Rapid detection of sildenafil analogue in Eurycoma longifolia products using a new two-tier procedure of the near infrared (NIR) spectra database.

A simple and cost-effective two-tier drug screening procedure comprises a 'dedicated' NIR spectral database of common medicines and a 'unified' database was developed to detect the sildenafil analogue in Eurycoma longifolia products. Diffuse reflectance spectra of ten commercial herbal products containing E. longifolia were obtained over the wavelength range of 1100-2500 nm. The spectral search of two products purchased via the internet against a dedicated database of reputable E. longifolia products have resulted in the similarity index of more than 0.1 which indicated significantly different spectra. Further searches against the unified database showed a close match to the spectra of drug containing sildenafil citrate suggesting the presence of a sildenafil analogue. This finding was supported by clustering of these spectra in the PCA score plot within 5% significance level. This approach has alleviated the use of reference product or standard active for direct comparison and has a potential to be used for adulterated food and drugs detection.

Near-infrared spectroscopy (NIRS) and chemometric analysis of Malaysian and UK paracetamol tablets: a spectral database study.

The influx of medicines from different sources into healthcare systems of developing countries presents a challenge to monitor their origin and quality. The absence of a repository of reference samples or spectra prevents the analysis of tablets by direct comparison. A set of paracetamol tablets purchased in Malaysian pharmacies were compared to a similar set of sample purchased in the UK using near-infrared spectroscopy (NIRS). Additional samples of products containing ibuprofen or paracetamol in combination with other actives were added to the study as negative controls. NIR spectra of the samples were acquired and compared by using multivariate modeling and classification algorithms (PCA/SIMCA) and stored in a spectral database. All analysed paracetamol samples contained the purported active ingredient with only 1 out of 20 batches excluded from the 95% confidence interval, while the negative controls were clearly classified as outliers of the set. Although the substandard products were not detected in the purchased sample set, our results indicated variability in the quality of the Malaysian tablets. A database of spectra was created and search methods were evaluated for correct identification of tablets. The approach presented here can be further developed as a method for identifying substandard pharmaceutical products.

A procedure for calibration transfer between near-infrared instruments--a worked example using a transmittance single tablet assay for piroxicam in intact tablets.

A procedure was developed for different modes of calibration transfer in near-infrared (NIR) spectroscopy, which included a method for the selection of a subset of samples appropriate for transfer. As a worked example, these guidelines were applied to the transfer of a multivariate calibration model, representing a validated NIR single tablet assay for the active within an intact pharmaceutical product, between three equivalent dispersive NIR transmission instruments. Transfer was first evaluated between two instruments, representing the situation where both were available during calibration development. A spectral correction method alone, applied to the transfer instrument, was not sufficient to facilitate transfer, with further optimisation of the calibration model using a novel wavelength selection algorithm necessary to remove regions of the spectral range that resulted in skewed predictions on the second instrument. Through this approach, a single calibration model was found to be equally accurate and precise on the two instruments. A procedure, using the Kennard-Stone algorithm, is described for determining a reduced number of samples as a transfer set using only the spectral information from the original instrument. The purpose of the subset was to permit transfer to a new instrument where that instrument was not available until after calibration development or where it was undesirable to re-measure the full sample set (i.e. due to excessive reference chemistry). Utilising the transfer set, transfer to a third instrument was evaluated. The calibration model, optimised between the first two instruments, was not directly applicable for the third instrument, with further wavelength selection required to remove a small region of spectral data. On completion, using a full statistical evaluation, a single calibration model was found to be equally accurate and precise on all three instruments.

Application of near-infrared spectroscopy to the determination of the sites of manufacture of proprietary products.

Reflectance near-infrared (NIR) spectroscopy has been investigated as a method to distinguish between the sites of manufacture of a number of proprietary tablets. As test samples, parallel imports which are pharmaceutically equivalent products manufactured at different sites have been used. Three products: Aremis/Besitran, Renitec and Voltarol Retard originating from two or more sites and Adalat from a single site were examined. The principal component analysis (PCA) score plots showed that spectra of tablets originating from different sites of manufacture often gave rise to statistically different populations. PCA loadings indicated that the differences were related to moisture content and excipients. Spectra were used to construct a library for the classification of tablets to predict the site of manufacture based on the method of residual variance of the principal components. Where a large data set was available (Aremis/Besitran tablets) prediction rates for the successful identification of the two sites of manufacture, Madrid and Barcelona, were 95.7 and 98.1%, respectively for the validation set with all errors encountered of Type I.

Optimisation of partial least squares regression calibration models in near-infrared spectroscopy: a novel algorithm for wavelength selection.

