Macromolecules in Bioprocess Engineering

Macromolecules in Bioprocess Engineering

Motivation

Macromolecular components play an important role in bioprocesses, where they are frequently the desired end-product, e.g. virus particles, viral vectors, virus like particles (VLPs), phages, or other large compounds.

Composition as well as chemical and physical properties of biological macromolecular structures are often not fully known. However, they have a major impact on the process outcome and product characteristics. Hence, without detailed understanding of process components and their interactions efficient process design and optimizations is nearly impossible.

Aim of the project

The primary goal of the project is to investigate size distributions and aggregation behavior of virus particles during the downstream processing (DSP) of bioreactor harvests for manufacturing of human and veterinary vaccines. Several different complementary nanoparticle measurement methods will be used for the analysis, e.g. differential centrifugation sedimentation (DCS) [3], tunable resistive pulse sensing (TRPS) [4], and others. Based on the results obtained, the established DSP trains will be optimized to improve yields and product characteristics.

References
Pieler, M.; Heyse, A.; Wolff, M. W.; Reichl, U.: Specific ion effects on the particle size distributions of cell culture–derived influenza A virus particles within the Hofmeister series. Engineering in Life Sciences 17 (5), pp. 470 - 478 (2017)
Hämmerling, F.; Pieler, M.; Hennig, R.; Serve, A.; Rapp, E.; Wolff, M. W.; Reichl, U.; Hubbuch, J.: Influence of the production system on the surface properties of influenza A virus particles. Engineering in Life Sciences 17 (10), pp. 1071 - 1077 (2017)
Neumann, A.; Hoyer, W.; Wolff, M. W.; Reichl, U.; Pfitzner, A.; Roth, B.: New method for density determination of nanoparticles using a CPS disc centrifuge (TM). Colloids and Surfaces B: Biointerfaces 104, pp. 27 - 31 (2013)
Akpinar, F., Yin, J.
Characterization of vesicular stomatitis virus populations by tunable resistive pulse sensing.
Journal of Virology Methods 218,pp. 71–76, (2015)
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