Analysis of the binary mixtures of amlodipine and atorvastatin by chemometric-spectophotometric method

The utilization of selection methods such as genetic algorithm (GA) aims to construct better partial least squares (PLS) and principal component regression (PCR) models than those established from the full-spectrum range. Determination of paracetamol (PAR), orphenadrine citrate (Or.cit), and caffeine (CAF) in the presence of PAR nephrotoxic impurity [p-aminophenol (PAP)]. GA was applied to select the optimum wavelengths used. A calibration set was prepared in which the three drugs, together with PAP, were modeled by multilevel multifactor design. This calibration set was used to build the PLS and PCR models, either with or without preprocessing the data using GA. Results were compared with and without preprocessing, and this revealed that GA can find an optimized combination of spectral wavelengths, yielding a lower root mean square error of prediction as well as a lower number of latent variables used. The results of the two models show that simultaneous determination of the aforementioned drugs can be performed in the concentration ranges of 20-60, 3-11, and 1-9 μg/mL for PAR, Or.cit, and CAF, respectively. The proposed models were applied for the determination of the three drugs in their pharmaceutical formulations, and the results were verified by the standard addition technique. GA can be useful as a wavelength selection tool before applying multivariate PLS and PCR methods. GA gives an improvement in the predictive ability of the models with lower RMSEP and less number of latent variables (LVs). The proposed PLS, PCR, GA-PLS, and GA-PCR spectrophotometric methods were able to determine paracetamol, orphenadrine citrate, and caffeine in the presence of p-aminophenol and severe spectral overlapping.

Spectrophotometric multicomponent determination of sunset yellow, tartrazine and allura red in soft drink powder by double divisor-ratio spectra derivative, inverse least-squares and principal component regression methods

Simultaneous spectrofluorimetric and spectrophotometric determination of melatonin and pyridoxine in pharmaceutical preparations by multivariate calibration methods

NIR spectroscopy was used to measure the moisture content of Virginia and Valencia type in-shell peanuts. Peanuts were conditioned to various moisture levels between 7 and 26 % (wet basis) and the moisture content verified using a standard oven method on a sub-sample of each level. The various moisture levels were separated as calibration and validation sets of samples. NIR absorption spectra data from 400 to 2500 nm were collected from peanuts within the calibration and validation sample sets. Measurements were obtained on 30 replicates within each moisture level. Spectral data were mathematically treated to get its derivative function. Partial Least Square (PLS) analysis was performed on the calibration set and models were developed using the raw spectral data and its derivative function data. These models were used to predict the in-shell moisture content of peanuts in the validation sample set. The Standard Error of Calibration (SEC) and R2 of the calibration models were calculated to select the best calibration model. Predicted and reference moisture contents were compared. Relative Percent Deviation (RPD) and Standard Error of Prediction (SEP) were calculated to validate the calibration models

Two chemometrics methods—principal component regression and partial least squares—were developed for simultaneous spectrophotometric estimation of ciprofloxacin and doxycycline hyclate in pharmaceutical dosage forms without any pretreatment. The UV spectra of both drugs were recorded at concentrations within their linear ranges between 200 and 400 nm with the intervals λ = 2 nm at 100 wavelengths in distilled water. Beer's law was obeyed for both drugs in the concentration ranges of 1–10 μg/mL for ciprofloxacin and 5–25 μg/mL for doxycycline hyclate. Two sets of standard mixtures, 25 as a calibration set and 9 as a validation set, were prepared. The calibration models were evaluated by cross-validation and external validation over synthetic mixtures. The optimized models were successfully applied for chemometric analysis of ciprofloxacin and doxycycline hyclate in synthetic and pharmaceutical mixtures with satisfactory accuracy (recovery values from 97.50% to 101.87%) and precision (RSD < 2%).

Direct orthogonal signal correction(DOSC) and Savitzky-Golay filters (SGF) were applied as preprocessing methods on the original and first derivative absorbance data. Principle component regression (PCR), partial least squares (PLS) and iterative target transformation factor analysis (ITTFA), were used in spectrophotometric simultaneous determination of heavy divalent metal ions, lead, zinc, mercury and cadmium, using 4-(2-pyridylazo) resorcinol (PAR) as metallochromi c indicator. The optimum values of the parameters for DOSC and SGF were obtained according to REP, R 2 and RMSEP functions for calibration and prediction sets. The concentration for Hg 2+ , Pb 2+ , Zn 2+ and Cd 2+ ions in calibration set were varied between 0 - 12.24, 0 - 9.81, 0 - 0.87 and 0 - 3.96 ppm, respectively. The experimental calibration set was composed of 35 sample solutions and the 7 solutions as prediction set using a simple lattice (4,4) mixture design. The absorption spectra were recorded from 450 to 600 nm and absorbance data were autoscaled. The effect of pH on the sensitivity and selectivity was studied in the range of 1.00 - 11.00 and pH=7.50 was chosen according to net analyte signal (NAS) as a function of pH.

