Computational analysis of integrated biosensing and shear flow in a microfluidic vascular model

Abstract

Fluid flow and flow-induced shear stress are critical components of the vascular microenvironment commonly studied using microfluidic cell culture models. Microfluidic vascular models mimicking the physiological microenvironment also offer great potential for incorporating on-chip biomolecular detection. In spite of this potential, however, there are few examples of such functionality. Detection of biomolecules released by cells under flow-induced shear stress is a significant challenge due to severe sample dilution caused by the fluid flow used to generate the shear stress, frequently to the extent where the analyte is no longer detectable. In this work, we developed a computational model of a vascular microfluidic cell culture model that integrates physiological shear flow and on-chip monitoring of cell-secreted factors. Applicable to multilayer device configurations, the computational model was applied to a bilayer configuration, which has been used in numerous cell culture applications including vascular models. Guidelines were established that allow cells to be subjected to a wide range of physiological shear stress while ensuring optimal rapid transport of analyte to the biosensor surface and minimized biosensor response times. These guidelines therefore enable the development of microfluidic vascular models that integrate cell-secreted factor detection while addressing flow constraints imposed by physiological shear stress. Ultimately, this work will result in the addition of valuable functionality to microfluidic cell culture models that further fulfill their potential as labs-on-chips.