Simultaneous multivariate spectrophotometric analysis of paracetamol and minor components (diphenhydramine or phenylpropanolamine) in tablet preparations

The use of multivariate spectrophotometric calibration is reported for the analysis of two decongestant tablets, where paracetamol is the principal component and diphenhydramine or phenylpropanolamine are the minor components. The resolution of these mixtures has been accomplished without prior separation or derivatisation, by using partial least-squares (PLS-1) regression analysis of electronic absorption spectral data. Although the molar ratios of paracetamol to the minor components were 38:1 and 25:1 respectively, the latter have been determined with high accuracy and precision, and with no interference from tablet excipients. PLS is able to take into account small deviations of paracetamol from linearity in the studied concentration range. The application of classical least-squares (CLS) analysis yields unsatisfactory results, due to the low absorbances of the minor components within the range where all components obey Beer's law.     

High-Throughput NIR-Chemometric Method for Meloxicam Assay from Powder Blends for Tableting

A near infrared (NIR) method able to directly quantify the active content in pharmaceutical powder blends used for manufacturing meloxicam tablets, without any sample preparation, was developed and fully validated. To develop calibration models for the assay of meloxicam in powder blends for tableting, the NIR reflectance spectra of different meloxicam powder blends prepared according to a calibration protocol was analysed using different preprocessing methods by partial last-square regression (PLS) and principal component regression (PCR).The best calibration model was found when partial last-square regression (PLS) was used as regression algorithm in association with Smoothing-Savitsky as pre-processing spectrum method. The trueness, precision (repeatability and intermediate precision), accuracy, linearity and range of application of the developed NIR method were validated according to the International Conference of Harmonization (ICH) and Medicine European Agency (EMA) guidelines and found to be fit for its intended purpose.     

Simultaneous spectrophotometric determination of diclofenac potassium and methocarbamol in binary mixture using chemometric techniques and artificial neural networks

In this study, the simultaneous determination of diclofenac potassium (DP) and methocarbamol (MT) by chemometric approaches and artificial neural networks using UV spectrophotometry has been reported as a simple alternative to using separate models for each component. Three chemometric techniques-classical least-squares (CLS), principal component regression (PCR), and partial least-squares (PLS)-along with radial basis function-artificial neural network (RBF-ANN) were prepared by using the synthetic mixtures containing the two drugs in methanol. A set of synthetic mixtures of DP and MT was evaluated and the results obtained by the application of these methods were discussed and compared. In CLS, PCR, and PLS, the absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range 260-310 nm in the intervals with Δλ = 0.2 nm in their zero-order spectra. Then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of DP and MT in their mixtures. In RBF-ANN, the input layer consisting of 251 neurons, 9 neurons in the hidden layer, and 2 output neurons were found appropriate for the simultaneous determination of DP and MT. The accuracy and the precision of the four methods have been determined and they have been validated by analyzing synthetic mixtures containing the two drugs. The proposed methods were successfully applied to a pharmaceutical formulation containing the examined drugs.     

Simultaneous estimation of ramipril, acetylsalicylic acid and atorvastatin calcium by chemometrics assisted UV-spectrophotometric method in capsules

In the present work, three different spectrophotometric methods for simultaneous estimation of ramipril, aspirin and atorvastatin calcium in raw materials and in formulations are described. Overlapped data was quantitatively resolved by using chemometric methods, viz. inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS). Calibrations were constructed using the absorption data matrix corresponding to the concentration data matrix. The linearity range was found to be 1-5, 10-50 and 2-10 μg mL-1 for ramipril, aspirin and atorvastatin calcium, respectively. The absorbance matrix was obtained by measuring the zero-order absorbance in the wavelength range between 210 and 320 nm. A training set design of the concentration data corresponding to the ramipril, aspirin and atorvastatin calcium mixtures was organized statistically to maximize the information content from the spectra and to minimize the error of multivariate calibrations. By applying the respective algorithms for PLS 1, PCR and ILS to the measured spectra of the calibration set, a suitable model was obtained. This model was selected on the basis of RMSECV and RMSEP values. The same was applied to the prediction set and capsule formulation. Mean recoveries of the commercial formulation set together with the figures of merit (calibration sensitivity, selectivity, limit of detection, limit of quantification and analytical sensitivity) were estimated. Validity of the proposed approaches was successfully assessed for analyses of drugs in the various prepared physical mixtures and formulations.     

