Raman spectroscopy as a process analytical technology (PAT) tool for the in-line monitoring and understanding of a powder blending process.

The aim of this study is to propose a strategy to implement a PAT system in the blending step of pharmaceutical production processes. It was examined whether Raman spectroscopy can be used as PAT tool for the in-line and real-time endpoint monitoring and understanding of a powder blending process. A screening design was used to identify and understand the significant effects of two process variables (blending speed and loading of the blender) and of a formulation variable (concentration of active pharmaceutical ingredient (API): diltiazem hydrochloride) upon the required blending time (response variable). Interactions between the variables were investigated as well. A Soft Independent Modelling of Class Analogy (SIMCA) model was developed to determine the homogeneity of the blends in-line and real-time using Raman spectroscopy in combination with a fiber optical immersion probe. One blending experiment was monitored using Raman and NIR spectroscopy simultaneously. This was done to verify whether two independent monitoring tools can confirm each other's endpoint conclusions. The analysis of the experimental design results showed that the measured endpoints were excessively rounded due to the large measurement intervals relative to the first blending times. This resulted in effects and critical effects which cannot be interpreted properly. To be able to study the effects properly, the ratio between the blending times and the measurement intervals should be sufficiently high. In this study, it anyway was demonstrated that Raman spectroscopy is a suitable PAT tool for the endpoint control of a powder blending process. Raman spectroscopy not only allowed in-line and real-time monitoring of the blend homogeneity, but also helped to understand the process better in combination with experimental design. Furthermore, the correctness of the Raman endpoint conclusions was demonstrated for one process by using a second independent endpoint monitoring tool (NIR spectroscopy). Hence, the use of two independent techniques for the control of one response variable not only means a mutual confirmation of both methods, but also provides a higher certainty in the determined endpoint.

Influence of particle size on the quantitative determination of salicylic acid in a pharmaceutical ointment using FT-Raman spectroscopy.

A second order polynomial calibration model was developed and statistically validated for the direct and non-destructive quantitative analysis - without sample preparation - of the active pharmaceutical ingredient (API) salicylic acid in a pharmaceutical ointment using FT-Raman spectroscopy. The calibration curve was modeled by plotting the peak intensity of the vector normalized spectral band between 757 and 784cm(-1) against the known salicylic acid concentrations in standards. At this band, no spectral interferences from the ointment vehiculum (white vaseline) are observed. For the validation of the polynomial model, its fit and its predictive properties were evaluated. The validated model was used for the quantification of 25 ointments, compounded by different retail pharmacists. The same standards and samples were used, both for development and validation of a regression model and for quantitative determination by HPLC - with sample preparation - as described for the related substances of salicylic acid in the Ph. Eur. IV. The quantification results obtained by the FT-Raman method corresponded with the HPLC results (p=0.22), provided that the particle size of salicylic acid in the standards is the same as in the analyzed samples. The non-destructive FT-Raman method is a reliable alternative for the destructive HPLC method, as it is faster and does not require sample pre-treatment procedures.

Increasing conclusiveness of metabonomic studies by chem-informatic preprocessing of capillary electrophoretic data on urinary nucleoside profiles.

Nowadays, bioinformatics offers advanced tools and procedures of data mining aimed at finding consistent patterns or systematic relationships between variables. Numerous metabolites concentrations can readily be determined in a given biological system by high-throughput analytical methods. However, such row analytical data comprise noninformative components due to many disturbances normally occurring in analysis of biological samples. To eliminate those unwanted original analytical data components advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. The electrophoretic nucleoside profiles were obtained under following conditions: 100 mM borate, 72.5 mM phosphate, 160 mM SDS, pH 6.7; 25 kV voltage, 30 degrees C temperature; untreated fused silica capillary 70 cm effective length, 50 microm I.D. Different most advanced preprocessing tools were applied for baseline correction, denoising and alignment of electrophoretic data. That approach was compared to standard procedure of electrophoretic peak integration. The best results of preprocessing were obtained after application of the so-called correlation optimized warping (COW) to align the data. The principal component analysis (PCA) of preprocessed data provides a clearly better consistency of the nucleoside electrophoretic profiles with health status of subjects than PCA of peak areas of original data (without preprocessing).

