Modeling and Control of Microscale Cell Culture Environments
Research output: Book/Report › Doctoral thesis › Collection of Articles
|Publisher||Tampere University of Technology|
|Number of pages||59|
|Publication status||Published - 16 Aug 2018|
|Publication type||G5 Doctoral dissertation (article)|
|Name||Tampere University of Technology. Publication|
Bioreactors are typically used for cell culture in vitro. However, precise control of each cell culture’s microenvironment is diﬃcult, leading to uneven culture conditions that can aﬀect cell behavior. Furthermore, studying how certain environmental parameter aﬀect the cultures is challenging, as it is diﬃcult, or even impossible, to vary certain parameters in a controlled manner between each culture.
Microscale cell culture systems, known as microbioreactors, have recently been extensively studied to enhance control and improve long-term cell culturing by better mimicking cells’ microenvironments. Microbioreactors provide better environment control, thereby enhancing long-term cell cultivation. Unfortunately, integrating microbioreactors with the required sensors, actuators, electronics and other required devices can be challenging. Implementing sensors near the cell culture can also disturb them or prevent other measurements, such as optical microscopy. Certain measurements, such as direct longterm pH measurement, can be impossible, as there are no suitable microscale sensors available.
For these reasons, there is a huge demand for methods that can be used to study and develop proper microbioreactors. This thesis includes several studies in which modeling was used as design tools to improve and control culture environments. First, an analytical model to study gravity-driven ﬂows in microﬂuidic devices is developed. Next, developed ﬁnite element method (FEM) computer models are used to study ﬂuid ﬂow proﬁles, drug distributions, shear stress levels on cells, and sensitivity of a calorimetric ﬂow measurement system. A FEM model of carbon dioxide transport and liquid pH is also created. Additionally, the thesis proposes a novel method to indirectly control the cell culture temperature. Using system identiﬁcation techniques, a developed estimation model can precisely control temperature with a sensor that does not disturb cells or other measurements. Although this thesis only demonstrates temperature control in the cell culture, the method can potentially be used to control other environment parameters as well. Lastly, this thesis considers the limitations of the presented models and control methods, and provides recommendations for future studies.