Chemometrics-Assisted UV Spectrophotometric and RP-HPLC Methods for the Simultaneous Determination of Tolperisone Hydrochloride and Diclofenac Sodium in their Combined Pharmaceutical Formulation

Chemometrics-assisted UV spectrophotometric and RP-HPLC methods are presented for the simultaneous determination of tolperisone hydrochloride (TOL) and diclofenac sodium (DIC) from their combined pharmaceutical dosage form. Chemometric methods are based on principal component regression and partial least-square regression models. Two sets of standard mixtures, calibration sets, and validation sets were prepared. Both models were optimized to quantify each drug in the mixture using the information included in the UV absorption spectra of the appropriate solution in the range 241–290 nm with the intervals λ = 1 nm at 50 wavelengths. The optimized models were successfully applied to the simultaneous determination of these drugs in synthetic mixture and pharmaceutical formulation. In addition, an HPLC method was developed using a reversed-phase C18 column at ambient temperature with a mobile phase consisting of methanol:acetonitrile:water (60:30:10 v/v/v), pH-adjusted to 3.0, with UV detection at 275 nm. The methods were validated in terms of linearity, accuracy, precision, sensitivity, specificity, and robustness in the range of 3–30 μg/mL for TOL and 1–10 μg/mL for DIC. The robustness of the HPLC method was tested using an experimental design approach. The developed HPLC method, and the PCR and PLS models were used to determine the amount of TOL and DIC in tablets. The data obtained from the PCR and PLS models were not significantly different from those obtained from the HPLC method at 95% confidence limit.     

Simultaneous spectrophotometric determination of pseudoephedrine hydrochloride and ibuprofen in a pharmaceutical preparation using ratio spectra derivative spectrophotometry and multivariate calibration techniques

Spectrophotometric methods are described for the simultaneous determination of pseudoephedrine hydrochloride and ibuprofen in their combination. The obtained data were evaluated by using five different methods. In the first method, ratio spectra derivative spectrophotometry, analytical signals were measured at the wavelengths corresponding to either maximums and minimums for both drugs in the first derivative spectra of the ratio spectra obtained by using each other spectra as divisor in their solution in 0.1 M HCl. In the other four spectrophotometric methods using chemometric techniques, classical least-squares, inverse least-squares, principal component regression and partial least-squares (PLS), the concentration data matrix were prepared by using the synthetic mixtures containing these drugs in methanol:0.1 M HCl (3:1). The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range 240-285 nm in the intervals with deltalambda = 2.5 nm at 18 wavelengths in their zero-order spectra, then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of pseudoephedrine hydrochloride and ibuprofen in their mixture. The procedures did not require any separation step. The linear range was found to be 300-1300 microg/ml for ibuprofen and 100-1300 microg/ml for pseudoephedrine hydrochloride in all five methods. The accuracy and the precision of the methods have been determined and they have been validated by analyzing synthetic mixtures. The five methods were successfully applied to tablets and the results were compared with each other.     

Stability‐indicating chemometric methods for the determination of tazarotene

Two multivariate calibration methods—principal component regression (PCR) and partial least square (PLS)—have been used to determine tazarotene in the presence of its degradation products. Both methods are useful in spectral analysis because of the simultaneous inclusion of many spectral wavelengths instead of the single wavelength used in derivative spectrophotometry. A great improvement in the precision and predictive abilities of these multivariate calibrations was observed. A calibration set was constructed for the mixture and the best model was used to predict the concentration of the selected drug. The proposed methods were applied successfully in the determination of tazarotene in laboratory‐prepared mixtures and in commercial preparations. Tazarotene was analyzed with mean accuracies of 100.006 ± 0.695 and 100.007 ± 0.690 using the PCR and PLS methods, respectively. The validity of the proposed methods was assessed using the standard addition technique. The proposed methods were found to be rapid, simple and required no preliminary separation. They can therefore be used for the routine analysis of tazarotene in quality‐control laboratories. Copyright © 2010 John Wiley & Sons, Ltd.     

Determination of paracetamol and orphenadrine citrate in pharmaceutical tablets by modeling of spectrophotometric data using partial least-squares and artificial neural networks

The estimation of paracetamol and orphenadrine citrate in a multicomponent pharmaceutical dosage form by spectrophotometric method has been reported. Because of highly interference in the spectra and the presence of non-linearity caused by the analyte concentrations which deviate from Beer and Lambert's law, partial least-squares (PLS) and artificial neural networks (ANN) techniques were used for the calibration. A validation set of spiked samples was employed for testing the accuracy and precision of the methods. Reasonably good recoveries were obtained with PLS for paracetamol and the use of an ANN allowed the estimation of orphenadrine citrate, a minor component which could not be adequately modeled by PLS. Three production batches of a commercial sample were analysed, and there was statistically no significant difference (P<0.05) between the results with the proposed method and those obtain with the official comparative method.     