A comparison of three algorithms for chromatograms alignment.

In this paper the performance of three alignment algorithms, correlation optimized warping, parametric time warping and semi-parametric time warping, is compared on real chromatograms. Among these, parametric time warping is the simplest and fastest; generally less than 1s is required to align two chromatograms. It does not require the optimization of input parameters and allows the alignment of peak shifts in only one direction, or non-complex peak shifts in both directions. With correlation optimized warping and semi-parametric time warping complex peak shifts in both directions can be corrected but at the expense of the optimization of two input parameters. Semi-parametric time warping requires the selection of the proper number of B-splines in the warping function and, if necessary, the optimization of the penalty parameter. Often the default values can be used to obtain aligned signals. The optimization of the input parameters for correlation optimized warping (section length, slack) is not easy and time-consuming. Moreover, dependent on the input parameters, the computation time of the correlation optimized warping algorithm can be twice as long as for semi-parametric time warping for which computation times up to 23 s are required. However, the performance of both algorithms is equally good considering the improvement of the precision of the peak retention times and correlation coefficients between the chromatograms, after alignment. For the data aligned in this study, the average retention time precision and the lowest correlation before warping were 14 and 0.17, and were improved to three and 0.83, and six and 0.87 after warping, with correlation optimized warping and semi-parametric time warping, respectively.

Evaluation of chemometric techniques to select orthogonal chromatographic systems.

Several chemometric techniques were compared for their performance to determine the orthogonality and similarity between chromatographic systems. Pearson's correlation coefficient (r) based color maps earlier were used to indicate selectivity differences between systems. These maps, in which the systems were ranked according to decreasing or increasing dissimilarities observed in the weighted-average-linkage dendrogram, were now applied as reference method. A number of chemometric techniques were evaluated as potential alternative (visualization) methods for the same purpose. They include hierarchical clustering techniques (single, complete, unweighted-average-linkage, centroid and Ward's method), the Kennard and Stone algorithm, auto-associative multivariate regression trees (AAMRT), and the generalized pairwise correlation method (GPCM) with McNemar's statistical test. After all, the reference method remained our preferred technique to select orthogonal and identify similar systems.

Orthogonality and similarity within silica-based reversed-phased chromatographic systems.

The starting point of this study was a current set of 32 chromatographic systems used to select initial conditions for method development to determine the impurity profile of a drug. The system exhibiting the best selectivity is then selected for further method development. In this current set eight silica-based phases are applied in conjunction with four mobile phases at different pH. In order to save time and resources, the possibilities for a meaningful subset selection were investigated. The most differing systems in terms of selectivity, in other words only the most orthogonal systems, need to be selected. Since the stationary phases are all silica-based, the selectivity differences are examined within a more homogeneous group than if, for instance, also zirconia- or polymer-based columns would be involved. To select the subset of systems also the best overall separation performances are taken into account. The selection is based both on the HPLC-DAD data of a generic set of 68 drugs, and on the LC-MS-DAD results for a mixture of 15 drugs, less different in structure. The orthogonality is evaluated using weighted-average-linkage dendrograms and color maps, both created from the Pearson-correlation coefficients r between normalized retention times r. The Derringer's desirability functions are applied to define the systems with the best overall separation performances. Proposals for different representative subsets of the initial 32 systems are made.

Enantioselective capillary electrophoretic separation of tryptophane- and tyrosine-methylesters in a dual system with a tetra-oxadiaza-crown-ether derivative and a cyclodextrin.

