Validation of an HPLC-DAD Method for Quercetin Quantification in Nanoparticles.
Pharmaceuticals (Basel)
; 16(12)2023 Dec 17.
Article
em En
| MEDLINE
| ID: mdl-38139862
ABSTRACT
The evaluation of the efficacy of incorporation of quercetin in nanoparticles is crucial, both for the development and quality control of pharmaceutical formulations. The validation of analytical methods for the precise quantification of quercetin is useful for the evaluation of various potential quercetin delivery systems and quercetin pharmacokinetics. This work aimed to validate a high-performance liquid chromatography with diode array detection (HPLC-DAD) method for quercetin detection and quantification in nanoparticles. Different mobile phase conditions and detection wavelengths (254 and 368 nm) were tested, and the major validation parameters were assessed (precision, accuracy, linearity, sensitivity, stability, and selectivity). The best peak resolution was obtained when quercetin was analyzed at 368 nm with a mobile phase of 1.5% acetic acid and a water/acetonitrile/methanol ratio of 55405. Under these conditions, quercetin also eluted rapidly (retention time of 3.6 min). The method proved to be linear (R2 > 0.995), specific, and repeatable (variation coefficient between 2.4% and 6.7%) and presented intermediate precision (variation coefficient between 7.2% and 9.4%). The accuracy of the analysis ranged between 88.6% and 110.7%, and detection and quantification limits were 0.046 and 0.14 µg/mL, respectively. Quercetin solutions were more stable when stored at 4 °C than at room temperature or -20 °C. This validated method satisfied more parameters of bias assessment than most recent methods for quercetin determination and presented itself as more sensitive and efficient than general spectrophotometric methods. The method was successfully used for the analysis of quercetin incorporation in nanoparticles and will be evaluated in the future for its adequacy for the determination of quercetin in more complex matrices.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Pharmaceuticals (Basel)
Ano de publicação:
2023
Tipo de documento:
Article