Simultaneous determination of sulphamethoxazole and trimethoprim in powder mixtures by attenuated total reflection-Fourier transform infrared and multivariate calibration

Quantification and Classification of Diclofenac Sodium Content in Dispersed Commercially Available Tablets by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

A new methodology, based on Fourier transform infrared spectroscopy equipped with an attenuated total reflectance accessory (ATR FT-IR), was developed for the determination of diclofenac sodium (DS) in dispersed commercially available tablets using chemometric tools such as partial least squares (PLS) coupled with discriminant analysis (PLS-DA). The results of PLS-DA depicted a perfect classification of the tablets into three different groups based on their DS concentrations, while the developed model with PLS had a sufficiently low root mean square error (RMSE) for the prediction of the samples’ concentration (~5%) and therefore can be practically used for any tablet with an unknown concentration of DS. Comparison with ultraviolet/visible (UV/Vis) spectrophotometry as the reference method revealed no significant difference between the two methods. The proposed methodology exhibited satisfactory results in terms of both accuracy and precision while being rapid, simple and of low cost.

Development and Validation of a Simple, Green Infrared Spectroscopic Method for Quantitation of Sildenafil Citrate in Siloflam Tablets of Unknown Manufacturing Formula

A simple, easy-to-implement, and green infrared spectroscopic method was developed and validated for the quantitative determination of sildenafil citrate in tablets of unknown manufacturing formula. Homogenized tablet powder with known mass content (%, m/m) of sildenafil citrate was mixed with paracetamol to form standard mixtures with different percentages of sildenafil citrate on the total quantity of sildenafil citrate and paracetamol (designated as R). Unknown tablet samples were finely ground and mixed with paracetamol to form test mixtures having R values about 50%. Infrared spectra of standard mixtures, measured in attenuated total reflectance mode, in the wavenumber zone from 1800 cm^-1 to 1300 cm^-1 were selected and processed by partial least square regression to form the calibration model for quantitation of sildenafil citrate in unknown samples. Spectral responses of test mixtures and the calibration model were used to determine the exact mass content (%, m/m) of sildenafil citrate in the powder of unknown tablet samples. The method was fully validated in terms of linearity, precision, and accuracy according to the requirements of current guidelines and was proved as reliable and suitable for the intended application.

Diagonal designs for a multi-component calibration experiment

Modern spectroscopic and sensor technologies combined with multivariate modelling are increasingly used for the quantitative analysis of complex mixtures. Their performance depends directly on the data design chosen for model training and validation. A well-balanced calibration experiment with the fewest samples possible presents additional challenges when several mixture components (factors) need to be calibrated on the same dataset and subsequently quantified from the same multivariate measurement. This practically important problem stays poorly addressed by the theory of experimental design. This theoretical work systematically formulates the requirements to an optimal calibration/validation dataset and introduces a new family of calibration designs, where the samples are placed along the diagonals of an experimental space that is a hypercube. Such placement is appropriate due to reasonable assumptions about the linear nature of analytical response. Suggested filling schemes allow economical diagonal designs with intrinsic validation to be built for multiple factors presented in as many levels as the number of samples. The most important practical cases of two and three factors are considered in detail, and generalization to higher dimensions is outlined. Diagonal designs of any complexity can be generated using a simple geometrical scheme or with a supplied script.

Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations

An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.

Determination of propranolol hydrochloride in pharmaceutical preparations using near infrared spectrometry with fiber optic probe and multivariate calibration methods

A method for determination of propranolol hydrochloride in pharmaceutical preparation using near infrared spectrometry with fiber optic probe (FTNIR/PROBE) and combined with chemometric methods was developed. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). The treatments based on the mean centered data and multiplicative scatter correction (MSC) were selected for models construction. A root mean square error of prediction (RMSEP) of 8.2 mg g(-1) was achieved using siPLS (s2i20PLS) algorithm with spectra divided into 20 intervals and combination of 2 intervals (8501 to 8801 and 5201 to 5501 cm(-1)). Results obtained by the proposed method were compared with those using the pharmacopoeia reference method and significant difference was not observed. Therefore, proposed method allowed a fast, precise, and accurate determination of propranolol hydrochloride in pharmaceutical preparations. Furthermore, it is possible to carry out on-line analysis of this active principle in pharmaceutical formulations with use of fiber optic probe.

Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

Near-infrared reflectance spectroscopy (NIRS) with partial least squares regression (PLSR) was used to determine levels of fat, protein and moisture in ricotta cheese without complex sample preparation. Spectra of 19 conventional and low-fat ricotta samples from different manufacturers were collected in duplicate, with 33 of the 38 spectra used as a calibration set and the remaining 5 spectra used as an external validation set. The best results were obtained by processing the spectral region between 1,100 and 2,500 nm. Multivariate models with six latent variables (LVs) showed good prediction capability for fat and protein determinations, with average relative errors (Er) of 6.37 % and 5.95 %, respectively. For moisture, a more robust model was obtained with 4 LVs, showing better prevision capacity and Er of 1.91 %.

