Paracetamol printlets were prepared via hot-melt extrusion process and fused deposition modelling, using two types of backbone polymers. Polycaprolactone (PCL) and Polyethylene oxides (PEO) 100 K and 200 K were used, while Arabic gum was used as a plasticizer to facilitate the material flow and Gelucire® 44/14 as an enhancer of drug release. Different drug/polymer ratios were prepared. Extrusion temperature was adjusted according to the mixture/polymer types. It was possible to produce filaments with maximum of 60% w/w of drug. Mechanical properties of filaments were evaluated using three-point bend test, while obtained parameters were modelled using decision tree as a data mining method. Correlation between maximum displacement, maximum force and printability was obtained with accuracy of 84.85% and can be a useful tool for predicting printability of filaments. This study briefly demonstrated that backbone polymer in formulation plays crucial role in obtaining FDM printlets with desired properties. PEO-based filaments were more prone to be clogged in printcore, but their printlets showed much faster drug release. Drug release from all printlets was prolonged: from 50% in 8 h (PCL), to complete release in 4 h (PEO). Paracetamol release kinetics was guided by anomalous transport, attributed to the diffusion and erosion process.
Keywords: 3D printing; Decision tree model; Extended release; Fused deposition modelling; Printability; Three-point bend test.
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