Preparation of 3D printed metoprolol tartrate chewable tablets and optimization of printing process / 药学学报

With the growing demand of personalized medicine for children, it is especially important to develop medicines for children. In this study, using metoprolol tartrate as model drug, we developed 3D printed chewable tablets suitable for children with automated dosage distribution using semi-solid extruded (SSE) 3D printing technology. Based on the quality by design concept, this study prepared a semi-solid material with good printability using gelatin as the substrate, constructed 3D models and printed tablets with the aid of computer-aided design. The printing parameters were optimized and determined as follows: print temperature of 35-37 ℃, print speed of 25 mm·s-1, fill rate of 15%, and number of outer profile layers of 2. Subsequently, the printing process and the quality uniformity of the tablets were verified, and a linear relationship between the dose and the number of model layers was obtained. Finally, 3D printed chewable tablets were superior in terms of appearance, dose accuracy and compliance compared with traditional split-dose commercially available tablets. In this study, 3D printed metoprolol tartrate chewable tablets with good performance were successfully prepared to address the personalized medication needs of pediatric patients.

Optimization of process parameters of 3D printed clozapine dispersive tablets and establishment of personalized dose model / 药学学报

This study aims to establish the design space of the key processes for drop-on-powder 3D printing based on design of experiment (DoE). By utilizing Minitab, an experimental scheme with three factors, two levels and three center points was designed to analyze the factors that significantly affected the tablet quality attributes. Furthermore, the factor interactions were analyzed using Minitab. subsequently, the computer aided drafting (CAD) software was used to adjust the model volume with fixed radius/height ratio (r/h = 1.25) and establish a linear regression equation between model volume and dose. As a result, the drug dose could be controlled in a flexible manner. The finally determined process parameters were: ink-jet level is 12, layer thickness is 150 μm, and the X-axis printing head speed of 635 mm·s-1. Regression equation between drug content (y) and model volume (x) was y = 0.062 x - 0.582 7 (R2 = 0.999 9) showing good linear relationship. This indicated that robust and feasible process parameters were obtained through DoE, and the preparation of personalized-dose tablets was realized with good reproducibility.