Novel Production Processes and Multi-Scale Analysis, Modelling and Design of Cell-Cell and Cell-Bioreactor Interactions (SPP2170)


Person to contact: Sebastian Hofmann 

Financing: German Research Foundation (Deutsche Forschungsgemeinschaft - DFG) 

Duration: December 2019 - November 2022 (first funding period)


Prof. Dr.-Ing. Ralf Takors, US, Institute of Biochemical Engineering (IBVT);

Prof. Dr. Georg Sprenger, US, Institute of Microbiology (IMB);

Prof. Dr. rer. nat. Miriam Agler-Rosenbaum, Leibniz-HKI;

Prof. Dr.-Ing. Jochen Büchs, RWTH, Biochemical Engineering (AVT);

Dr. Meike Baumgart, FZ Jülich, Institute of Bio- and Geosciences (IBG);

Prof. Dr. Dietrich Kohlheyer, FZ Jülich, Institute of Bio- and Geosciences (IBG);

Dr.-Ing. Christian Dusny , Helmholtz UFZ;

Dr.-Ing. Stephan Noack, FZ Jülich, Institute of Bio- and Geosciences (IBG);

Prof. Dr.-Ing. Alexander Grünberger, UB, Multiscale Bioengineering;

Prof. Dr.-Ing. Heiko Briesen, TUM, Process Systems Engineering (SVT);

Dr. Anna-Lena Heins, TUM, Biochemical Engineering (BioVT);

Prof. Dr.-Ing. Andreas Kremling, TUM, Systems Biotechnology (SBT);

Dr. Katharina Pflüger-Grau, TUM, Systems Biotechnology (SBT);

Prof. Dr.-Ing. Dirk Weuster-Botz, TUM, Biochemical Engineering (BioVT);



Reliable production of new biological agents and efficient strategies to scale-up the processes to industrial sizes are of particular importance. This is a major challenge because industrial scale bioreactors are often subjected to transient cultivation conditions caused by spatial and temporal gradients, which often diminish the cellular performance and cell viability of microorganisms (Lara et al., 2006; Paul and Herwig, 2020). Particularly modern local probes, which are usually located near the reactor wall (Busse et al., 2017) lack the ability to spatiotemporally quantify these heterogeneities in mixing and cellular performance throughout the reactor. Hence, the residence times of cells in prevailing compartments (Kuschel and Takors, 2020) and their turbulent pathways, also called lifelines (Lapin et al., 2004), cannot be mapped, which emphasizes the necessity for a transfer technology between laboratory and industrial scale.


Free-floating Lagrangian Sensor Particles (LSP) that follow the fluid flow in a characteristic way are the state-of-the-art to represent both experimentally-based trajectories and spatiotemporal resolved conditions (Bisgaard et al., 2020). This approach may portray a characteristic footprint of a stirred tank reactor (STR) and adjusted cultivation parameters and offers eventual optimization potential for industrial scales, however, strongly dependent on the LSP’s design. The goal of such a LSP is to mimic the lifeline of a cell and sufficiently resolve gradients of pH, the concentration of dissolved oxygen or substrate at the corresponding position in the reactor. Nonetheless, their minimum size and weight is predetermined by technical limitations in sensor miniaturization on printed circuit boards (PCB), battery size and type of data handling. The accompanying flow-following capability of such a finite-sized, inertial particle in a turbulent regime is not yet fully understood and so is the significance of recorded data sets. For this reason, a combined approach of laboratory-, pilot-, and production-scale experiments and associated numerical simulations using a commercial Lattice-Boltzmann CFD solver (M-Star CFD, M-Star Simulations, LLC, Ellicott City, MD, USA) is being developed at the Institute for Multiphase Flows (IMS) at the Hamburg University of Technology (TUHH).

