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Tissue Engineering

Tissue Engineering - Poster Session B

Poster K18 - Developing a Dataset of Printability Assessments Under Various Extrusion Bioprint Conditions

Thursday, October 24, 2024
2:45 PM – 3:45 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Extrusion based bioprinting is an advancing manufacturing technique in tissue engineering, particularly for the fabrication of intricate tissue constructs. Improving the printability of bioinks, specifically the structural fidelity and print accuracy, remains a significant challenge for researchers. This presents an urgent and worthwhile investigation, given that manual determination of printing parameters is a time consuming and resource intensive trial and error process. There is a pressing need for more innovative and effective methods to optimize printability. The overarching goal for this project aims to develop and validate a dataset for training machine learning algorithms capable of efficiently estimating printing parameters. This investigation has the potential to transform biotechnology applications in tissue engineering and healthcare.

Materials and

Methods:  An open-source extrusion print parameter dataset was used to select conditions for printability assessment. We focused on the five parameters of extrusion temperature, pressure, print speed, nozzle shape (conical vs. cylindrical), and nozzle size. The dataset was preprocessed using Python’s scikit-learn package such that a) units were converted to those consistent with our 6 degree-of-freedom bioprinter (BioAssemblyBot 400; Advanced Solutions), and b) missing information was imputed using a K-nearest neighbors approach (K=3). The dataset was filtered down to include only 5% and 10% wt./vol gelatin methacrylate (GelMA) bioinks, a popular extrudable hydrogel with excellent cytocompatibility. The printability assessment used was the filament collapse test, which is a measure of filament strength and ability to bridge gaps. Images of each test were captured on an internet protocol (IP) camera (UEyeCockpit, IDS Imaging) connected to the bioprinter. Within an image analysis software (ImageJ, NIH), we captured the correlation of half the gap distance, L, and the deflection angle at the point where the filament and pillar meet, Θ, which represent well-validated measures of the strength and structural integrity of the bio-ink. At the time of printing each condition, environmental conditions of ambient temperature, ambient pressure, relative humidity, and concentration of volatile organic compounds were also captured.

Results, Conclusions, and Discussions: We performed printability assessments under 18 different print conditions. Smaller Θ's created by the bio-ink indicated stronger and more successful prints. Bioinks that did not create a bridge from pillar to pillar, were considered over-gelatinated and prescribed a maximum deflection angle of 90⁰, the worst possible score. All the angles created by each of the different length gaps of the filament collapse test were plotted. Despite all prints being represented in a repository of conditions utilized in peer-reviewed literature, the printability of most of the bio-inks was not ideal. We take this to indicate that printability is not solely influenced by well-described properties of print conditions or bioink viscoelastic properties, but also by external factors such as the environmental conditions at the time of printing. Further analysis is needed to better characterize the influence of environmental conditions such as humidity, room temperature, and pressure on the resultant printability. As part of our future work, we endeavor to employ multifaceted tests on extrusion bioink printability, such as print accuracy and line tests. Furthermore, we aim to adjust our design of experiments to account for human-decision maker’s optimization process towards improving printability. Finally, we hope to consolidate a repository of data allowing for accurate automated printability estimations without the need for manual tuning through serial trial-and-error printability assessments. This study and future research have the potential to improve the practice of bioprinting as a manufacturing technique within the field of tissue engineering and regenerative medicine.

Acknowledgements (Optional):