Different dual selector systems containing a cyclodextrin derivative (methyl-beta-cyclodextrin and dimethyl-beta-cyclodextrin) and a new diaza-crown-ether derivative (N-[2-(1,4,10,13-tetraoxa-7,16-diazacyclooctadecan-7-yl)propanoyl]glycine) were studied in the enantioselective separation of tryptophan-methylester and tyrosine-methylester enantiomers. This paper deals with the systematic study of the effects of changing the composition of the background electrolyte on the resolution of the d- and l- forms using an experimental design approach. It was found that the dual systems allowed a better chiral separation of the amino acid derivatives. The experimental design approach also allowed improving the separation compared to the starting conditions (center point of the design), which were adopted from a previous study.

Classification of drugs in absorption classes using the classification and regression trees (CART) methodology.

Classification and regression trees (CART) were evaluated for their potential use in a quantitative structure-activity relationship (QSAR) context. Models were build using the published absorption values for 141 drug-like molecules as response variable and over 1400 molecular descriptors as potential explanatory variables. Both the role of two- and three-dimensional descriptors and their relative importance were evaluated. For the used dataset, CART models showed high descriptive and predictive abilities. The predictive abilities were evaluated based on both cross-validation and an external test set. Application of the variable ranking method to the models showed high importances for the n-octanol/water partition coefficient (logP) and polar surface area (PSA). This shows that CART is capable of selecting the most important descriptors, as known from the literature, for the absorption process in the intestinal tract.

Inclusion complexation of diazepam with different cyclodextrins in formulations for parenteral use.

A parenteral formulation for the water-insoluble benzodiazepine diazepam was developed. Different cyclodextrins (CDs) suitable for parenteral injection: hydroxypropyl-beta-cyclodextrin (HP-beta-CD), hydroxy-propyl-gamma-cyclodextrin (HP-gamma-CD), sulfobutylether-7-beta-cyclodextrin (SBE-7-beta-CD) and maltosyl-beta-cyclodextrin (malt-beta-CD) were used as alternatives to cosolvents to increase solubility. The increase in solubility displayed a concentration dependency for the four CDs used. Diazepam's solubility is enhanced linearly as a function of each CD concentration. The highest improvements in solubility (dissolved concentration circa 3.5 mg/ml in 40% CD) were found by adding HP-beta-CD or SBE-7-beta-CD. The additional use of polyvinylpyrrolidone (PVP) did not further increase the solubility of diazepam with HP-beta-CD. A parenteral aqueous diazepam solution was prepared containing 10 mg diazepam/5 ml 30% HP-beta-CD or SBE-7-beta-CD solution. The preparations are in agreement with the requirements for parenteralia. Sterilisation by filtration is required since autoclaving degrades the active compound. The stability of the preparations, with and without pH adjustment to pH 5, was investigated during 18 months and during this period no noticeable degradation was observed.

Evaluation of size-exclusion chromatography and size-exclusion electrochromatography calibration curves.

Size-exclusion chromatography (SEC) and size-exclusion electrochromatography (SEEC) are chromatographic techniques used to determine molecular mass (weight) distributions (MWD) of polymers. One important step in the data treatment to derive MWD parameters is the modelling of the calibration curves. The calibration curves applied in SEC and SEEC are generally not linear. In this study the modelling of calibration curves is being examined. Different polynomial models have been evaluated and compared, not only for model fit but also for their predictive properties. It was found that sometimes a straight line and sometimes a third-order polynomial model were best. The best model across the effective range (also called linear range) is not always found to be a straight line. The SEEC curves were found to have considerably higher prediction errors than the SEC ones. Reduction of the number of calibration standards to five or six did not greatly affect the predictive properties of the calibration curves, neither in SEC nor in SEEC.

Screening approach for chiral separation of pharmaceuticals part II. Reversed-phase liquid chromatography.

A screening strategy for the rapid separation of drug enantiomers by reversed-phase liquid chromatography was developed using three cellulose/amylose stationary phases. The key point to achieve enantioselectivity is the control of the compound ionisation. Only two mobile phases, i.e. an acidic phosphate buffer (pH 2.0) containing a chaotropic salt (KPF6) and a borate buffer (pH 9.0) mixed with acetonitrile, are used in the proposed strategy. This strategy was successfully applied to a set of 37 diverse chiral pharmaceuticals. Satisfactory enantioselectivity was achieved for 89% of them.

