ABSTRACT
Organs-on-a-chip (OoCs) have proven to mimic the basic physiological behavior of organs and the influence of therapeutics on them in greater detail than conventional models, resulting in enormous projected market growth rates. However, the breakthrough to profitable commercialization of that technology has not yet been achieved, partly because the production process chain is characterized by a high proportion of manual laboratory work. The present work addresses this point. Utilizing affordable components, a demonstrator was developed that can be integrated into an existing 3D-bioprinting system and enables the automated production of perfusion-ready OoC devices starting from pre-fabricated injection-molded microfluidic chips. To this end, a corresponding process chain was first defined, and an expandable, configurable algorithm was developed and validated in the form of a finite state machine (FSM). This algorithm controls a modified 4-axis robot arm that covers the steps upstream and downstream of the printing process in the manufacturing process and achieves success rates of up to 100 %. A virtual interface between the robot and printer enables mutual communication and full integration of the algorithm into the process chain. Steps that pose a challenge for the automation of the process chain and appropriate countermeasures and optimizations were identified. This lays the foundation for scaling and standardizing the automated production of OoCs.
ABSTRACT
3D bioprinting possesses the potential to revolutionize contemporary methodologies for fabricating tissue models employed in pharmaceutical research and experimental investigations. This is enhanced by combining bioprinting with advanced organs-on-a-chip (OOCs), which includes a complex arrangement of multiple cell types representing organ-specific cells, connective tissue, and vasculature. However, both OOCs and bioprinting so far demand a high degree of manual intervention, thereby impeding efficiency and inhibiting scalability to meet technological requirements. Through the combination of drop-on-demand bioprinting with robotic handling of microfluidic chips, a print procedure is achieved that is proficient in managing three distinct tissue models on a chip within only a minute, as well as capable of consecutively processing numerous OOCs without manual intervention. This process rests upon the development of a post-printing sealable microfluidic chip, that is compatible with different types of 3D-bioprinters and easily connected to a perfusion system. The capabilities of the automized bioprint process are showcased through the creation of a multicellular and vascularized liver carcinoma model on the chip. The process achieves full vascularization and stable microvascular network formation over 14 days of culture time, with pronounced spheroidal cell growth and albumin secretion of HepG2 serving as a representative cell model.
Subject(s)
Bioprinting , Lab-On-A-Chip Devices , Printing, Three-Dimensional , Tissue Engineering , Humans , Bioprinting/methods , Tissue Engineering/methods , Neovascularization, Physiologic , Hep G2 CellsABSTRACT
Biofabrication, specifically 3D-Bioprinting, has the potential to disruptively impact a wide range of future technological developments to improve human well-being. Organs-on-Chips could enable animal-free and individualized drug development, printed organs may help to overcome non-treatable diseases as well as deficiencies in donor organs and cultured meat may solve a worldwide environmental threat in factory farming. A high degree of manual labor in the laboratory in combination with little trained personnel leads to high costs and is along with strict regulations currently often a hindrance to the commercialization of technologies that have already been well researched. This paper therefore illustrates current developments in process automation in 3D-Bioprinting and provides a perspective on how the use of proven and new automation solutions can help to overcome regulatory and technological hurdles to achieve an economically scalable production.