A new technique for spectrophotometric determination of pseudoephedrine and guaifenesin in syrup and synthetic mixture

The accuracy in predicting different chemometric methods was compared when applied on ordinary UV spectra and first order derivative spectra. Principal component regression (PCR) and partial least squares with one dependent variable (PLS1) and two dependent variables (PLS2) were applied on spectral data of pharmaceutical formula containing pseudoephedrine (PDP) and guaifenesin (GFN). The ability to derivative in resolved overlapping spectra chloropheniramine maleate was evaluated when multivariate methods are adopted for analysis of two component mixtures without using any chemical pretreatment. The chemometrics models were tested on an external validation dataset and finally applied to the analysis of pharmaceuticals. Significant advantages were found in analysis of the real samples when the calibration models from derivative spectra were used. It should also be mentioned that the proposed method is a simple and rapid way requiring no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories.     

Detection of diethylene glycol adulteration in propylene glycol--method validation through a multi-instrument collaborative study

Four portable NIR instruments from the same manufacturer that were nominally identical were programmed with a PLS model for the detection of diethylene glycol (DEG) contamination in propylene glycol (PG)-water mixtures. The model was developed on one spectrometer and used on other units after a calibration transfer procedure that used piecewise direct standardization. Although quantitative results were produced, in practice the instrument interface was programmed to report in Pass/Fail mode. The Pass/Fail determinations were made within 10s and were based on a threshold that passed a blank sample with 95% confidence. The detection limit was then established as the concentration at which a sample would fail with 95% confidence. For a 1% DEG threshold one false negative (Type II) and eight false positive (Type I) errors were found in over 500 samples measured. A representative test set produced standard errors of less than 2%. Since the range of diethylene glycol for economically motivated adulteration (EMA) is expected to be above 1%, the sensitivity of field calibrated portable NIR instruments is sufficient to rapidly screen out potentially problematic materials. Following method development, the instruments were shipped to different sites around the country for a collaborative study with a fixed protocol to be carried out by different analysts. NIR spectra of replicate sets of calibration transfer, system suitability and test samples were all processed with the same chemometric model on multiple instruments to determine the overall analytical precision of the method. The combined results collected for all participants were statistically analyzed to determine a limit of detection (2.0% DEG) and limit of quantitation (6.5%) that can be expected for a method distributed to multiple field laboratories.     

Acetaminophen determination in low-dose pharmaceutical syrup by NIR spectroscopy

The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2%, w/v). Therefore, variability sources such as production campaigns, batches, API concentration, syrup basis, operators and sample temperatures were introduced in the calibration set. A prediction model was then built using partial least square (PLS) regression. First derivative followed by standard normal variate (SNV) were chosen as signal pre-processing. Based on the random subsets cross-validation, 4 PLS factors were selected for the prediction model. The method was then validated for an API concentration ranging from 16 to 24 mg/mL (1.6–2.4%, w/v) using an external validation set. The 0.26 mg/mL RMSEP suggested the global accuracy of the model. The accuracy profile obtained from the validation results, based on tolerance intervals, confirmed the adequate accuracy of the results generated by the method all over the investigated API concentration range. Finally, the NIR model was used to monitor in real time the API concentration while mixing syrups containing various amounts of API, a good agreement was found between the NIR method and the theoretical concentrations.     

Rapid quantification of constituents in St. John's wort extracts by NIR spectroscopy

A quantitative near-infrared reflectance spectroscopy (NIRS) method was established for the determination of two major constituents (hyperforin and I3,II8-biapigenin) in St. John's wort extracts. Hyperforin was chosen due to the fact that it is found in a concentration range from 1 to 5%, a common one for NIRS determinations. I3,II8-Biapigenin on the other hand was selected as a constituent with very low concentrations (0.1-0.7%) but an extensive chromophore that allows very precise measurements in the ultraviolet (UV) and thus exact reference values that are vital for proper NIRS calibrations. Reference measurements were performed by reversed-phase high performance liquid chromatography (HPLC), determining the constituents' content in 35 pharmaceutical dry extracts of different origins. The reference method was validated according to the ICH guideline Q2B. Using partial-least squares (PLS) regression a multivariate calibration was done for the two ingredients each (PLS1). Satisfactory calibration statistics were obtained for hyperforin with a root mean square error of calibration (RMSEC) of 0.17 and a root mean square error of prediction (RMSEP) of 0.22 at a concentration range from 1 to 6% in the dry extracts. Due to the very low concentrations of I3,II8-biapigenin the accuracy of prediction is somewhat lower. However, it is possible to obtain very good results and reliable prediction by dividing the concentration range at 0.35%. The study emphasizes the potential of NIRS as a rapid and highly effective alternative method to conventional quantitative analysis of plant extracts.     

