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QbD guided development of immediate release FDM-3D printed tablets with customizable API doses

[Display omitted] •Proper tablet designs enable fast API release from PVA-based 3D printed structures.•Tablet size scaling guided by predictive models allows API dose customization.•The API release from honeycomb designs is less affected by varied printing settings.•Personalized medications are obta...

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Bibliographic Details
Published in:International journal of pharmaceutics 2022-02, Vol.613, p.121411-121411, Article 121411
Main Authors: Crișan, Andrea Gabriela, Iurian, Sonia, Porfire, Alina, Rus, Lucia Maria, Bogdan, Cătălina, Casian, Tibor, Lucacel, Raluca Ciceo, Turza, Alexandru, Porav, Sebastian, Tomuță, Ioan
Format: Article
Language:English
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Summary:[Display omitted] •Proper tablet designs enable fast API release from PVA-based 3D printed structures.•Tablet size scaling guided by predictive models allows API dose customization.•The API release from honeycomb designs is less affected by varied printing settings.•Personalized medications are obtainable via rational choice of printing parameters. The objective of this work was to develop a fused deposition modeling (FDM) 3D printed immediate release (IR) tablet with flexibility in adjusting the dose of the active pharmaceutical ingredient (API) by scaling the size of the dosage form and appropriate drug release profile steadiness to the variation of dimensions or thickness of the deposited layers throughout the printing process. Polyvinyl alcohol-based filaments with elevated API content (50% w/w) were prepared by hot melt extrusion (HME), through systematic screening of polymeric formulations with different drug loadings, and their printability was evaluated by means of mechanical characterization. For the tablet fabrication step by 3D printing (3DP), the Quality by Design (QbD) approach was implemented by employing risk management strategies and Design of Experiments (DoE). The effects of the tablet design, tablet size and the layer height settings on the drug release and the API content were investigated. Between the two proposed original tablet architectures, the honeycomb configuration was found to be a suitable candidate for the preparation of IR dosage forms with readily customizable API doses. Also, a predictive model was obtained, which assists the optimization of variables involved in the printing phase and thereby facilitates the tailoring process.
ISSN:0378-5173
1873-3476
DOI:10.1016/j.ijpharm.2021.121411