Size-Tailored Design of Highly Monodisperse Lipid Nanocapsules for Drug Delivery
dc.contributor.author | Aparicio Blanco, Juan | |
dc.contributor.author | Sebastián, Víctor | |
dc.contributor.author | Rodríguez-Amaro, Miguel | |
dc.contributor.author | García-Díaz, Héctor C. | |
dc.contributor.author | Torres Suárez, Ana Isabel | |
dc.date.accessioned | 2024-01-31T12:25:49Z | |
dc.date.available | 2024-01-31T12:25:49Z | |
dc.date.issued | 2019-06-01 | |
dc.description.abstract | The empirical development of nanocarriers has unfortunately led to high attrition rates in clinical trials. This underpins the importance of the rational design of nanomedicines to achieve efficient disease-driven therapies. Since particle size certainly influences in vivo behaviour, rational disease-driven colloid design can only be achieved by determining the parameters that accurately control their size distribution. To this end, we have thoroughly revisited the parameters that drive the phase-inversion temperature nanoemulsification method to obtain kinetically stable and monodisperse lipid nanocapsules. Notably, we have evidenced that the major parameter driving nanocapsule formation is the oily phase/surfactant ratio and consequently, we have established a linear univariate mathematical model that predicts the particle size distribution for various oily phase-surfactant combinations (R 2 > 0 99). Furthermore, we have observed that the difference between the HLB values of the surfactants and the triglycerides utilized as oily phase correlates with the steepness of the slope of the linear mathematical model. This model will bring the implementation of size-tailored lipid drug carriers determined by pathophysiological features a step closer. Importantly, this model pioneeringly fits all data available in the literature on size distribution of colloids prepared by low-energy methods and that were originally evaluated following other parameters. Moreover, the nanocapsules have been obtained following a single-step process, with the ensuing potential for a future scale-up in an energetically-efficient manner. These findings will eventually enable nanomedicines to be obtained "on-demand" to meet disease-driven criteria in terms of particle size and will also increase their chances of success. | |
dc.description.department | Depto. de Farmacia Galénica y Tecnología Alimentaria | |
dc.description.faculty | Fac. de Farmacia | |
dc.description.refereed | TRUE | |
dc.description.sponsorship | Universidad Complutense de Madrid | |
dc.description.sponsorship | Banco Santander | |
dc.description.sponsorship | Ministerio de Educación, Cultura y Deporte(España) | |
dc.description.status | pub | |
dc.identifier.doi | 10.1166/jbn.2019.2765 | |
dc.identifier.issn | 1550-7033 | |
dc.identifier.officialurl | https://doi.org/10.1166/jbn.2019.2765 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/97114 | |
dc.issue.number | 6 | |
dc.journal.title | Journal of Biomedical Nanotechnology | |
dc.language.iso | eng | |
dc.page.final | 1161 | |
dc.page.initial | 1149 | |
dc.publisher | American Scientific Publishers | |
dc.relation.projectID | info:eu-repo/grantAgreement/PR75/18-21606 | |
dc.relation.projectID | info:eu-repo/grantAgreement/FPU13/02325 | |
dc.rights.accessRights | restricted access | |
dc.subject.keyword | Phase Inversion Temperature | |
dc.subject.keyword | Low-Energy Nanoemulsification Method | |
dc.subject.keyword | Lipid Drug Carriers | |
dc.subject.keyword | Nanomedicine | |
dc.subject.keyword | Customized Colloid Design | |
dc.subject.keyword | Univariate Linear Model | |
dc.subject.ucm | Tecnología farmaceútica | |
dc.subject.unesco | 3209.08 Preparación de Medicamentos | |
dc.title | Size-Tailored Design of Highly Monodisperse Lipid Nanocapsules for Drug Delivery | |
dc.type | journal article | |
dc.type.hasVersion | VoR | |
dc.volume.number | 15 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 4cb1a1cd-ad04-41d8-b28d-ed9b8dde4d92 | |
relation.isAuthorOfPublication | a7294851-3d9d-4fc2-98cc-80bf8b256236 | |
relation.isAuthorOfPublication.latestForDiscovery | 4cb1a1cd-ad04-41d8-b28d-ed9b8dde4d92 |
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