Real-time imaging and analysis of cell-hydrogel interplay within an extrusion-bioprinting capillary

Additive manufacturing platforms are transforming research and industrial sectors worldwide. In regenerative medicine and pharmaceutical applications, they facilitate the development of patient-specific devices for implantation, as well as in vitro models of tissues and organs for disease modelling and drug screening. A key example is extrusion-based bioprinting, where a bioink that contains cells, biomolecules and a support matrix (often hydrogel), is extruded through a narrow capillary onto a platform forming the desired structure. The printing parameters and hydrogel flow behavior likely determine the extent to which cells are damaged mechanically as they pass through the capillary. Here, we present direct observations of the hydrogels and suspended cells during the printing process to help elucidate conditions potentially leading to mechanical damage and cell death. Light-sheet fluorescence microscopy was applied to observe the real-time flow of bioinks through a capillary mimicking the conditions found in bioprinting. Bioink formulations exhibiting constant and shear thinning viscosities, along with UV-crosslinked gelatin methacrylol (GelMA) were studied, and cell viability of post-printed gels were measured via fluorescent imaging. Cell tracking enabled flow profiles of bioinks to be deduced. In agreement with current flow simulations, the constant and shear thinning formulations displayed a Poiseuille flow profile although with a plug velocity profile for the latter. The UV-crosslinked GelMA formulation exhibited a two-phase annular flow with gel morphologies depicting gross-melt fractures attributed to over-gelled hydrogels. Cell viability was higher in UV-crosslinked GelMA at high flow rates compared to uncrosslinked GelMA. The findings presented here will improve modeling cell-material flow during bioprinting through accurate estimation of flow conditions, in particular for complex materials. The novel imaging approach could be further exploited to provide process monitoring and feedback to improve the outcomes of 3D bioprinting.