Slicing parameter optimization for 3D printing of biodegradable drug-eluting tracheal stents. (2nd July 2020)

• Record Type: Journal Article
• Authors: Feuerbach, Tim; Kock, Stefanie; Thommes, Markus
• Is Part Of: Pharmaceutical development and technology. Volume 25:Number 6(2020)
• Page Start: 650
• Page End: 658
• Publication Date: 2020-07-02
• Subjects: 3D printing -- fused deposition modeling -- stent -- slicing -- porosity -- tensile strength -- implant; Drug delivery systems -- Periodicals; Pharmaceutical technology -- Periodicals; Drugs -- Administration -- Research -- Periodicals; Drug Delivery Systems -- Periodicals; Pharmaceutical Preparations -- Periodicals; Technology, Pharmaceutical -- Periodicals; 615
• DOI: 10.1080/10837450.2020.1727921
• Languages: English
• ISSNs: 1083-7450

Abstract

Abstract: In 3D printing, the schematic representation of an object must be converted into machine commands. This process is called slicing. Depending on the slicing parameters, products with different properties are obtained. In this work, biodegradable drug-eluting tracheal stents consisting of a medical grade poly(lactic-co-glycolic acid) and a drug were printed by fused deposition modeling. A slicing parameter optimization method was proposed with the aim of obtaining a particularly low stent porosity and high mechanical strength while maintaining the stent dimensions, which is essential regarding patient-tailored implants. Depending on the three slicing parameters printing pattern, lateral strand distance and spatial fill, porosities of approximately 2–5% were obtained. The tensile strength was used as a measure for the mechanical strength of the implants and was found to be dependent on the porosity as well as the strand orientation relative to the load direction. Strand orientations in load direction yielded the highest tensile strengths of 40–46 MPa and the bonding between individual layers yielded the lowest tensile strengths of 20–24 MPa. In vitro dissolution tests of successfully printed stents were used to predict sustained release of the drug over several months.