2018
DOI: 10.1208/s12249-018-1176-z
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Virtual Prototyping and Parametric Design of 3D-Printed Tablets Based on the Solution of Inverse Problem

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Cited by 20 publications
(9 citation statements)
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“…Notably, the amount of the active ingredient conveyed in the cores was in all cases > of 98% with respect to the theoretical value calculated based on prototypes weight and composition. In agreement with literature data, the removal of the top and bottom layers and the infill reduction turned out essential for speeding up the liberation of the drug tracer from the printed cores, probably due to the impact of such parameters on porosity and area exposed to the aqueous medium [58][59][60][61][62][63]. With all the formulations, the best results were obtained by decreasing the infill to 50%, independent of the presence of an adjuvant in the formulation.…”
Section: Coresupporting
confidence: 86%
“…Notably, the amount of the active ingredient conveyed in the cores was in all cases > of 98% with respect to the theoretical value calculated based on prototypes weight and composition. In agreement with literature data, the removal of the top and bottom layers and the infill reduction turned out essential for speeding up the liberation of the drug tracer from the printed cores, probably due to the impact of such parameters on porosity and area exposed to the aqueous medium [58][59][60][61][62][63]. With all the formulations, the best results were obtained by decreasing the infill to 50%, independent of the presence of an adjuvant in the formulation.…”
Section: Coresupporting
confidence: 86%
“…By adjusting the porosity of the tablet, the drug release profile can be changed efficiently. The method correctly predicted the drug release rate for both single and multiple porosity tablets [ 112 ].…”
Section: Computational Approaches In Pharmaceutical 3d Printingmentioning
confidence: 99%
“…For example, Novák investigated the influence of varying infills and resulting tablet porosities on drug release using an ANN. This resulted in an in-silico design method of infill variations for 3D printed dosage geometries [ 48 ].…”
Section: Introductionmentioning
confidence: 99%