Trends in Process Analytical Technology: Present State in Bioprocessing.

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

Equipment characterization to mitigate risks during transfers of cell culture manufacturing processes.

The production of monoclonal antibodies by mammalian cell culture in bioreactors up to 25,000 L is state of the art technology in the biotech industry. During the lifecycle of a product, several scale up activities and technology transfers are typically executed to enable the supply chain strategy of a global pharmaceutical company. Given the sensitivity of mammalian cells to physicochemical culture conditions, process and equipment knowledge are critical to avoid impacts on timelines, product quantity and quality. Especially, the fluid dynamics of large scale bioreactors versus small scale models need to be described, and similarity demonstrated, in light of the Quality by Design approach promoted by the FDA. This approach comprises an associated design space which is established during process characterization and validation in bench scale bioreactors. Therefore the establishment of predictive models and simulation tools for major operating conditions of stirred vessels (mixing, mass transfer, and shear force.), based on fundamental engineering principles, have experienced a renaissance in the recent years. This work illustrates the systematic characterization of a large variety of bioreactor designs deployed in a global manufacturing network ranging from small bench scale equipment to large scale production equipment (25,000 L). Several traditional methods to determine power input, mixing, mass transfer and shear force have been used to create a data base and identify differences for various impeller types and configurations in operating ranges typically applied in cell culture processes at manufacturing scale. In addition, extrapolation of different empirical models, e.g. Cooke et al. (Paper presented at the proceedings of the 2nd international conference of bioreactor fluid dynamics, Cranfield, UK, 1988), have been assessed for their validity in these operational ranges. Results for selected designs are shown and serve as examples of structured characterization to enable fast and agile process transfers, scale up and troubleshooting.

Influence of pluronic F68 on oxygen mass transfer.

Pluronic F68 is one of the most used shear protecting additives in cell culture cultivations. It is well known from literature that such surface-active surfactants lower the surface tension at the gas-liquid interface, which influences the mass transfer. In this study, the effect of Pluronic F68 on oxygen mass transfer in aqueous solutions was examined. Therefore, the gassing in/gassing out method and bubble size measurements were used. At low concentrations of 0.02 g/L, a 50% reduction on mass transfer was observed for all tested spargers and working conditions. An explanation of the observed effects by means of Higbie's penetration or Dankwerts surface renewal theory was applied. It could be demonstrated that the suppressed movement of the bubble surface layer is the main cause for the significant drop down of the kL a-values. For Pluronic F68 concentrations above 0.1 g/L, it was observed that it comes to changes in bubble appearance and bubble size strongly dependent on the sparger type. By using the bubble size measurement data, it could be shown that only small changes in mass transfer coefficient (kL ) take place above the critical micelle concentration. Further changes on overall mass transfer at higher Pluronic F68 concentrations are mainly based on increasing of gas holdup and, more importantly, by increasing of the surface area available for mass transfer.

Optimizing capacity utilization by large scale 3000 L perfusion in seed train bioreactors.

Increasing capacity utilization and lowering manufacturing costs are critical for pharmaceutical companies to improve their competitiveness in a challenging environment. Development of next generation cell lines, improved media formulations, application of mature technologies and innovative operational strategies have been deployed to improve yields and capacity utilization. This article describes a large-scale perfusion strategy for the N-1 seed train bioreactor that was successfully applied to achieve higher inoculation cell densities in the production culture. The N-1 perfusion at 3,000-L scale, utilizing a inclined settler, achieved cell densities of up to 158 × 10(5) cell mL(-1) at perfusion rates of 2950 L day(-1) and a retention efficiency of >85%. This approach increased inoculation cell densities and decreased cultivation times by ~20% in a CHO-based, fed-batch antibody manufacturing process while providing comparable culture performance, productivity, and product quality. The strategy therefore yielded significant increase in capacity utilization and concomitant cost improvement in a large scale cGMP facility. Details of the strategy, the cell retention device, and the cell culture performance are described in this article.

Insights into large-scale cell-culture reactors: I. Liquid mixing and oxygen supply.