Potential antioxidant compounds in Mallotus species fingerprints. Part II: fingerprint alignment, data analysis and peak identification.

Some Mallotus species are commonly used as traditional medicine (TM) ingredients in Vietnam and China, but only a few are studied for their activities. In Part I, high-performance liquid chromatography (HPLC) fingerprints of 39 Mallotus samples (17 species) were developed and, because of the complexity of and the large differences between the samples, it was chosen to analyse the unaligned fingerprints. The peaks, potentially responsible for the antioxidant activity in given Mallotus species, were indicated by the regression coefficients from an orthogonal projections to latent structures (O-PLS) model. In the present study, an in depth discussion on the need for alignment of the Mallotus fingerprints for the indication of the potentially active compounds is made, as well as an experimental analysis and identification of the previously indicated peaks by HPLC-mass spectrometry (HPLC-MS). Additionally, to thoroughly study and discuss the alignment problem, the modelling and prediction of the antioxidant activity of green tea samples based on HPLC fingerprints were also considered.

Direct orthogonal signal correction as data pretreatment in the classification of clinical lots of creams from near infrared spectroscopy data.

Direct orthogonal signal correction (DOSC) is applied to correct for major variance sources such as temperature effects, time influences and instrumental differences in near infrared (NIR) data. The samples analysed are creams containing different concentrations of an active drug. The final aim is to classify the samples according to their concentration of active compound. Having performed DOSC on the data, it is not necessary anymore to apply sophisticated chemometric techniques to correct for temperature or time effects and to attribute the samples to their respective concentration classes. Moreover, the application of DOSC on the NIR spectra recorded on two different instruments shows that this method can be considered as a valuable alternative for the standardisation in classification applications. Since the applied algorithm tends to overfit, in a second part of this paper, a comparison is made with an algorithm designed by Westerhuis, which should overcome this problem. Although the calibration set results show that the overfitting has been partially corrected for by the latter algorithm, the test set results did not improve significantly.

Implementation of a process analytical technology system in a freeze-drying process using Raman spectroscopy for in-line process monitoring.

The aim of the present study was to propose a strategy for the implementation of a Process Analytical Technology system in freeze-drying processes. Mannitol solutions, some of them supplied with NaCl, were used as models to freeze-dry. Noninvasive and in-line Raman measurements were continuously performed during lyophilization of the solutions to monitor real time the mannitol solid state, the end points of the different process steps (freezing, primary drying, secondary drying), and physical phenomena occurring during the process. At-line near-infrared (NIR) and X-ray powder diffractometry (XRPD) measurements were done to confirm the Raman conclusions and to find out additional information. The collected spectra during the processes were analyzed using principal component analysis and multivariate curve resolution. A two-level full factorial design was used to study the significant influence of process (freezing rate) and formulation variables (concentration of mannitol, concentration of NaCl, volume of freeze-dried sample) upon freeze-drying. Raman spectroscopy was able to monitor (i) the mannitol solid state (amorphous, alpha, beta, delta, and hemihydrate), (ii) several process step end points (end of mannitol crystallization during freezing, primary drying), and (iii) physical phenomena occurring during freeze-drying (onset of ice nucleation, onset of mannitol crystallization during the freezing step, onset of ice sublimation). NIR proved to be a more sensitive tool to monitor sublimation than Raman spectroscopy, while XRPD helped to unravel the mannitol hemihydrate in the samples. The experimental design results showed that several process and formulation variables significantly influence different aspects of lyophilization and that both are interrelated. Raman spectroscopy (in-line) and NIR spectroscopy and XRPD (at-line) not only allowed the real-time monitoring of mannitol freeze-drying processes but also helped (in combination with experimental design) us to understand the process.