Document Detail


Evaluation of anticancer drug-loaded nanoparticle characteristics by nondestructive methodologies.
MedLine Citation:
PMID:  22535519     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The purpose of this study was to utilize near-infrared (NIR) spectroscopy and near-infrared chemical imaging (NIR-CI) as non-invasive techniques to evaluate the drug loading in letrozole-loaded PLGA nanoparticle formulations prepared by the emulsification-solvent evaporation method. A Plackett-Burman design was applied to evaluate the main effects of amount of drug (X(1)), amount of polymer (X(2)), stirring rate (X(3)), emulsifier concentration (X(4)), organic to aqueous phase volume ratio (X(5)), type of organic solvent (X(6)), and homogenization time (X(7)) on drug entrapment efficiency. The influence of three different spectral pretreatment methods (multiplicative scatter correction, standard normal variate, and Savitzky-Golay second derivative transformation with third-order polynomial) and two different regression methods (PLS regression and principal component regression (PCR)) on model prediction ability were compared. PLS of spectra that were pretreated with Savitzky-Golay second derivative transformation provided better model prediction than PCR as it revealed better linear correlation (correlation coefficient of 0.991) for both calibration and prediction models. Relatively low values of root mean square errors of calibration (RMSEC = 0.748) and prediction (RMSEP = 0.786) and low standard errors of calibration (SEC = 0.758) and prediction (SEP = 0.589) suggested good predictability for estimation of the loading of letrozole in PLGA nanoparticles. NIR-CI analysis also revealed mutual homogenous distribution of both polymer and drug and was capable of clearly distinguishing the 12 formulations both quantitatively and qualitatively. In conclusion, NIR and NIR-CI could be potentially used to characterize anticancer drug-loaded nanoparticulate matrix.
Authors:
David Awotwe-Otoo; Ahmed S Zidan; Ziyaur Rahman; Muhammad J Habib
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Publication Detail:
Type:  Comparative Study; Evaluation Studies; Journal Article     Date:  2012-04-26
Journal Detail:
Title:  AAPS PharmSciTech     Volume:  13     ISSN:  1530-9932     ISO Abbreviation:  AAPS PharmSciTech     Publication Date:  2012 Jun 
Date Detail:
Created Date:  2012-05-31     Completed Date:  2012-10-05     Revised Date:  2013-06-25    
Medline Journal Info:
Nlm Unique ID:  100960111     Medline TA:  AAPS PharmSciTech     Country:  United States    
Other Details:
Languages:  eng     Pagination:  611-22     Citation Subset:  IM    
Affiliation:
Department of Pharmaceutical Sciences, College of Pharmacy, Howard University, 2300 4th street, N.W., Washington, District of Columbia 20059, USA.
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MeSH Terms
Descriptor/Qualifier:
Antineoplastic Agents, Hormonal / chemistry*
Aromatase Inhibitors / chemistry*
Calibration
Chemistry, Pharmaceutical
Chromatography, High Pressure Liquid
Chromatography, Reverse-Phase
Drug Carriers*
Emulsifying Agents / chemistry
Lactic Acid / chemistry*
Least-Squares Analysis
Linear Models
Models, Chemical
Models, Statistical
Nanoparticles*
Nanotechnology
Nitriles / chemistry*
Polyglycolic Acid / chemistry*
Principal Component Analysis
Quality Control
Spectroscopy, Near-Infrared* / standards
Technology, Pharmaceutical / methods*,  standards
Triazoles / chemistry*
Chemical
Reg. No./Substance:
0/Antineoplastic Agents, Hormonal; 0/Aromatase Inhibitors; 0/Drug Carriers; 0/Emulsifying Agents; 0/Nitriles; 0/Triazoles; 0/polylactic acid-polyglycolic acid copolymer; 112809-51-5/letrozole; 26009-03-0/Polyglycolic Acid; 50-21-5/Lactic Acid
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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