In the pharmaceutical industry, it is state of the art to produce recombinant proteins and antibodies with animal-cell cultures using bioreactors with volumes of up to 20 m(3) . Recent guidelines and position papers for the industry by the US FDA and the European Medicines Agency stress the necessity of mechanistic insights into large-scale bioreactors. A detailed mechanistic view of their practically relevant subsystems is required as well as their mutual interactions, i.e., mixing or homogenization of the culture broth and sufficient mass and heat transfer. In large-scale bioreactors for animal-cell cultures, different agitation systems are employed. Here, we discuss details of the flows induced in stirred tank reactors relevant for animal-cell cultures. In addition, solutions of the governing fluid dynamic equations obtained with the so-called computational fluid dynamics are presented. Experimental data obtained with improved measurement techniques are shown. The results are compared to previous studies and it is found that they support current hypotheses or models. Progress in improving insights requires continuous interactions between more accurate measurements and physical models. The paper aims at promoting the basic mechanistic understanding of transport phenomena that are crucial for large-scale animal-cell culture reactors.

Insights into large-scale cell-culture reactors: II. Gas-phase mixing and CO2 stripping.

Most discussions about stirred tank bioreactors for cell cultures focus on liquid-phase motions and neglect the importance of the gas phase for mixing, power input and especially CO(2) stripping. Particularly in large production reactors, CO(2) removal from the culture is known to be a major problem. Here, we show that stripping is mainly affected by the change of the gas composition during the movement of the gas phase through the bioreactor from the sparger system towards the headspace. A mathematical model for CO(2)-stripping and O(2)-mass transfer is presented taking gas-residence times into account. The gas phase is not moving through the reactor in form of a plug flow as often assumed. The model is validated by measurement data. Further measurement results are presented that show how the gas is partly recirculated by the impellers, thus increasing the gas-residence time. The gas-residence times can be measured easily with stimulus-response techniques. The results offer further insights on the gas-residence time distributions in stirred tank reactors.

Product formation kinetics in genetically modified E. coli bacteria: inclusion body formation.

A data-driven model is presented that can serve two important purposes. First, the specific growth rate and the specific product formation rate are determined as a function of time and thus the dependency of the specific product formation rate from the specific biomass growth rate. The results appear in form of trained artificial neural networks from which concrete values can easily be computed. The second purpose is using these results for online estimation of current values for the most important state variables of the fermentation process. One only needs online data of the total carbon dioxide production rate (tCPR) produced and an initial value x of the biomass, i.e., the size of the inoculum, for model evaluation. Hence, given the inoculum size and online values of tCPR, the model can directly be employed as a softsensor for the actual value of the biomass, the product mass as well as the specific biomass growth rate and the specific product formation rate. In this paper the method is applied to fermentation experiments on the laboratory scale with an E. coli strain producing a recombinant protein that appears in form of inclusion bodies within the cells' cytoplasm.

Control of cultivation processes for recombinant protein production: a review.

The current state-of-the-art in control of cultivation processes for recombinant protein production is examined including the quantitative knowledge that can be activated for this purpose and the measurement techniques that can be employed for control at industrial manufacturing sites.

Periplasmic production of native human proinsulin as a fusion to E. coli ecotin.

Native proinsulin belongs to the class of the difficult-to-express proteins in Escherichia coli. Problems mainly arise due to its small size, a high proteolytic decay, and the necessity to form a native disulfide pattern. In the present study, human proinsulin was produced in the periplasm of E. coli as a fusion to ecotin, which is a small periplasmic protein of 16 kDa encoded by the host, containing one disulfide bond. The fusion protein was secreted to the periplasm and native proinsulin was determined by ELISA. Cultivation parameters were studied in parallel batch mode fermentations using E. coli BL21(DE3)Gold as a host. After improvement of fed-batch high density fermentation conditions, 153 mg fusion protein corresponding to 51.5mg native proinsulin was obtained per L. Proteins were extracted from the periplasm by osmotic shock treatment. The fusion protein was purified in one step by ecotin affinity chromatography on immobilized trypsinogen. After thrombin cleavage of the fusion protein, the products were separated by Ni-NTA chromatography. Proinsulin was quantified by ELISA and characterized by mass spectrometry. To evaluate the influence of periplasmic proteases, the amount of ecotin-proinsulin was determined in E. coli BL21(DE3)Gold and in a periplasmic protease deficient strain, E. coli SF120.

Improving the batch-to-batch reproducibility of microbial cultures during recombinant protein production by regulation of the total carbon dioxide production.

