Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools

This study explores novel alginate–konjac glucomannan core–shell aerogel particles for drug delivery systems fabricated via air-assisted coaxial prilling. A systematic approach is needed for the optimization of this method due to the numerous processing variables involved. This study investigated th...

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Detalles Bibliográficos
Autores: Illanes Bordomás, Carlos, Landín Pérez, Mariana, García González, Carlos A.
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/45764
Acceso en línea:https://hdl.handle.net/10347/45764
Access Level:acceso abierto
Palabra clave:Aerogels
Porous particles
Konjac glucomannan
Alginate
Supercritical CO2
Artificial intelligence tools
Coated particles
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spelling Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence ToolsIllanes Bordomás, CarlosLandín Pérez, MarianaGarcía González, Carlos A.AerogelsPorous particlesKonjac glucomannanAlginateSupercritical CO2Artificial intelligence toolsCoated particlesThis study explores novel alginate–konjac glucomannan core–shell aerogel particles for drug delivery systems fabricated via air-assisted coaxial prilling. A systematic approach is needed for the optimization of this method due to the numerous processing variables involved. This study investigated the influence of six variables: alginate and konjac glucomannan concentrations, compressed airflow, liquid pump pressures, and nozzle configuration. A hybrid software using Artificial Neural Networks and genetic algorithms was used to model and optimize the hydrogel formation, achieving a 100% desirable solution. The optimal formulation identified resulted in particles displaying a log-normal size distribution (R2 = 0.967) with an average diameter of 1.57 mm. Supercritical CO2 drying yielded aerogels with macropores and mesopores and a high specific surface area (201 ± 10 m2/g). The loading of vancomycin hydrochloride (Van) or a dexamethasone base (DX) into the aerogel cores during the process was tested. The aerogels exhibited appropriate structural characteristics, and both drugs showed burst release profiles with ca. 80% release within 10 min for DX and medium-dependent release for Van. This study demonstrates the feasibility of producing konjac aerogel particles for delivery systems and the high potential of AI-driven optimization methods, highlighting the need for coating modifications to achieve the desired release profiles.MDPIUniversidade de Santiago de Compostela. Facultade de FarmaciaUniversidade de Santiago de Compostela. Instituto de Materiais (iMATUS)20252025-07-1120252025-07-11journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10347/45764reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostelainstname:Universidad de Santiago de Compostela (USC)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-120010RB-I00 INGENIERIA DE AEROGELES PARA APLICACIONES BIOMEDICAS AVANZADASAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2023-151340OB-I00 AVANCES EN AEROGELES PARA APLICACIONES BIOMEDICAS A TRAVES DE SOLUCIONES SOSTENIBLES Y HERRAMIENTAS DE INTELIGENCIA ARTIFICIALopen accesshttp://purl.org/coar/access_right/c_abf2© 2025 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/info:eu-repo/semantics/openAccessoai:minerva.usc.gal:10347/457642026-06-15T12:47:27Z
dc.title.none.fl_str_mv Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
title Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
spellingShingle Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
Illanes Bordomás, Carlos
Aerogels
Porous particles
Konjac glucomannan
Alginate
Supercritical CO2
Artificial intelligence tools
Coated particles
title_short Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
title_full Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
title_fullStr Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
title_full_unstemmed Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
title_sort Novel Core–Shell Aerogel Formulation for Drug Delivery Based on Alginate and Konjac Glucomannan: Rational Design Using Artificial Intelligence Tools
dc.creator.none.fl_str_mv Illanes Bordomás, Carlos
Landín Pérez, Mariana
García González, Carlos A.
author Illanes Bordomás, Carlos
author_facet Illanes Bordomás, Carlos
Landín Pérez, Mariana
García González, Carlos A.
author_role author
author2 Landín Pérez, Mariana
García González, Carlos A.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade de Santiago de Compostela. Facultade de Farmacia
Universidade de Santiago de Compostela. Instituto de Materiais (iMATUS)
dc.subject.none.fl_str_mv Aerogels
Porous particles
Konjac glucomannan
Alginate
Supercritical CO2
Artificial intelligence tools
Coated particles
topic Aerogels
Porous particles
Konjac glucomannan
Alginate
Supercritical CO2
Artificial intelligence tools
Coated particles
description This study explores novel alginate–konjac glucomannan core–shell aerogel particles for drug delivery systems fabricated via air-assisted coaxial prilling. A systematic approach is needed for the optimization of this method due to the numerous processing variables involved. This study investigated the influence of six variables: alginate and konjac glucomannan concentrations, compressed airflow, liquid pump pressures, and nozzle configuration. A hybrid software using Artificial Neural Networks and genetic algorithms was used to model and optimize the hydrogel formation, achieving a 100% desirable solution. The optimal formulation identified resulted in particles displaying a log-normal size distribution (R2 = 0.967) with an average diameter of 1.57 mm. Supercritical CO2 drying yielded aerogels with macropores and mesopores and a high specific surface area (201 ± 10 m2/g). The loading of vancomycin hydrochloride (Van) or a dexamethasone base (DX) into the aerogel cores during the process was tested. The aerogels exhibited appropriate structural characteristics, and both drugs showed burst release profiles with ca. 80% release within 10 min for DX and medium-dependent release for Van. This study demonstrates the feasibility of producing konjac aerogel particles for delivery systems and the high potential of AI-driven optimization methods, highlighting the need for coating modifications to achieve the desired release profiles.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-07-11
2025
2025-07-11
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10347/45764
url https://hdl.handle.net/10347/45764
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-120010RB-I00 INGENIERIA DE AEROGELES PARA APLICACIONES BIOMEDICAS AVANZADAS
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2023-151340OB-I00 AVANCES EN AEROGELES PARA APLICACIONES BIOMEDICAS A TRAVES DE SOLUCIONES SOSTENIBLES Y HERRAMIENTAS DE INTELIGENCIA ARTIFICIAL
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname:Universidad de Santiago de Compostela (USC)
instname_str Universidad de Santiago de Compostela (USC)
reponame_str Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
collection Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
repository.name.fl_str_mv
repository.mail.fl_str_mv
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