Image analysis as PAT-Tool for use in extrusion-based bioprinting

  • chair:

    Strauß, S. / Meutelet, R. / Radosevic, L. / Gretzinger, S. / Hubbuch, J. (2020)

  • place:

    Bioprinting, 2021, 21, e00112


  • Date: November 2020
  • Abstract

    The technology of bioprinting is arousing a growing interest in biopharmaceutical research and industry. In order to accelerate process development in the field of bioprinting, image-based analysis methods are non-invasive, time- and cost-saving tools which are useable for printer characterization, bioink printability evaluation, and process optimization. Image processing can also be used for the study of reproducibility, since reliable production is important in the transition from research to industrial application, and more precisely to clinical studies. This study revolves around the establishment of an automated and image-based line analysis method for bioprinting applications which enables an easy comparison of 3D-printed lines. Diverse rheological properties of bioinks and the printing process affect the geometry of the resulting object. The line represents a simple geometry, where the influence of the rheological properties and printing parameters is directly apparent. Therefore, a method for line analysis was developed on the basis of image recognition. At first, the method is tested for several substances such as Nivea®, pure and colored Kolliphor solutions, and two commercially available hydrogel formulations which can be used as bioinks. These are Biogelx™-ink-RGD by Biogelx and Cellink® Bioink by Cellink. The examination of limitations showed that transparent materials such as Kolliphor-based solutions cannot be analyzed with the developed method whereas opaque materials such as Nivea® and both bioinks can be analyzed. In the course of process characterization, the method was used to investigate the shrinkage behavior for both bionks. With the help of the line analysis tool, a shrinkage behavior of both bioinks was demonstrated and thus, process time could be identified as a critical process parameter.