Automated and dynamic extrusion pressure adjustment based on real-time flow rate measurements for precise ink dispensing in 3D bioprinting

Extrusion-based printing relying on pneumatic dispensing systems is the most widely employed tool in bioprinting. However, standardized and reliable methods for process development, monitoring and control are still not established. Suitable printing parameters are often determined in a trial-and-error approach and neither process monitoring nor real-time adjustments of extrusion pressure to environmental and process-related changes are commonly employed. The present study evaluates an approach to introduce flow rate as a main process parameter to monitor and control extrusion-based bioprinting. An experimental setup was established by integrating a liquid flow meter between the cartridge and nozzle of a pneumatically driven bioprinter to measure the actual flow of dispensed ink in real-time. The measured flow rate was fed to a Python-based software tool implementing a proportional-integral-derivative (PID) feedback loop that automatically and dynamically adapted the extrusion pressure of the bioprinter to meet a specified target flow rate. The performance of the employed experimental setup was evaluated with three different model inks in three application examples. a) Continuous dispensing: Several runs of continuous dispensing showed that the PID-based pressure control was able to generate a steady flow rate more consistently and precisely than constant pressure settings. b) Adaptation to ink inhomogeneities: Deliberately created ink inhomogeneities were successfully compensated for by real-time pressure adjustments which profoundly enhanced the printing quality compared to printing without adaptive pressure. c) Process transfer to other nozzle types: Experiments with different nozzle types demonstrated the potential of the established setup to facilitate and accelerate process transfer and development. The present study provides an alternative approach for process design, monitoring and control by introducing flow rate as a main process parameter. We propose bioprinting processes to be based on flow rate specifications instead of constant pressure settings. This approach has the potential to save time by avoiding tedious parameter screenings and to introduce an active, real-time control over the printing process. Subjective influences by individual users during process development can be reduced and the process transfer between different devices and experimental setups can be facilitated and accelerated.