On the one hand, 4D-Particle Tracking Velocimetry (4D-PTV, DaVis, LaVision GmbH, Göttingen, Germany) and the “Shake-the-Box” method (Schanz et al., 2016) is utilized in order to obtain spatially (148 µm/px) and temporally (up to 525 Hz) highly resolved particle trajectories of differently sized inertial particles (180 µm, 1000 kg/m3 and 732 µm, 1024 kg/m3) in a 3 L STR. Accompanying Lattice-Boltzmann simulations are assessed and validated by gained experimental data in the same geometry with respect to non-dimensional numbers, such as the particle Reynolds number and the Stokes number. The latter provides information about the particle flow-following behavior (Ouellette et al., 2008), and thus crucial information regarding hydrodynamics in a highly turbulent regime.

On the other hand, experiments in a 200 L and a 15000 L transparent acrylic glass bioreactor are conducted to investigate multiple LSP designs (own developed designs in the left picture below). They differ not only in hardware components or data type handling (storage or wireless transfer), but also in shape, size and shell material (Bisgaard et al., 2021; Buntkiel et al., 2021; Lauterbach et al., 2019; Stine et al., 2020), which strongly influences the LSP’s sensitivity to hardware failure, its axial distribution and velocity in the reactor and most importantly its overall trajectory (see right picture below).

In this project, evaluations of experimental and numerical Lagrangian particle trajectories inside a 3 L bioreactor are done together with those of LSPs inside the 200 L and 15000 L scale. Thereof, similarities and differences regarding their flow-following behavior in the respective scale may be deduced. It will be investigated whether recorded LSP data can be ascribed to lifelines of a cell during a cultivation process and how further Lattice-Boltzmann simulations in combination with a multiscale experimental analysis have the potential to become the transfer technology of choice.

We gratefully acknowledge the funding by the German Research Foundation (DFG) within the Priority Program “InterZell” (SPP2170, project number 427899833).


Bisgaard, J., Muldbak, M., Cornelissen, S., Tajsoleiman, T., Huusom, J.K., Rasmussen, T., Gernaey, K.V., 2020. Computational and Structural Biotechnology Journal 18, 2908–2919. doi:10.1016/j.csbj.2020.10.004

Bisgaard, J., Muldbak, M., Tajsoleiman, T., Rydal, T., Rasmussen, T., Huusom, J.K., Gernaey, K.V., 2021. Chemical Engineering Research and Design 174, 471–485. doi:10.1016/j.cherd.2021.08.008

Buntkiel, L., Reinecke, S., Heller, A., Budelmann, C., Hampel, U., 2021. Dresdner Sensor-Symposium 2021, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, Online, pp. 22–27. doi:10.5162/15dss2021/2.2

Busse, C., Biechele, P., de Vries, I., Reardon, K.F., Solle, D., Scheper, T., 2017. Eng. Life Sci. 17, 940–952. doi:10.1002/elsc.201700049

Kuschel, M., Takors, R., 2020. Biotechnology and Bioengineering 117, 2760–2770. doi:10.1002/bit.27457

Lapin, A., Müller, D., Reuss, M., 2004. Ind. Eng. Chem. Res. 43, 4647–4656. doi:10.1021/ie030786k

Lara, A.R., Galindo, E., Ramírez, O.T., Palomares, L.A., 2006. MB 34, 355–382. doi:10.1385/MB:34:3:355

Lauterbach, T., Lüke, T., Büker, M.-J., Hedayat, C., Gernandt, T., Moll, R., Grösel, M., Lenk, S., Seidel, F., Brunner, D., Bley, T., Walther, T., Lenk, F., 2019. Sensors and Actuators A: Physical 287, 29–38. doi:10.1016/j.sna.2019.01.003

Ouellette, N.T., O’Malley, P.J.J., Gollub, J.P., 2008. Phys. Rev. Lett. 101, 174504. doi:10.1103/PhysRevLett.101.174504

Paul, K., Herwig, C., 2020. Eng. Life Sci. elsc.201900162. doi:10.1002/elsc.201900162

Schanz, D., Gesemann, S., Schröder, A., 2016. Exp Fluids 57, 70. doi:10.1007/s00348-016-2157-1

Stine, J.M., Beardslee, L.A., Sathyam, R.M., Bentley, W.E., Ghodssi, R., 2020. Sensors and Actuators B: Chemical 320, 128381. doi:10.1016/j.snb.2020.128381