estimations of viable cell concentrations in fed-batch cultivation processes for CHO cells. Data from six fed-batch cultivation experiments were used to identify the underlying models and further six independent data sets were used to determine the performance of the estimators. The performances were quantified by means of the root mean square error (RMSE) between the estimates and the corresponding off-line measured validation data sets. It is shown that even simple techniques based on empirical and linear model approaches provide a fairly good on-line estimation performance. Best results with respect to the validation data sets were obtained with hybrid models, multivariate linear regression technique and support vector regression. Hybrid models provide additional important information about the specific cellular growth rates during the cultivation.

Simple adaptive pH control in bioreactors using gain-scheduling methods.

A simple well-performing adaptive control technique for pH control in fermentations of recombinant protein production processes is described and its design procedure is explained. First, the entire control algorithm was simulated and parameterized. Afterwards it was tested in real cultivation processes. The results show that this simple technique leads to significant reductions in the fluctuations of the pH values in microbial cultures at a minimum of expenditures. The signal-to-noise ratio and thus the information captured by the pH signal were increased by about an order of magnitude. This leads to a substantial improvement in the noise of many other process signals that are used to monitor and control the process. For instance, respiratory off-gas data of CO(2) and its derived carbon dioxide production rate signals from the cultures carry much less noise as compared to those values obtained with conventional pH control. Detailed process analysis revealed that even very small pH jumps of 0.03 values during the fermentation were shown to result in pronounced deflections in CO(2)-volume fraction of 8% (peak to peak). The proposed controller, maintaining the pH within the interval of 0.01 around the setpoint, reduces the noise considerably.

Advanced control of dissolved oxygen concentration in fed batch cultures during recombinant protein production.

Design and experimental validation of advanced pO(2) controllers for fermentation processes operated in the fed-batch mode are described. In most situations, the presented controllers are able to keep the pO(2) in fermentations for recombinant protein productions exactly on the desired value. The controllers are based on the gain-scheduling approach to parameter-adaptive proportional-integral controllers. In order to cope with the most often appearing distortions, the basic gain-scheduling feedback controller was complemented with a feedforward control component. This feedforward/feedback controller significantly improved pO(2) control. By means of numerical simulations, the controller behavior was tested and its parameters were determined. Validation runs were performed with three Escherichia coli strains producing different recombinant proteins. It is finally shown that the new controller leads to significant improvements in the signal-to-noise ratio of other key process variables and, thus, to a higher process quality.

Process Analytical Technology (PAT): batch-to-batch reproducibility of fermentation processes by robust process operational design and control.

The Process Analytical Technology (PAT) initiative of the FDA is a reaction on the increasing discrepancy between current possibilities in process supervision and control of pharmaceutical production processes and its current application in industrial manufacturing processes. With rigid approval practices based on standard operational procedures, adaptations of production reactors towards the state of the art were more or less inhibited for long years. Now PAT paves the way for continuous process and product improvements through improved process supervision based on knowledge-based data analysis, "Quality-by-Design"-concepts, and, finally, through feedback control. Examples of up-to-date implementations of this concept are presented. They are taken from one key group of processes in recombinant pharmaceutical protein manufacturing, the cultivations of genetically modified Escherichia coli bacteria.

Hybrid process models for process optimisation, monitoring and control.

Hybrid models aim to describe different components of a process in different ways. This makes sense when the corresponding knowledge to be represented is different as well. In this way, the most efficient representations can be chosen and, thus, the model performance can be increased significantly. From the various possible variants of hybrid model, three are selected which were applied for important biotechnical processes, two of them from existing production processes. The examples show that hybrid models are powerful tools for process optimisation, monitoring and control.

Determination of initial velocities of enzymic reactions from progress curves.

The present communication describes a novel method for estimating initial velocities (v) of enzyme-catalysed reactions. It is based on an approximation of experimental data obtained by the cubic spline function. The initial velocity of a reaction is calculated as a derivative of the approximating function at a time value equal to zero. The proposed method is usable on a computer with a FORTRAN IV program. The method can be successfully used in such cases as substantial extents of substrate conversion, the inactivation of an enzyme in the course of a reaction, the existence of large experimental error or when the reaction mechanism is unknown.

A measuring system for biotechnical processes based on discrete methods of estimation.

An adaptive measuring system of the main variables of biotechnical processes based on the theory of estimation is elaborated upon here. All stages of system synthesis are considered. It is shown that for an adaptive measuring system all a priori information on modelling and measurement noise and process mathematical models must be used. The data of direct and indirect measurements are used for estimating the main variables. The performance of the proposed measuring system was checked using imitative modelling.