A method is proposed for the determination of chromatographic peak purity by means of principal component analysis (PCA) of high-performance liquid chromatography with diode array detection (HPLC-DAD) data. The method is exemplified with analysis of binary mixtures of lidocaine and prilocaine with different levels of separation. Lidocaine and prilocaine have very similar spectra and the chromatograms used had substantial peak overlap. The samples analysed contained a constant amount of lidocaine and a minor amount of prilocaine (0.02-2 conc.%) and hence the focus was on determining the purity of the lidocaine peak in the presence of much smaller levels of prilocaine. The peak purity determination was made by examination of relative observation residuals, scores and loadings from the PCA decomposition of DAD data over a chromatographic peak. As a reference method, the functions for peak purity analysis in the chromatographic data system used (Chromeleon) were applied. The PCA method showed good results at the same level as the detection limit of baseline-separated prilocaine, outperforming the methods in Chromeleon by a factor of ten. There is a discussion of the interpretation of the result, with some comparisons with evolving factor analysis (EFA). The main advantage of the PCA method for determination of peak purity over methods like EFA lies in its simplicity, short time of calculation and ease of use.
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[Show abstract][Hide abstract] ABSTRACT: A simple and sensitive spectrophotometric method was developed for the determination of prilocaine HCl in pharmaceutical preparation and human plasma. The quantitative analysis of prilocaine HCl was carried out using of wavelength at 230 nm. The method was linear in concentration range of 3-15 μg/mL for standard solution and 4-15 μg/mL for human plasma. Linearity was determined by calculating correlation coefficient. These values were found as a 0.9999 and 0.9967 in standard solution and human plasma, respectively. Developed spectrophotometric method was found suitable in terms of accuracy, sensitivity, precision, reproducibility. In addition to these, this method could be easily and directly applied to both human plasma and pharmaceutical preparation. INTRODUCTION: The reason of using local anesthetics is to block the conduction of impulses in nerve fibers which cause anesthesia. They are most commonly used in dentistry and minor surgery in order to provide temporary relief of pain. There are two application types of local anesthetics which are topical and parenteral applications that reversibly block the nerve conductances.
[Show abstract][Hide abstract] ABSTRACT: An approach was proposed to develop two-dimensional fingerprint (2D fingerprint) by means of principal component analysis (PCA) of high-performance liquid chromatography with diode array detection (HPLC/DAD) data. The approach was applied to establish 2D fingerprints of various Qingkailing injections which were produced by different manufacturers and procedures. In comparison with common one-dimensional fingerprint (ID fingerprint) at fixed wavelength, 2D fingerprint compiled additional spectral data and was hence more informative. Principal component analysis of the 2D fingerprint data was performed in this study, and it led to an accurate classification of various samples on their manufacturers and procedures. The quality of Qingkailing samples was further evaluated by similarity measures and the same results were achieved. For comparison, four conventional ID fingerprints were also applied to the quality assessment for the same samples. Finally, we demonstrated that 2D fingerprint was a more powerful tool to characterize the quality of samples, and could be used to comprehensively conduct the quality control of traditional Chinese medicines.
No preview · Article · Nov 2005 · Journal of Chromatography A
[Show abstract][Hide abstract] ABSTRACT: The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate calibration methods constitute an attractive alternative, even when they are applied to intrinsically unselective spectroscopic or electrochemical signals. First-order (i.e., vectorized) data are conveniently analyzed with classical chemometric tools such as partial least-squares (PLS). Certain analytical problems require more sophisticated models, such as artificial neural networks (ANNs), which are especially able to cope with non-linearities in the data structure. Finally, models based on the acquisition and processing of second- or higher-order data (i.e., matrices or higher dimensional data arrays) present the phenomenon known as “second-order advantage”, which permits quantitation of calibrated analytes in the presence of interferents. The latter models show immense potentialities in the field of biomedical analysis. Pertinent literature examples are reviewed.
No preview · Article · Jan 2006 · Microchemical Journal