Batch-to-batch reproducibility of fermentation processes performed during the manufacturing processes of biologics can be increased by operating the cultures at feed rate profiles that are robust against typically arising disturbances. Remaining randomly appearing deviations from the desired path should be suppressed automatically by manipulating the feed rate. With respect to the cells' physiology it is best guiding the cultivations along an optimal profile of the specific biomass growth rate mu(t). However, there are two problems that speak for further investigations: Upon severe disturbances that may happen during the fermentation, the biomass concentration X may significantly deviate from its desired value, then a fixed mu-profile leads to a diminished batch-to-batch reproducibility. Second, the specific growth rate cannot easily be estimated online to a favourably high accuracy, hence it is difficult to determine the deviations in mu from the desired profile. The alternative discussed here solves both problems by keeping the process at the corresponding total cumulative carbon dioxide production-profile: it is robust against distortions in X and the controlled variable can accurately be measured online during cultivations of all relevant sizes. As compared to the fermentation practice currently used in industry, the experimental results, presented at the example of a recombinant protein production with Escherichia coli cells, show that CPR-based corrections lead to a considerably improved batch-to-batch reproducibility.

Improving the batch-to-batch reproducibility in microbial cultures during recombinant protein production by guiding the process along a predefined total biomass profile.

In industry Escherichia coli is the preferred host system for the heterologous biosynthesis of therapeutic proteins that do not need posttranslational modifications. In this report, the development of a robust high-cell-density fed-batch procedure for the efficient production of a therapeutic hormone is described. The strategy is to guide the process along a predefined profile of the total biomass that was derived from a given specific growth rate profile. This profile might have been built upon experience or derived from numerical process optimization. A surprisingly simple adaptive procedure correcting for deviations from the desired path was developed. In this way the batch-to-batch reproducibility can be drastically improved as compared to the process control strategies typically applied in industry. This applies not only to the biomass but, as the results clearly show, to the product titer also.

Open-loop control of the biomass concentration within the growth phase of recombinant protein production processes.

Recombinant protein production processes are typically divided into two phases. In the first one, pure cell propagation takes place, while in the second one product formation is switched on within the cells by adding an inducer. In the initial biomass formation phase, the cell density is rather low and, hence, the measurement quantities that could be used to determine the process' state depict small values and are rather severely distorted by measurement noise. Because of these measurement problems, the fermentation cannot be reliably controlled by feedback control during this first production phase; instead, the process must be controlled in an open-loop fashion. The consequence, worked out in this paper, is to design substrate feed rate profiles for the growth phase in such a way that they are robust with respect to the main disturbances observed in practice. The robustness of the biomass formation is shown to be primarily dependent on the specific growth rate adjusted in the first hours. High batch-to-batch reproducibility can be obtained with exponential feeding profiles F(t) corresponding to specific growth rates micro(set) well below the maximal specific growth rate micro(max) of the organism. The reduction in the growth rate needed to obtain a robust process behavior depends on the inaccuracies in the initial biomass concentrations. Quantitative feed rate profiles were obtained by numerical simulation and these results were validated experimentally by means of a series of cultivation runs, where a recombinant pharmaceutical protein was produced. All experimental data confirmed the assumptions made in the robust process design study.

Estimation of biomass concentrations in fermentation processes for recombinant protein production.

Online biomass estimation for bioprocess supervision and control purposes is addressed. As the biomass concentration cannot be measured online during the production to sufficient accuracy, indirect measurement techniques are required. Here we compare several possibilities for the concrete case of recombinant protein production with genetically modified Escherichia coli bacteria and perform a ranking. At normal process operation, the best estimates can be obtained with artificial neural networks (ANNs). When they cannot be employed, statistical correlation techniques can be used such as multivariate regression techniques. Simple model-based techniques, e.g., those based on the Luedeking/Piret-type are not as accurate as the ANN approach; however, they are very robust. Techniques based on principal component analysis can be used to recognize abnormal cultivation behavior. For the cases investigated, a complete ranking list of the methods is given in terms of the root-mean-square error of the estimates. All techniques examined are in line with the recommendations expressed in the process analytical technology (PAT)-initiative of the FDA.

Generic model control of the specific growth rate in recombinant Escherichia coli cultivations.

Generic model control is shown to be a powerful tool for keeping a microbial cultivation process close to its predetermined (optimized) control profile. This is demonstrated at the example of the green fluorescent protein expressed in genetically modified Escherichia coli host cells. It is shown that the process can be run very closely to a predefined complex profile of the specific cell growth rate mu(t). Controlling the experiments at many different growth conditions is a straightforward way of effectively collecting the data necessary for optimization of recombinant protein production systems. Although the process dynamics is rather complex, the model for the controller can be kept quite simple. The control technique, used here for specific growth rate control, is quite universal and can be applied for different biotechnological processes as well.