Validation of a fully automated solid‐phase extraction and ultra‐high‐performance liquid chromatography–tandem mass spectrometry method for quantification of 30 pharmaceuticals and metabolites in post‐mortem blood and brain samples

In this study, we present the validation of an analytical method capable of quantifying 30 commonly encountered pharmaceuticals and metabolites in whole blood and brain tissue from forensic cases. Solid‐phase extraction was performed by a fully automated robotic system, thereby minimising manual labour and human error while increasing sample throughput, robustness, and traceability. The method was validated in blood in terms of selectivity, linear range, matrix effect, extraction recovery, process efficiency, carry‐over, stability, precision, and accuracy. Deuterated analogues of each analyte were used as internal standards, which corrected adequately for any inter‐individual variability in matrix effects on analyte accuracy and precision. The lower limit of quantification (LLOQ) spanned from 0.0008 to 0.010 mg/kg, depending on the analyte, while the upper LOQ ranged between 0.40 and 2.0 mg/kg. Thus, the linear range covered both therapeutic and toxic levels. The method showed acceptable accuracy and precision, with accuracies ranging from 80 to 118% and precision below 19% for the majority of the analytes. Linear range, matrix effect, extraction recovery, process efficiency, precision, and accuracy were also tested in brain homogenate and the results agreed with those from blood. An additional finding was that the analyte concentrations in brain samples could be quantified by calibration curves obtained from spiked blood samples with acceptable precision and accuracy when using deuterated analogues of each analyte as internal standards. This method has been successfully implemented as a routine analysis procedure for quantification of pharmaceuticals in both blood and brain tissue since 2015.     

Simultaneous spectrofluorimetric determination of (acetyl)salicylic acid, codeine and pyridoxine in pharmaceutical preparations using partial least-squares multivariate calibration

A partial least-squares calibration (PLS) method for the simultaneous spectrofluorimetric determination of salicylic acid (SA), codeine (CO) and pyridoxine (PY) is proposed. The determination of SA, CO, and PY has been carried out in mixtures of up to three components by recording the emission fluorescence spectra between 300 and 500 nm (lambda(exc) = 220 nm). Due to the fact of the strong spectral overlap among the excitation and also among the emission spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrofluorimetric methodologies. Here, a full-spectrum multivariate calibration PLS method is developed. The experimental calibration matrix was constructed with 14 samples. The concentration ranges considered were 0.1-2.0 (SA), 0.25-3.0 (CO) and 0.10-2.0 (PY) mg x l(-1). The optimum number of factors was selected by using the cross-validation method. The method also allows the simultaneous determination of acetylsalicylic acid (ASA), CO and PY by previous alkaline hydrolysis of ASA to SA. To check the accuracy of the proposed method, it was applied to the determination of these compounds in synthetic mixtures and in pharmaceuticals.     

Simultaneous spectrophotometric determination of rutin, quercetin and ascorbic acid in drugs using a Kalman Filter approach

A UV-spectrophotometric analysis of severely overlapped spectra yielded by anti-capillary fragility pharmaceutical materials, viz. rutin, quercetin and ascorbic acid, in authentic mixtures and in tablets or soft elastic capsules was proposed. The method was based on Kalman Filter calibration of either orthogonal experimental design, i.e. standard solutions containing only one component at a time, or non-orthogonal experimental design, i.e. standard solutions containing more than one component. This calibration was followed by quantitative determinations of two- and three-component mixtures in synthetic mixtures or in oral dosages within the concentration range 2-10 microg ml(-1). A statistical analysis of the results was reported.     