A novel optimisation algorithm is presented for full spectrum calibration models in near-infrared (NIR) spectroscopy. The algorithm is used to investigate the affect of removing continuous spectral regions on parameters critical to the validity of the model (e.g. explained variance, bias etc.) and ultimately identify and remove problem areas of the spectrum. As an example of its application, this paper shows how to optimise partial least squares regression (PLSR) calibration models for predicting moisture content within an intact pharmaceutical product and how problems due to changes in the nature of samples since setting up the original model may be eliminated. On application of two validated calibration models to a new set of samples unacceptable results were obtained for bias (-0.26 and -0.21% m/m moisture content) between the NIR predicted values and the true values (Karl Fischer analysis). The optimisation algorithm identified small regions of the spectrum, which if included in development of the models contributed significant bias to the final prediction. On removal of these problem regions the calibration models were found to be equally accurate and precise, but with the added advantage of robustness to a variable region of the sample spectrum (bias reduced to -0.05 and -0.09% m/m).

Measurement of the percentage volume particle size distribution of powdered microcrystalline cellulose using reflectance near-infrared spectroscopy.

This is the first reported method for determining the percentage volume particle size distribution of a powder (microcrystalline cellulose) by near-infrared (NIR) reflectance spectroscopy. A total of 113 samples of powdered microcrystalline cellulose were used from six different commercially available grades, with different moisture contents (range: 0.9-4.8% m/m). NIR reflectance measurements of these samples were made in narrow soda glass vials. Reference particle size data for the samples were acquired by laser diffraction. The NIR data were then calibrated to measure particle size by partial least squares regression. The effects of a range of different NIR data pre-treatments on calibration and prediction precision were investigated. Overall, simple absorbance data were found to produce regression models with the best predictive ability (root mean square error of prediction = 0.90%). The method was also found to be insensitive to moisture content.

The quantification of citral in lemongrass and lemon oils by near-infrared spectroscopy.

Previous work has demonstrated the capability of near-infrared (NIR) spectroscopy to determine the cineole content (not less than 70% w/w) of eucalyptus oil with an accuracy comparable with that of the British Pharmacopoeia (BP) assay method. The aim of the present study was to determine if the same method was capable of quantifying other chemical constituents at similar levels in essential oils and also to ascertain if NIR spectroscopy can accurately quantify compounds present at much lower levels in essential oils. Lemongrass oil contains citral at concentrations of approximately 65-85% w/w, and lemon oil contains citral at a concentration of approximately 2-5% w/w. A total of 26 samples of pure lemongrass oil and 35 samples of pure lemon oil (both including samples that were "spiked" with citral to increase the calibration range) were scanned on the FOSS NIRSystems 6500 Rapid Content Sampler using a reflectance vessel as sample presentation method. The reference method for both types of oil was the BP monograph titration assay for the citral content of lemon oil and calibrations were constructed using these reference data. For the lemongrass oils, the mean accuracy was found to be 1.00% or less and the mean bias was 0.09% or less. For the lemon oils, the mean accuracy was found to be 4.28% or less and the mean bias was -0.71% or less. The NIR method developed was rapid, simple and non-destructive and may prove beneficial for the accurate determination of the citral content of lemongrass oils and for the approximate citral content of lemon oils.

The transfer between instruments of a reflectance near-infrared assay for paracetamol in intact tablets.

This study compares several correction methods to facilitate the transfer of a validated near-infrared (NIR) assay for paracetamol in intact tablets between two reflectance NIR instruments of the same type. Transfer was defined as the ability to accurately predict the true assay value of a sample measured on a NIR system using an assay developed on a different system, and was assessed using a comprehensive set of statistical tests. Direct electronic transfer of the calibration models, representing the NIR assay, was not possible as a result of a definite residual spectrum between instruments. The use of a correction method based on the standardisation of the material used to record the reference spectrum also proved ineffective. Two methods investigated did succeed, the first employed a response surface calculated between the reflectance values of a set of six certified photometric standards measured on both instruments, with all full range partial least square (PLS) regression models subsequently transferred. The next was correction of the spectra from the second instrument utilising the residual spectrum between the mean sample of the validation set measured on both instruments. Through this approach all PLS regression models and also a single multiple linear regression (MLR) model were transferred. As an outcome of this study guidelines are suggested for the transfer of NIR assays along with the criteria deemed necessary to conclusively prove transfer and justify any correction method utilised. The significant criteria were determined to be the paired t-test with both the UV reference assay data and the original NIR assay data, and comparison of the coefficient of multiple determinations.