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The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds
The aim of these studies was to determine the miscibility of different API with lipid excipients to predict drug loading and encapsulation properties for the production of solid lipid nanoparticles and nanostructured lipid carriers. Five API exhibiting different physicochemical characteristics, viz....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078564/ https://www.ncbi.nlm.nih.gov/pubmed/32194332 http://dx.doi.org/10.1016/j.jsps.2020.01.010 |
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author | Makoni, Pedzisai A. Ranchhod, Janeeta WaKasongo, Kasongo Khamanga, Sandile M. Walker, Roderick B. |
author_facet | Makoni, Pedzisai A. Ranchhod, Janeeta WaKasongo, Kasongo Khamanga, Sandile M. Walker, Roderick B. |
author_sort | Makoni, Pedzisai A. |
collection | PubMed |
description | The aim of these studies was to determine the miscibility of different API with lipid excipients to predict drug loading and encapsulation properties for the production of solid lipid nanoparticles and nanostructured lipid carriers. Five API exhibiting different physicochemical characteristics, viz., clarithromycin, efavirenz, minocycline hydrochloride, mometasone furoate, and didanosine were used and six solid lipids in addition to four liquid lipids were investigated. Determination of solid and liquid lipids with the best solubilization potential for each API were performed using a traditional shake-flask method and/or a modification thereof. Hansen solubility parameters of the API and different solid and liquid lipids were estimated from their chemical structure using Hiroshi Yamamoto’s molecular breaking method of Hansen Solubility Parameters in Practice software. Experimental results were in close agreement with solubility parameter predictions for systems with ΔδT < 4.0 MPa(1/2). A combination of Hansen solubility parameters with experimental drug-lipid miscibility tests can be successfully applied to predict lipids with the best solubilizing potential for different API prior to manufacture of solid lipid nanoparticles and nanostructured lipid carriers. |
format | Online Article Text |
id | pubmed-7078564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70785642020-03-19 The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds Makoni, Pedzisai A. Ranchhod, Janeeta WaKasongo, Kasongo Khamanga, Sandile M. Walker, Roderick B. Saudi Pharm J Article The aim of these studies was to determine the miscibility of different API with lipid excipients to predict drug loading and encapsulation properties for the production of solid lipid nanoparticles and nanostructured lipid carriers. Five API exhibiting different physicochemical characteristics, viz., clarithromycin, efavirenz, minocycline hydrochloride, mometasone furoate, and didanosine were used and six solid lipids in addition to four liquid lipids were investigated. Determination of solid and liquid lipids with the best solubilization potential for each API were performed using a traditional shake-flask method and/or a modification thereof. Hansen solubility parameters of the API and different solid and liquid lipids were estimated from their chemical structure using Hiroshi Yamamoto’s molecular breaking method of Hansen Solubility Parameters in Practice software. Experimental results were in close agreement with solubility parameter predictions for systems with ΔδT < 4.0 MPa(1/2). A combination of Hansen solubility parameters with experimental drug-lipid miscibility tests can be successfully applied to predict lipids with the best solubilizing potential for different API prior to manufacture of solid lipid nanoparticles and nanostructured lipid carriers. Elsevier 2020-03 2020-01-31 /pmc/articles/PMC7078564/ /pubmed/32194332 http://dx.doi.org/10.1016/j.jsps.2020.01.010 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Makoni, Pedzisai A. Ranchhod, Janeeta WaKasongo, Kasongo Khamanga, Sandile M. Walker, Roderick B. The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title | The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title_full | The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title_fullStr | The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title_full_unstemmed | The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title_short | The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
title_sort | use of quantitative analysis and hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078564/ https://www.ncbi.nlm.nih.gov/pubmed/32194332 http://dx.doi.org/10.1016/j.jsps.2020.01.010 |
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