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dc.contributor.authorLópez Iglesias, Clara
dc.contributor.authorLópez Iglesias, Enriqueta
dc.contributor.authorFernández Pérez, Josefa
dc.contributor.authorLandín Pérez, Mariana
dc.contributor.authorGarcía González, Carlos Alberto
dc.date.accessioned2020-12-17T13:05:40Z
dc.date.available2020-12-17T13:05:40Z
dc.date.issued2020
dc.identifier.citationLópez-Iglesias, C.; López, E.R.; Fernández, J.; Landin, M.; García-González, C.A. Modeling of the Production of Lipid Microparticles Using PGSS® Technique. Molecules 2020, 25, 4927
dc.identifier.urihttp://hdl.handle.net/10347/24069
dc.description.abstractSolid lipid microparticles (SLMPs) are attractive carriers as delivery systems as they are stable, easy to manufacture and can provide controlled release of bioactive agents and increase their efficacy and/or safety. Particles from Gas-Saturated Solutions (PGSS®) technique is a solvent-free technology to produce SLMPs, which involves the use of supercritical CO2 (scCO2) at mild pressures and temperatures for the melting of lipids and atomization into particles. The determination of the key processing variables is crucial in PGSS® technique to obtain reliable and reproducible microparticles, therefore the modelling of SLMPs production process and variables control are of great interest to obtain quality therapeutic systems. In this work, the melting point depression of a commercial lipid (glyceryl monostearate, GMS) under compressed CO2 was studied using view cell experiments. Based on an unconstrained D-optimal design for three variables (nozzle diameter, temperature and pressure), SLMPs were produced using the PGSS® technique. The yield of production was registered and the particles characterized in terms of particle size distribution. Variable modeling was carried out using artificial neural networks and fuzzy logic integrated into neurofuzzy software. Modeling results highlight the main effect of temperature to tune the mean diameter SLMPs, whereas the pressure-nozzle diameter interaction is the main responsible in the SLMPs size distribution and in the PGSS® production yield
dc.description.sponsorshipThis work was supported by Xunta de Galicia [ED431F 2016/010, ED431C 2020/17 & GRC ED431C 2020/10], MCIUN [RTI2018-094131-A-I00], Agrupación Estratégica de Materiales [AeMAT- BIOMEDCO2, ED431E 2018/08], Agencia Estatal de Investigación [AEI] and FEDER funds. C.A.G.-G. acknowledges to MINECO for a Ramón y Cajal Fellowship [RYC2014-15239]. Work carried out in the frame of the COST Action CA18224 (GREENERING) and funded by the European Commission
dc.language.isoeng
dc.publisherMDPI
dc.rights© 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/)
dc.rightsAtribución 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectLipid microparticles
dc.subjectPGSS®
dc.subjectSupercritical CO2
dc.subjectModeling
dc.subjectSolvent-free technology
dc.titleModeling of the Production of Lipid Microparticles Using PGSS® Technique
dc.typeinfo:eu-repo/semantics/article
dc.identifier.DOI10.3390/molecules25214927
dc.relation.publisherversionhttps://doi.org/10.3390/molecules25214927
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.e-issn1420-3049
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Farmacoloxía, Farmacia e Tecnoloxía Farmacéutica
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Física Aplicada
dc.description.peerreviewedSI


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© 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/)
Except where otherwise noted, this item's license is described as  © 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/)





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