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Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms

Although not readily accessible yet to many community and hospital pharmacists, fuse deposition modelling (FDM) is a 3D printing technique that can be used to create a 3D pharmaceutical dosage form by employing drug loaded filaments extruded via a nozzle, melted and deposited layer by layer. FDM req...

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Autores principales: Cerda, Jose R., Arifi, Talaya, Ayyoubi, Sejad, Knief, Peter, Ballesteros, Maria Paloma, Keeble, William, Barbu, Eugen, Healy, Anne Marie, Lalatsa, Aikaterini, Serrano, Dolores R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238181/
https://www.ncbi.nlm.nih.gov/pubmed/32290400
http://dx.doi.org/10.3390/pharmaceutics12040345
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author Cerda, Jose R.
Arifi, Talaya
Ayyoubi, Sejad
Knief, Peter
Ballesteros, Maria Paloma
Keeble, William
Barbu, Eugen
Healy, Anne Marie
Lalatsa, Aikaterini
Serrano, Dolores R.
author_facet Cerda, Jose R.
Arifi, Talaya
Ayyoubi, Sejad
Knief, Peter
Ballesteros, Maria Paloma
Keeble, William
Barbu, Eugen
Healy, Anne Marie
Lalatsa, Aikaterini
Serrano, Dolores R.
author_sort Cerda, Jose R.
collection PubMed
description Although not readily accessible yet to many community and hospital pharmacists, fuse deposition modelling (FDM) is a 3D printing technique that can be used to create a 3D pharmaceutical dosage form by employing drug loaded filaments extruded via a nozzle, melted and deposited layer by layer. FDM requires printable filaments, which are commonly manufactured by hot melt extrusion, and identifying a suitable extrudable drug-excipient mixture can sometimes be challenging. We propose here the use of passive diffusion as an accessible loading method for filaments that can be printed using FDM technology to allow for the fabrication of oral personalised medicines in clinical settings. Utilising Hansen Solubility Parameters (HSP) and the concept of HSP distances (Ra) between drug, solvent, and filament, we have developed a facile pre-screening tool for the selection of the optimal combination that can provide a high drug loading (a high solvent-drug Ra, >10, and an intermediate solvent–filament Ra value, ~10). We have identified that other parameters such as surface roughness and stiffness also play a key role in enhancing passive diffusion of the drug into the filaments. A predictive model for drug loading was developed based on Support Vector Machine (SVM) regression and indicated a strong correlation between both Ra and filament stiffness and the diffusion capacity of a model BCS Class II drug, nifedipine (NFD), into the filaments. A drug loading, close to 3% w/w, was achieved. 3D printed tablets prepared using a PVA-derived filament (Hydrosupport, 3D Fuel) showed promising characteristics in terms of dissolution (with a sustained release over 24 h) and predicted chemical stability (>3 years at 25 °C/60% relative humidity), similar to commercially available NFD oral dosage forms. We believe FDM coupled with passive diffusion could be implemented easily in clinical settings for the manufacture of tailored personalised medicines, which can be stored over long periods of time (similar to industrially manufactured solid dosage forms).
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spelling pubmed-72381812020-05-28 Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms Cerda, Jose R. Arifi, Talaya Ayyoubi, Sejad Knief, Peter Ballesteros, Maria Paloma Keeble, William Barbu, Eugen Healy, Anne Marie Lalatsa, Aikaterini Serrano, Dolores R. Pharmaceutics Article Although not readily accessible yet to many community and hospital pharmacists, fuse deposition modelling (FDM) is a 3D printing technique that can be used to create a 3D pharmaceutical dosage form by employing drug loaded filaments extruded via a nozzle, melted and deposited layer by layer. FDM requires printable filaments, which are commonly manufactured by hot melt extrusion, and identifying a suitable extrudable drug-excipient mixture can sometimes be challenging. We propose here the use of passive diffusion as an accessible loading method for filaments that can be printed using FDM technology to allow for the fabrication of oral personalised medicines in clinical settings. Utilising Hansen Solubility Parameters (HSP) and the concept of HSP distances (Ra) between drug, solvent, and filament, we have developed a facile pre-screening tool for the selection of the optimal combination that can provide a high drug loading (a high solvent-drug Ra, >10, and an intermediate solvent–filament Ra value, ~10). We have identified that other parameters such as surface roughness and stiffness also play a key role in enhancing passive diffusion of the drug into the filaments. A predictive model for drug loading was developed based on Support Vector Machine (SVM) regression and indicated a strong correlation between both Ra and filament stiffness and the diffusion capacity of a model BCS Class II drug, nifedipine (NFD), into the filaments. A drug loading, close to 3% w/w, was achieved. 3D printed tablets prepared using a PVA-derived filament (Hydrosupport, 3D Fuel) showed promising characteristics in terms of dissolution (with a sustained release over 24 h) and predicted chemical stability (>3 years at 25 °C/60% relative humidity), similar to commercially available NFD oral dosage forms. We believe FDM coupled with passive diffusion could be implemented easily in clinical settings for the manufacture of tailored personalised medicines, which can be stored over long periods of time (similar to industrially manufactured solid dosage forms). MDPI 2020-04-11 /pmc/articles/PMC7238181/ /pubmed/32290400 http://dx.doi.org/10.3390/pharmaceutics12040345 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cerda, Jose R.
Arifi, Talaya
Ayyoubi, Sejad
Knief, Peter
Ballesteros, Maria Paloma
Keeble, William
Barbu, Eugen
Healy, Anne Marie
Lalatsa, Aikaterini
Serrano, Dolores R.
Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title_full Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title_fullStr Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title_full_unstemmed Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title_short Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms
title_sort personalised 3d printed medicines: optimising material properties for successful passive diffusion loading of filaments for fused deposition modelling of solid dosage forms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238181/
https://www.ncbi.nlm.nih.gov/pubmed/32290400
http://dx.doi.org/10.3390/pharmaceutics12040345
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