A Newly Validated HPLC-DAD Method for the Determination of Ricinoleic Acid (RA) in PLGA Nanocapsules.

PLGA nanocapsules castor oil high-performance liquid chromatography ricinoleic acid (RA) validation

Journal

Pharmaceuticals (Basel, Switzerland)
ISSN: 1424-8247
Titre abrégé: Pharmaceuticals (Basel)
Pays: Switzerland
ID NLM: 101238453

Informations de publication

Date de publication:
17 Sep 2024
Historique:
received: 10 07 2024
revised: 05 08 2024
accepted: 08 08 2024
medline: 28 9 2024
pubmed: 28 9 2024
entrez: 28 9 2024
Statut: epublish

Résumé

The assessment of ricinoleic acid (RA) incorporated into polymeric nanoparticles is a challenge that has not yet been explored. This bioactive compound, the main component of castor oil, has attracted attention in the pharmaceutical field for its valuable anti-inflammatory, antifungal, and antimicrobial properties. This work aims to develop a new and simple analytical method using high-performance liquid chromatography with diode-array detection (HPLC-DAD) for the identification and quantification of ricinoleic acid, with potential applicability in several other complex systems. The method was validated through analytical parameters, such as linearity, limit of detection and quantification, accuracy, precision, selectivity, and robustness. The physicochemical properties of the nanocapsules were characterized by dynamic light scattering (DLS) to determine their hydrodynamic mean diameter, polydispersity index (PDI), and zeta potential (ZP), via transmission electron microscopy (TEM) and quantifying the encapsulation efficiency. The proposed analytical method utilized a mobile phase consisting of a 65:35 ratio of acetonitrile to water, acidified with 1.5% phosphoric acid. It successfully depicted a symmetric peak of ricinoleic acid (retention time of 7.5 min) for both the standard and the RA present in the polymeric nanoparticles, enabling the quantification of the drug loaded into the nanocapsules. The nanocapsules containing ricinoleic acid (RA) exhibited an approximate size ranging from 309 nm to 441 nm, a PDI lower than 0.2, ζ values of approximately -30 mV, and high encapsulation efficiency (~99%). Overall, the developed HPLC-DAD procedure provides adequate confidence for the identification and quantification of ricinoleic acid in PLGA nanocapsules and other complex matrices.

Identifiants

pubmed: 39338382
pii: ph17091220
doi: 10.3390/ph17091220
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul
ID : PPSUS- Fundect 08/2020

Auteurs

Lucas Rannier M de Andrade (LRM)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Larissa F Dos Santos (LF)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Débora S Pires (DS)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Érika P Machado (ÉP)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Marco Antonio U Martines (MAU)

Institute of Chemistry, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Maria Ligia R Macedo (MLR)

Pharmaceutical Sciences, Food and Nutrition College, University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Teófilo Fernando M Cardoso (TFM)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Patrícia Severino (P)

Institute of Technology and Research (ITP), Tiradentes University, Ave. Murilo Dantas, Farolândia, Aracaju 49032-490, SE, Brazil.

Eliana B Souto (EB)

UCD School of Chemical and Bioprocess Engineering, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland.

Najla M Kassab (NM)

Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, MS, Brazil.

Classifications MeSH