Biotechnology Journal
DOI 10.1002/biot.201000413
Biotechnol. J. 2011, 6, 902–903
Editorial: Towards faster bioprocess development
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olecular biosciences have created a phenomenal resource of innumerable molecules, enzymes, and organisms that await further exploitation. In addition to rapid development in the pharmaceutical sector, industrial biotechnology has also demonstrated impressive growth, and consequently biotechnology is seen as one of the key technologies of the 21st century. In 2030 it is expected that one third of the worldwide industrial production is related to biotechnological processes with a market volume of more than $300 billion (http://www.bio-economy.net/ reports/files/koln_paper.pdf). The big advantage of bioprocesses compared to chemical processes is their sustainability. Enzymes, which are the basic catalysts in almost all bioprocesses, work under normal air pressure and moderate temperatures, and are regenerable from recultivable resources. The biggest current challenge for the establishment of a real bioeconomy is the timeline from identifying a potential product to market launch, which has a significant direct effect on the costs. Currently, the process development time remains long, with about 3–8 years in the industrial biotechnology sector and 8–15 years in the pharmaceutical sector. Although other factors, such as lengthy clinical studies, contribute to this timeframe, the real process development time is often delayed by trial-and-error phases and inconsistent use of engineering principles. Consistent process development today should be performed from the perspective of the final process scale, i.e., an
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integrated view of the whole production line and the whole process development strategy. Based on this, strategies should be aligned through development from early screening phases to the final process and process development should be rather based on a proper scaledown instead of the use of standard procedures that have been developed in laboratories for other purposes. Although such principles are increasingly applied in some larger companies, in many cases process development still lacks consistency in several areas: i. decisions are made based on personal educational background and competences ii. cultivation/process strategies change in the line of process development (fed-batch is standard in production, but rarely used for screening in early process development) iii. process development is generally performed in well mixed, homogeneous systems while final processes are inhomogeneous by the limited possible energy input. In conclusion scale-up and scaledown strategies are a key for successful implementation of bioprocesses in industry. These days, many pharmaceutical companies have recognized the importance of a detailed reactor and process characterization for approval by the authorities and also the transfer of processes to other facilities around the globe, which often can differ by their specific equipment. Despite the experiences that exist in industry in view of bioprocess scaleup, and despite the activities of few laboratories in scale-up re-
search, our knowledge in this area from an interdisciplinary point of view is quite incomplete or at least restricted to single case studies. Scale-up and scale-down strategies are a key for successful implementation of bioprocesses in industry A more effective scale-up demands emphasis especially in the following areas of research: i. A proper data-based description of industrial-scale bioreactors and conclusions in relation to the effect of engineering changes for an improved process performance. In the paper by Noorman [1] the literature on bioprocess scale-down is extensively discussed and important conclusions are drawn. A key for a better scale-up is a more comprehensive characterization not only of the fluid dynamics in industrial-scale bioreactors, but also data collection for biological phenomena, which in consequence would allow the establishment of better models as a basis for a proper scaledown. Thus, sensors and sampling tools in different parts of a bioreactor are needed. Examples of how industrial scale bioreactors can be described are provided in this review. ii. The establishment of proper scale-down simulators that allow the estimation of effects of changed process parameters in relation to the process robustness. Such simulators should resolve the kinetics of cellular responses
© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim
Biotechnol. J. 2011, 6, 902–903
as a basis for improved process models. The paper by de Jonge et al. [2] is an excellent study that points in the direction of these needs using the example of a Penicillium process. Nienow et al. [3] apply a scale down simulator as a tool to propose improved mixing strategies for brewery fermentations, indicating that even traditional bioprocesses carry a large potential for optimization. Finally, Baez et al. [4] introduce the issue of carbon dioxide gradients to scale-down systems – an issue that has been discussed for a long time, but so far no data existed that describe the effects of carbon dioxide gradients in largescale bioreactors. iii. Explicit tools and strategies that are applicable for largescale characterization and process scale-up (what should be performed? what needs to be measured?). These standards have been implemented in the -omics areas and in metabolic modeling, and would be a valuable tool for industries and applied academia. One example for a scale-down system that could be widely applied is described in the paper by Junne et al. [5]. It describes an improved version of a scale-down bioreactor that fully fulfills the needs of a scale-down system that can simulate inhomogeneities from large scale bioreactors and at the same time allows for metabolic studies. It is important to mention that this system is composed of commercially available units and thus can be easily installed
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and applied in industrial environments. If these tools are in place, process development can make full use of current molecular analytical tools from the area of proteomics, transcriptomics and metabolomics, as discussed for transcriptomics by Schweder [6]. Physiological data from large-scale bioreactors can be not easily interpreted if they are evaluated without knowledge about the fluid dynamics in bioreactors [7]. Thus, only an integrated view of all the factors mentioned above will provide a comprehensive picture about the physiological responses and reaction times of industrial organisms. The idea for the actual scaleup/down issue in the Biotechnology Journal goes back to the first BioProScale symposium Inhomogeneities in large-scale bioreactors, Description – Scaling – Control in autumn 2009 in Berlin. This symposium obtained an unforeseen amount of interest from industry and initiated a number of discussions and collaborative activities. Thus, we believed that such an issue summarizing the experiences of academic and industrial researchers from different areas may provide a comprehensive picture of the ongoing research in the area and may increase the awareness of these large-scale issues to the scientific public.
Peter Neubauer
References [1] Norman, H. An industrial perspective on bioreactor scale-down: What we can learn from combined largescale bioprocess and model fluid studies. Biotechnol. J. 2011, 6, 934–943. [2] de Jonge, L. P., Buijs, N. A. A., ten Pierick, A., Deshmukh, A. et al., Scale-down of the penicillin production in Penicillium chrysogenum. Biotechnol. J. 2011, 6, 944–958. [3] Nienow, A. W., Nordkvist, M., Boulton, C. A., Scale-down/scale-up studies leading to improved commercial beer fermentation. Biotechnol. J. 2011, 6, 911–925. [4] Baez, A., Flores, N., Bolívar, F., Ramírez, O. T., Simulation of dissolved CO2 gradients in a scale-down system: A metabolic and transcriptional study of recombinant Escherichia coli. Biotechnol. J. 2011, 6, 959–967. [5] Junne, S., Klingner, A., Kabisch, J., Schweder, T., Neubauer, P., A twocompartment bioreactor system made of commercial parts for bioprocess scale-down studies: Impact of oscillations on Bacillus subtilis fed-batch cultivations. Biotechnol. J. 2011, 6, 1009–1017. [6] Schweder, T., Bioprocess monitoring by marker gene analysis. Biotechnol. J. 2011, 6, 926–933. [7] Enfors, S. O., Jahic, M., Rozkov, A., Xu, B., et al., Physiological responses to mixing in large scale bioreactors. J. Biotechnol. 2001, 85, 175–185.
Peter Neubauer Technische Universität Berlin, Germany E-mail:
[email protected]
© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim
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