Quantitative optimization of solid freeform deposition of aqueous hydrogels

Many soft tissues exhibit complex anatomical geometry that is challenging to replicate for regenerative medicine applications. Solid freeform fabrication (SFF) has emerged as an attractive approach for creating 3D tissues, but a detailed understanding of how specific fabrication parameters affect accuracy and viability has not been established to date. In this study, we evaluate the effects of printing parameters of the Fab@Home 3D printing system on accuracy using alginate, photocrosslinkable polyethylene-glycol diacrylate (PEG-DA) and gelatin as commonly used model hydrogel materials. Print accuracy and resolution along the length, width and height were determined based on quantitative image analysis. The effects of extrusion parameters on cell viability were assessed using porcine aortic valve interstitial cells (PAVIC) as a model cell type. We observed that pressure, pathheight and pathspace all significantly affected print accuracy and resolution. Printing conditions did not affect PAVIC viability within the ranges applied. We predicted that optimal pressure, pathheight and pathspace values would be increased linearly with increasing nozzle diameter, and we confirmed that the predicted values generate accurate 3D geometries while poorly chosen parameters yield inaccurate, unpredictable geometries. This systematic optimization strategy therefore improves the accuracy of 3D printing platforms for biofabrication and tissue engineering applications.