Predicting Printability of Bio-inks by Capillary Rheology

Background and purpose:
Extrusion-based 3D bioprinting offers a promising avenue for the fabrication of near-physiological tissue models. However, it remains a technical challenge to achieve reliable and reproducible printing since fundamental understanding of the causes of extrusion instabilities during bioprinting is still poor. Hydrogel printability is commonly assessed by rotational rheology (RR), which does not capture the flow profile of the extrusion process, resulting in poor reliability and predictability of the assessment, while visual assessment of filament morphological features is commonly performed after the bioprinting. Lack of reliable methodologies for faithful analysis of hydrogel extrusion affects material design, bio-ink development, cell viability, and 3D print quality, which further limits the translatability of results obtained from RR to real-life extrusion of these materials. These limitations impede the development and translation of such materials for biofabrication applications. We hypothesize that a faithful assessment of printability requires understanding the phenomena affecting bio-inks in the reservoir and the nozzle during the extrusion process. To this end, we employ principles of capillary rheology (CR), which characterizes material deformation and flow through capillaries, for quantitative assessment of bio-ink printability.
Methods:
We developed a CR system that enables real-time quantification of in situ bio-ink properties in a printing-like setup. The bio-ink flows through a capillary with integrated pressure and temperature sensors to measure bio-ink rheological properties, which are simultaneously supplemented by visual data. For these experiments, we selected model bio-inks based on Pluronic F-127 and gelatin methacrylate (GelMA). In addition, GelMA-based granular materials with unknown flow behavior were selected to further highlight the applicability of the CR-based method.
Results and conclusions:
Our results show a considerable discrepancy in key printability-related properties such as viscosity and shear-thinning for CR compared to RR. Besides, CR pressure data reveal nuanced flow dynamics throughout the extrusion process, which reflect material-dependent changes in extrusion uniformity. The effects of material properties such as viscoelasticity, temperature sensitivity, and shear-thinning are reflected in these pressure data. For example, the amplitude of local pressure fluctuations suggests material-dependent impairment in extrusion uniformity. These discrepancies are further accentuated when assessing GelMA-based granular materials. The RR demonstrates non-significantly differing shear-thinning behavior for all compositions of granular materials, but the CR reveals significantly higher local pressure fluctuation and a higher pressure requirement to extrude fully granular material compared to other compositions. Moreover, the CR temperature sensors show a dramatic temperature gradient throughout the bio-ink, which significantly affects bio-ink behavior. These discrepancies suggest that RR, due to its differences in process mechanics, cannot faithfully predict the material flow behavior under capillary extrusion, which leads to inaccurate data and information when translating to the extrusion process. These results underscore the importance of temperature-viscosity relations and bio-ink capillary flow behavior in extrusion-based bioprinting. Overall, CR provides accurate and detailed information on the extrudability of hydrogels and pinpoints extrusion-dependent phenomena in each stage of the printing course which cannot be captured with RR.
Our ongoing work will correlate CR and visual data to establish quantitative printability assessment criteria. Overall, our approach offers new fundamental insight into the rheological properties of the bio-inks during the extrusion process, which can considerably improve the translation of bio-inks and the optimization of 3D printing processes.