TOF-SIMS analysis of exhaled particles from patients with asthma and healthy controls.

Particles in exhaled air (PEx) may reflect the composition of respiratory tract lining fluid (RTLF); thus, there is a need to assess their potential as sources of biomarkers for respiratory diseases. In the present study, we compared PEx from patients with asthma and controls using time-of-flight-secondary ion mass spectrometry (TOF-SIMS) and multivariate analysis. Particles were collected using an instrument developed in-house. 15 nonsmoking subjects with physician-diagnosed asthma and 11 nonsmoking healthy controls performed 10 consecutive forced exhalations into the instrument. Particle concentrations were recorded and samples of particles collected on silicon plates were analysed by TOF-SIMS. Subjects with asthma exhaled significantly lower numbers of particles than controls (p=0.03) and the ratio of unsaturated to saturated phospholipids was significantly lower in samples from subjects with asthma (0.25 versus 0.35; p=0.036). Orthogonal partial least squares-discriminant analysis models showed good separation between both positive and negative spectra. Molecular ions from phosphatidylcholine and phosphatidylglycerol, and protein fragments were found to discriminate the groups. We conclude that analysis of PEx is a promising method to examine the composition of RTLF. In the present explorative study, we could discriminate between subjects with asthma and healthy controls based on TOF-SIMS spectra from PEx.

The synthesis of metoprolol monitored using Raman spectroscopy and chemometrics.

The synthesis of Metoprolol base was studied using Raman spectroscopy with a 785-nm laser, optical fibres, a holographic transmission grating, confocal optics and a charge-coupled device (CCD) detector. The reaction mixture was heated according to a temperature gradient and spectra of the reaction mixture were obtained by focusing the laser beam through ordinary reaction flasks. Because of overlapping bands, multivariate techniques such as principal components analysis (PCA) and partial least-squares projections to latent structures (PLS) were used in the evaluation of the obtained spectra. The use of PCA or PLS against time does not require any calibration samples and a quantitative calibration is not necessary in order to monitor the reaction. A method for reaction endpoint determination, based on euclidean distances in the score space, is presented. The use of multivariate batch control charts have been demonstrated and a number of problems and solutions regarding the sample presentation have been discussed. The effect of spectral pretreatment on the multivariate results is shown and discussed. The monitoring results show that the time to produce Metoprolol base could be reduced.

Multicomponent analysis: a case report.

Three cases are described. Case 1: kinetic studies often need high time resolution measurements in order to follow the pattern of reactions taking place during the experiment. This is often laborious to achieve with the collection of fractions for chromatographic separation. Some tool for separation is, however, necessary in order to decompose the concentrations of reactants, products and intermediate species. The spectra of the intermediates may not be known at the time when the kinetic studies are needed. With unknown spectra there are still possibilities to use spectroscopy and multivariate techniques to obtain qualitative information. Case 2: it is possible to use Partial Least Squares (PLS) in order to describe the chromatographic profiles for the species even if the separation is insufficient for traditional peak measurement methods. This requires that mixtures are available with known concentrations of the species to be determined. Case 3: with modern diode array liquid chromatography detectors there is the possibility to capture the chromatogram and the spectra at the same time. The ability to reproduce the chromatographic profile between samples makes it possible to use the Generalized Rank Annihilation Method (GRAM) possible. Whereas PLS only treats one spectrum at a time, this method treats the full two-dimensional chromatogram as an entity. The GRAM calibration is claimed to be insensitive to interfering species which are not present in the calibration. Limitations are that GRAM requires a linear detector response and very good repeatability of the retention time. The use of GRAM for calibration with real samples is demonstrated.

Monitoring of a film coating process for tablets using near infrared reflectance spectrometry.

