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Research at the Division of Biotechnology


We are involved in several projects aiming at the development of cell-based biosensors for in vitro analysis. The research has the following directions:

Development of Organ-on-a-Chip devices for in vitro toxicity assaying and drúg testing.

The  using patient specific cells derived from induced pluripotant stem cells (iPSC) where differentiated cells are used in 3D configurations in the biochip. The work is done together with partners in the IMI-EU StemBANCC project

Recent publications from the projects:

  • Bergström G, Nilsson K, Robinson N, Mandenius CF 2014. Macroporous microcarriers for introducing cells in a microfluidic chip. Lab Chip 14, 3502-3504.
  • Fritzsche M, Fritzsche J, Tegenfeldt JO, Mandenius CF 2014. A highly UV-transparent fused silica biochip for sensitive hepatotoxicity testing by autofluorescence. Biochip J. 8, 115-121
  • Bergström G, Christoffersson J, Zweigerdt R, Schwanke K, Mandenius CF 2015. Stem cell derived cardiac bodies in a microfluidic device for toxicity testing by beating frequency imaging. Lab Chip 15, 3242-3249.


In collaboration with the Division of Industrial Production (IEI) at LiU we study the methodology for development and design of complex biotechnology instruments, devices and processes. The study also includes applications of stem cell manufacture and artificial organ bioreactors. The work has resulted in several publications including a new book where the biomechatronic methodology is decribed for a number of biotechnology applications. Read excerpts...

Recent papers from the group

  • Mandenius CF, Björkman. 2010. Mechatronic design principles for biotechnology product development, Trends Biotechnol. 28(5), 230-236
  • Mandenius CF, Björkman M. 2011. Biomechatronic Design in Biotechnology: a Methodology for Development of Biotechnology Products. John Wiley & Sons, Inc., Hoboken, New Jersey, USA
  • Darkins CL, Mandenius CF 2014. Design of large-scale manufacturing of induced pluripotent stem cell derived cardiomyocytes. Chem. Eng. Res. Design 92, 1142–1152
  • Gerlach I, Volc CH, Mandenius CF. 2015. Conceptual design of an operating training simulator for a bio-ethanol plant. Processes MDPI (Open Access) 3(3), 664-683.

Soft sensors for bioprocesses

Soft sensor principle

Methods for better monitoring and control of bioprocesses are studied with the purpose to enhance Process Analytical Technology (PAT) principles. Our approach is broader than PAT from the regulatory scope. PAT is expanded to cover bioprocesses in general (not only pheramceutical products) and economical and industrial aspects are purpsued.  In particular we exploit the following methods:

Soft sensors Robust on-line sensors supported by mathematical models derived from the systems under study. Soft sensors are useful for bioprocess monitoring due to the complexity of the biological mechanisms of the producing cells. We have used software sensors to monitor physiological signals from typical industrial cultures by combining on-line sensors such as NIR, gas analyzers and HPLC for biomass, effluent gases and key metabolites with basic mass balance and kinetic equations.

Rational design of sensor and control systems By using systematic design principles (Biomechatromnics) sensor and control systems are design in a more rational way. The systematic design aims at finding the most efficient sensor and control configuaration for the process in relation to the the users goals, either economical, quality-related or else (see also separation project).

Operator Training Simulators The practial use of sensor systems in a bioprocess requires efficient training and education methods of production staff and bioengineers. This is done by creating a vitrual process environment on the training laboratory. Also here, systematic approaches provide significant improvements in training as already done within other areas (e.g. flight simulators).

Recent papers from the group

  • Gustavsson and Mandenius, 2013 Soft sensor control of a recombinant Escherichia coli fed-batch culture producing Green Fluorescent Protein, Bioproc. Biosys. Eng. 36, 1375-84 .
  • Gerlach I, Hass VC, Brüning S, Mandenius CF. 2013. Virtual bioreactor cultivation for operator training and simulation: Application to ethanol and protein production . J. Chem. Technol. Biotechnol. 88, 2159–2168
  • Mandenius CF (2012) Design of monitoring and sensor systems for bioprocesses using biomechatronic principles. Chem. Eng. Technol., 35 (8), 1412-1420
  • Gerlach I, Mandenius CF, Hass VC, 2015. Operator training simulation for integrating cultivation and homogenisation in protein production. Biotechnol Reports 6, 91-99.
  • Gustavsson R, Lukasser C, Mandenius CF 2015. Control of specific carbon dioxide production in a fed-batch culture producing recombinant protein using a soft sensor. J. Biotechnol. 200, 41-49.
  • Mandenius CF, Gustavsson R 2015. Mini-review: Soft sensors as means for process analytical technology in the manufacture of bio-therapeutics. J Chem Technol Biotechnol  90, 215-227.

Responsible for this page: Susanne Andersson
Last updated: 10/23/15