Modeling in vitro cell culture microenvironments

Culturing cells in vitro is one of the most used method in many biomedical and biochemical engineering fields. Optimal environment is essential for human cell cultures. To mimic normal human body conditions in vitro, cells should be cultured in a biomimetic and controlled environment. Several environmental parameters, such as, temperature, nutrient delivery, oxygen (O2) and carbon dioxide (CO2) (used to control medium pH), are required to be maintained in a physiologically relevant level. Furthermore, cell morphology, orientation, and fate of differentiated stem cells can be affected by mechanical stimulation.
Modeling allows us to study environmental changes and mechanical stimulation in a cell level, thus improve microscale cell culture systems. Here we summarize the modeling work related to the microscale cell culture system currently under development. The system does not only provide physiologically relevant cell culture conditions in vitro but can also regulate the microenvironment and the functions of cells.
Models of passive delivery of nutrient and drug molecules using gravity-driven flow were used to study for example drug distribution1-3. Developed temperature estimation model4 provided a method to control indirectly cell culture temperature. It has been used in temperature-dependent cell study to regulate the beating rate of cardiomyocytes cell cultures5. Developed finite element model (FEM) has been used to study and optimize gas transport and liquid pH inside the culturing device6. Finally, a FEM model was used to characterize the developed stretching device7. To conclude, developed models have improved the understanding of cell culture microenvironments and have helped to improve in vitro cell culture systems.

References
[1] A.-J. Mäki et al. J. Fluids Eng. 137, 21105 (2015).
[2] A.-J. Mäki et al. in ASME 2014 12th Int. Conf. Nanochannels, Microchannels Minichannels V001T02A003 (2014).
[3] A.-J. Mäki et al. in 2016 IEEE 11th Annu. Int. Conf. Nano/Micro Eng. Mol. Syst. 1–5 (2016).
[4] A.-J. Mäki et al. IEEE Trans. Autom. Sci. Eng. 1–10 (2016).
[5] A.-J. Mäki et al. SLAS Technol. (accepted).
[6] A.-J. Mäki et al. Chem. Eng. Sci. 137, 515–524 (2015).
[7] J. Kreutzer et al. in 2017 Int. Conf. Manip. Autom. Robot. Small Scales 1–5 (2017).