A process analytical chemical method using near infrared diffuse reflectance spectrometry was developed for the determination of the amount of tablet coating on single tablets. This method is based on calibration of the spectra versus the added mass of coating solution. The tablet core was composed of two halves of different chemical composition and spectra were recorded from both sides of the tablets. The calibration was carried out using the chemometric methods principal component analysis (PCA), partial least squares (PLS), and multiplicative signal correction (MSC). The PLS-model utilised spectra obtained from both sides, pretreated with MSC, and ordered into one object. This method can be used in process analytical chemistry at-line. Additional characterisation of the measurements was obtained by calibrating the spectra versus coating thicknesses obtained from optical microscopy. Using PCA, it was possible to roughly estimate the maximum depth in the coating material that returns chemical information, the 'information depth', which was 0.1-0.2 mm.

Vibrational spectrometry for the assessment of active substance in metoprolol tablets: a comparison between transmission and diffuse reflectance near-infrared spectrometry.

Near-infrared spectrometry (NIR) was used to quantify metroprolol succinate in controlled release tablets. Metoprolol tablets were made according to an experimental design using different strengths around a central strength of 47.5 mg per tablet. A comparison was made between NIR in the diffuse reflectance mode and the transmission mode. This showed that, although a narrower wavelength range was available in the transmission mode, predictions were much better for models based on transmission spectra than for models based on diffuse reflectance spectra. The main reason for this is that in the reflectance mode NIR spectrometry is very sensitive to the inhomogeneity of the material, while in the transmission mode this problem is less severe. This is due to the larger volume of the material scanned in the transmission mode compared to that in diffuse reflectance. Spectra were taken before and after the tablets were stored under humid conditions. This allowed the final calibration models to be made more robust towards variations in the amount of water in the tablet. Different batches of metoprolol pellets and microcrystalline cellulose were used during the production of the tablets. this resulted in models that were more robust towards possible batch-to-batch differences in the main constituents.

Multivariate evaluation of doxorubicin surface-enhanced Raman spectra.

Multivariate evaluation of surface-enhanced Raman spectra of doxorubicin in plasma was performed. In a principal component analysis (PCA) all spectral features were modelled into three principal components. The major variation of the data was shown to be the variation of doxorubicin Raman signal together with the doxorubicin fluorescence, whereas the variation due to plasma was of minor importance. It was also shown that the surface-enhanced Raman scattering (SERS) measurements were independent on such factors as measurement occasion and silver colloids. The presented results show that with some improvements, quantification of doxorubicin directly in plasma could be possible.

Internal standard in surface-enhanced Raman spectroscopy.

A method is presented for the use of SAM layers as internal standards for calibration in surface-enhanced Raman spectroscopy. Three cyano-containing compounds were attached to gold colloids via a metal-sulfur bond and evaluated for spectral stability and normalization capacity. The results show that the analyte, rhodamine 6G, and the internal standard signal enhancement covaried, and it was possible to quantify the analyte with PLS. The fact that the enhancing substrate was chaotic assemblies with large variation in signal enhancement shows the versatility of this method.

Quantitative analysis of film coating in a fluidized bed process by in-line NIR spectrometry and multivariate batch calibration.

A method is described which enables real-time analysis of film coating on pharmaceutical pellets during an industrial manufacturing process. Measurements were conducted on the solid particulate material by near-infrared (NIR) spectrometry utilizing a diffuse reflectance fiber-optic probe positioned inside a fluidized bed process vessel. Time series of NIR spectra from 11 batches generated a three-way data matrix that was unfolded and modeled by partial least squares (PLS) in a multivariate batch calibration. The process conditions were deliberately varied according to an experimental design. This yielded good predictability of the coating thickness with a best model fit, R2 = 0.97, for one PLS-projection, and a root-mean-square error of calibration = 2.2 microm (range tested 0-50 microm). The regression vector was shown to be highly influenced by responses that are both direct (aliphatic C-H stretch overtones) and indirect (aromatic C-H stretch overtones), from film component and core material, respectively. The impact of different data pre-treatment methods on the normalization of the regression vector is reported. Justification of the process calibration approach is emphasized by good correlation between values predicted from NIR data and reference image analysis data on dissected pellets and a theoretical nonlinear coating thickness growth model. General aspects of in-line NIR on solids and multivariate batch calibration are discussed.