Chemometric quality inspection control of pyrantel pamoate, febantel and praziquantel in veterinary tablets by mid infrared spectroscopy

This paper describes the development and validation of a new multivariate calibration method based on diffuse reflectance mid infrared spectroscopy for direct and simultaneous determination of three veterinary pharmaceutical drugs, pyrantel pamoate, praziquantel and febantel, in commercial tablets. The best synergy interval partial least squares (siPLS) model was obtained by selecting three spectral regions, 3715-3150, 2865-2583, and 2298-1733 cm(-1), preprocessed by first derivative and Savitzky-Golay smoothing followed by mean centering. This model was built with five latent variables and provided root mean square errors of prediction (RMSEP) equal or lower than 0.69 mg per 100 mg of powder for the three analytes. The method was validated according the appropriate regulations through the estimate of figures of merit, such as trueness, precision, linearity, analytical sensitivity, bias and residual prediction deviation (RPD). Then, it was applied to three different veterinary pharmaceutical formulations found in the Brazilian market, in a situation of multi-product calibration, since the excipient composition of these commercial products, which was not known a priori, was modeled by an experimental design that scanned the likely content range of the possible constituents. The results were verified with high performance liquid chromatography with diode array detection (HPLC-DAD) and high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and were in agreement with the predicted values at 95% confidence level. The developed method presented the advantages of being simple, rapid, solvent free, and about ten times faster than the HPLC ones.

Rapid quantification of methamphetamine: using attenuated total reflectance fourier transform infrared spectroscopy (ATR-FTIR) and chemometrics

In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1%-78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R(2) 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R(2) 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.

Vibrational spectroscopic and DFT study of trimethoprim

Structural investigations by different vibrational spectroscopic methods: FTIR, FT-Raman and surface-enhanced Raman scattering (SERS) spectroscopy, as well as density functional theory (DFT) calculations were performed on trimethoprim (5-(3,4,5-trimethoxybenzyl)pyrimidine-2,4-diamine). A reliable assignment of vibrational IR, Raman and SERS bands was possible by a proper choice of model used in quantum chemical calculations. Based on SERS spectrum analysis it is shown that the molecule is adsorbed on the silver surface through the pyrimidine ring, in a perpendicular orientation. Two theoretical models were used in order to simulate the silver surface and the interaction with trimethoprim molecule, the accuracy of the models being evaluated by comparing the predicted bands position of the two complexes with the SERS result.

Stability-Indicating Validated HPLC Method for Analysis of Berberine Hydrochloride and Trimethoprim in Pharmaceutical Dosage Form

A stability-indicating HPLC method was developed and validated for the determination of berberine hydrochloride and trimethoprim in pharmaceutical dosage form in the presence of degradation products. The proposed RP-HPLC method utilizes an Agilent TC-C18, 4.6 mm × 250 mm, 5 μm, column using a mobile phase consisting of acetonitrile-50 mM potassium dihydrogen phosphate (30 : 70, v/v, pH adjusted to 3 with orthophosphoric acid) at a flow rate of 1.0 mL/min and UV detection at 271 nm. The linearity of berberine hydrochloride and trimethoprim was in the range of 2 to 60 μg/mL (r=0.9996) and 1 to 30 μg/mL (r=0.9995), respectively. Repeatability and intermediate precisions were also determined with percentage relative standard deviation (% RSD) less than 2.0%. The limits of detection were found to be 9.8 ng/mL for berberine hydrochloride and 2.5 ng/mL for trimethoprim. The mean recoveries for berberine hydrochloride and trimethoprim were 99.8 and 98.8%, respectively. The stability of the two drugs was determined under different conditions and the proposed method has shown effective separation for their degradation products. And the proposed assays method can thus be considered stability-indicating.

Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods

Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm(-1)). This model produced a RMSECV of 400 mg kg(-1) S and RMSEP of 420 mg kg(-1) S, showing a correlation coefficient of 0.990.

Simultaneous diffuse reflectance infrared determination of clavulanic acid and amoxicillin using multivariate calibration techniques

A method for simultaneous determination of clavulanic acid (CA) and amoxicillin (AMO) in commercial tablets was developed using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and multivariate calibration. Twenty-five samples (10 commercial and 15 synthetic) were used as a calibration set and 15 samples (10 commercial and 5 synthetic) were used for a prediction set. Calibration models were developed using partial least squares (PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) algorithms. The best algorithm for CA determination was siPLS model with spectra divided in 30 intervals and combinations of 2 intervals. This model showed a root mean square error of prediction (RMSEP) of 5.1 mg g(-1). For AMO determination, the best siPLS model was obtained with spectra divided in 10 intervals and combinations of 4 intervals. This model showed a RMSEP of 22.3 mg g(-1). The proposed method was considered as a suitable for the simultaneous determination of CA and AMO in commercial pharmaceuticals products.