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dc.contributor.authorCerda, Jose R
dc.contributor.authorArifi, Talaya
dc.contributor.authorAyyoubi, Sejad
dc.contributor.authorKnief, Peter
dc.contributor.authorBallesteros, Maria Paloma
dc.contributor.authorKeeble, William
dc.contributor.authorBarbu, Eugen
dc.contributor.authorHealy, Anne Marie
dc.contributor.authorLalatsa, Aikaterini
dc.contributor.authorSerrano, Dolores R
dc.date.accessioned2020-09-23T10:09:59Z
dc.date.available2020-09-23T10:09:59Z
dc.date.issued2020-04-11
dc.identifier.issn1999-4923
dc.identifier.pmid32290400
dc.identifier.doi10.3390/pharmaceutics12040345
dc.identifier.urihttp://hdl.handle.net/10147/628329
dc.descriptionAlthough 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).en_US
dc.language.isoenen_US
dc.subject3D printingen_US
dc.subjectHansen Solubility Parametersen_US
dc.subjectPLAen_US
dc.subjectPVAen_US
dc.subjectfilamentsen_US
dc.subjectfused deposition modelling (FDM)en_US
dc.subjectnifedipineen_US
dc.subjectpassive diffusionen_US
dc.titlePersonalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms.en_US
dc.typeArticleen_US
dc.identifier.journalPharmaceuticsen_US
dc.source.journaltitlePharmaceutics
dc.source.volume12
dc.source.issue4
refterms.dateFOA2020-09-23T10:10:00Z
dc.source.countryIreland
dc.source.countryIreland
dc.source.countrySwitzerland


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