Application of some chemometric methods in conventional and derivative spectrophotometric analysis of acetaminophen and ascorbic acid

The multivariate methods, principal component regression (PCR) and partial least squares (PLS) were tested as a calibration procedure for simultaneous ultraviolet spectrophotometric determination of acetaminophen (AC) and ascorbic acid (AA). Determination of these compounds is important because of their pharmacotherapeutic advantages. Due to spectral overlapping of AC and AA, PCR and PLS were used for construction of the calibration sets. The concentration linear range of AC and AA were 1.5–24.2 and 1.8–21.1 µg mL^?1 respectively. The absorption spectra were recorded from 215–310 nm. The minimum root mean square error of prediction (RMSEP) was 1.3507 and 0.4088 for AC and AA, by PLS, 0.7525 and 0.4015 by PCR in original data and 0.9454 and 0.2875, by PLS and 1.0386 and 0.4000 by PCR in derivative data. The procedure allows the simultaneous determination of AC and AA in synthetic mixtures and real sample solutions made up from pharmaceutical products, human serum and urine. Copyright © 2010 John Wiley & Sons, Ltd.     

Development of a method for nondestructive NIR transmittance spectroscopic analysis of acetaminophen and caffeine anhydrate in intact bilayer tablets

Calibration models for nondestructive NIR analysis of API (active pharmaceutical ingredient) contents in two separate layers of intact bilayer tablets were established. These models will enable the use of NIR transmittance spectroscopy in bilayer tableting processes for the control of API contents in separate layers. Acetaminophen and caffeine anhydrate were used as APIs, and tablets were made by the direct compression method. Their NIR spectra were measured in the transmittance mode. The reference assay was performed by HPLC. Calibration models were generated by the partial least-squares (PLS) regression. The initial calibration generated models with insufficient linearity and accuracy because the fluctuation range of tablet thickness was excessively large and irrelevant information on the thickness fluctuation was included in the models. By narrowing the fluctuation range to determine the proper range for acceptable prediction accuracy, it was confirmed that calibration models with less irrelevant information can be generated when the range was 4.30 ± 0.06 mm or narrower. Furthermore, the fluctuation range of 4.30 ± 0.06 mm was considered to be empirically valid in covering the fluctuation actually observed in ordinary tableting processes. Thus, the sample tablets within this range were used to generate the final calibration models, and calibration models sufficient in linearity and accuracy were established. In addition, it was proven that controlling the irradiated side was unnecessary. Namely, it is not necessary to keep the same side of sampled tablets for the online NIR analysis during bilayer tableting. It is useful, in order to obtain adequate calibration models, to evaluate the variable factors that affect the linearity and accuracy of the generated models and restrict the range of models or use a subset of prepared samples. Loading vectors, explained variances, and correlation coefficients between components and scores are important for the evaluation of variable factors.     

Determination of molecular weight of hyaluronic acid by near-infrared spectroscopy

This paper attempted the feasibility to determine the molecular weight of hyaluronic acid with near-infrared (NIR) diffuse reflectance spectroscopy. In this work, 46 experimental samples of hyaluronic acid powder were analyzed by partial least square (PLS) regression multivariate calibration method in the selected region of NIR spectra. The leave-one-out cross-validation method was used for the PLS model selection criterion. The accuracy of the final model was evaluated according to correlation coefficient of prediction set (Rp) and root mean square error of prediction set (RMSEP). The repeatability was verified through repeated measurement of spectra coupled with an appropriate chi-square test. Finally, the optimal calibration model was obtained with Rp = 0.9814 and RMSEP = 88.32 when using Savitzky-Golay first (SG-1st) derivative with 9 smoothing points spectral preprocessing method. The parameters above and repeatability of NIR spectroscopy obtained from chi-square test were both within the range of permissible error in factories. This study demonstrated that NIR spectroscopy was superior to conventional methods for the fast determination of molecular weight of hyaluronic acid.     

Migration of ephedrine and salicylic acid from lipid mixtures containing isopropyl myristate

The migration rates of ephedrine and salicylic acid from white soft paraffin-isopropyl myristate mixtures into water have been measured using a previously described procedure. The rates for ephedrine decreased progressively with increasing isopropyl myristate concentration, and this was attributed to the observed accompanying increase in solubility, which decreased the activity of the solute in the solution. Solubility and partition coefficient determinations established that the improved solubility resulted from complexation between ephedrine and isopropyl myristate. In contrast, migration rates of salicylic acid in white soft paraffin-isopropyl myristate mixtures increased with increasing isopropyl myristate concentration up to 50% isopropyl myristate, and then declined. Solubility and partition coefficient determinations indicated that salicylic acid dimerised and also complexed with isopropyl myristate in the lipid mixtures. The diffusion rate profile was attributed to a balance between declining solute-solute and increasing solute-solvent complexation with increasing isopropyl myristate concentration. This mechanism was supported by the behaviour of salicylic acid in Witepsol H15-isopropyl myristate mixtures.