Simultaneaous spectrophotometric determination of clorsulon (CLO) and invermectin (IVE) in commercial veterinary formulation was performed by using the artificial neural network (ANN) based on the back propagation algorithm. In order to find the optimal ANN model various topogical networks were tested by using different hidden layers. A logsig input layer, a hidden layer of neurons using the logsig transfer function and an output layer of two neurons with purelin transfer function was found suitable for basic configuration for ANN model. A calibration set consisting of CLO and IVE in calibration set was prepared in the concentration range of 1-23 �g/mL and 1-14 �g/mL, repectively. This calibration set contains 36 different synthetic mixtures. A prediction set was prepared in order to evaluate the recovery of the investigated approach ANN chemometric calibration was applied to the simultaneous analysis of CLO and IVE in compounds in a commercial veterinary formulation. The experimental results indicate that the proposed method is appropriate for the routine quality control of the above mentioned active compounds.

95/00106 Properly designed transfer points reduce spillage and ease conveyor maintenance

Near-infrared spectroscopy quantitative determination of Pefloxacin mesylate concentration in pharmaceuticals by using partial least squares and principal component regression multivariate calibration

Multivariate analysis of paracetamol, propiphenazone, caffeine and thiamine in quaternary mixtures by PCR, PLS and ANN calibrations applied on wavelet transform data

Infrared (IR) spectroscopy can serve as a rapid method for the quantitative analysis of borophosphosilicate glass (BPSG) films on Si wafers for the microelectronics industry. The advantages of using statistically designed calibration sets are emphasized. Classical least-squares (CLS), partial least-squares (PLS), and principal component regression (PCR) methods are all found to provide improved precision over traditional peak-height measurements. The quantitative results from spectral measurements taken in transmission mode at both 0/sup 0/ and 60/sup 0/ incident angles were also compared. PLS and PCR methods yielded results that were comparable within the sampling error, and each exhibited a better analysis precision than that obtained from the CLS analysis. Both PLS and PCR methods yielded the best results when applied to the original 60/sup 0/ incident angle data, which was not corrected for film thickness. PLS and PCR analyses each gave a standard error of prediction (SEP) for boron of approx. = 0.1 wt% and approx. = 0.2 wt % for phosphorus for a set of 44 calibration samples which spanned a range of concentrations from 1 to 5 wt % B and 2 to 6 wt % P. The PLS and PCR methods applied to the IR spectra were also capablemore » of monitoring film thickness with a SEP of 14 nm for films that varied in thickness from 430 to 1000 nm. The importance of using these full-spectrum multivariate methods for outlier sample detection is presented, and the ability to extract qualitative spectral information from the CLS and PLS calibrations is demonstrated.« less

The results of UV spectrophotometric analysis were analysed using partial least squares (PLS) and principal component regression (PCR) techniques to allow simultaneous evaluation of tramadol hydrochloride (TRA) and p-acetaminophen (PAR) in tablets. A calibration set of 16 mixtures, each containing PAR and TRA in various amounts, was created using a 24-full fractional design. The absorbance data set for the calibration set were obtained between 215–280 nm (Δλ = 0.1 nm). Subsequently, the concentration and absorbance sets were used to generate PCR and PLS calibrations. The ratio spectra- first derivative method was devised as a solution to the same problem to compare the outcomes of the chemometric methods used for the same experiment. After the proposed methods were shown to be accurate in the testing of validation samples, they were used in analysing commercial tablet samples. The analytical results showed that PCR and PLS methods can be used as alternative methods to high-performance liquid chromatography (HPLC). Correlation coefficients were determined for the working concentration range of 6–36 g.mL−1 for PAR and 4–22 g.mL−1 for TRA. The limits of detection and quantification were calculated as 0.9104 μg.mL−1 and 3.0347 μg.mL−1, respectively. The test results of the chemometric analyses and ratio spectra- first derivative method of the commercial tablet form are in agreement with the results of the one-way ANOVA with a confidence interval of 95%. This study shows that the ratio spectra- first derivative method, PCR and PLS models based on spectrophotometric measurements are very useful and straightforward techniques for the quantitative resolution of a two-component pharmaceutical preparation, requiring little sample preparation and little time for analysis.

In this paper, a novel microwave measurement approach is presented, which is capable of determining selected food properties from the dielectric spectrum. Such properties could be the water content, a possible amount of additionally added water, the content of conducting ions or the percentage of other constituents, having a noticeable influence on the effective complex permittivity versus frequency. The approach is based on measured dielectric data across a significant bandwidth of one or two octaves (or more), and on data analysis using the multi-variate statistical method of Principal Component Analysis (PCA) and Principal Component Regression (PCR). The prototype of a dedicated microwave instrument is described and as an experimental example the viability of the new approach is demonstrated by the exact determination of the percentage of deliberately added water in fruit juices.

Multivariate calibration of first-order data with the correlation constrained MCR-ALS method

Dissolution and assaying of multicomponent tablets by chemometric methods using computer-aided spectrophotometer