Classification of washing powder brands using near-infrared spectroscopy combined with chemometric calibrations.

In this study, near-infrared (NIR) spectroscopy is applied for rapid and objective classification of 5 different brands of washing powder. Chemometric calibrations including partial least square discriminant analysis (PLS-DA), back propagation neural network (BP-NN) and least square support vector machine (LS-SVM) are investigated and compared to achieve an optimal result. Firstly, principal component analysis (PCA) is conducted to visualize the difference among washing powder samples of different brands and principal components (PCs) are extracted as inputs of BP-NN and LS-SVM models. The number of PCs and parameters of such models are optimized via cross validation. In experimental studies, a total of 225 spectra of washing powder samples (45 samples for each brand) were used to build models and 75 spectra of washing powder samples (15 samples for each brand) were used as the validation set to evaluate the performance of developed models. As for the comparison of the three investigated models, both BP-NN model and LS-SVM model successfully classified all samples in validation set according to their brands. However, the PLS-DA model failed to achieve 100% of classification accuracy. The results obtained in this investigation demonstrate that NIR spectroscopy combined with chemometric calibrations including BP-NN and LS-SVM can be successfully utilized to classify the brands of washing powder.

The use of colloid probe microscopy to predict aerosolization performance in dry powder inhalers: AFM and in vitro correlation.

The atomic force microscope (AFM) colloid probe technique was utilized to measure cohesion forces (separation energy) between three drug systems as a function of relative humidity (RH). The subsequent data was correlated with in vitro aerosolization data collected over the same RH range. Three drug-only systems were chosen for study; salbutamol sulphate (SS), triamcinolone acetonide (TAA), and di-sodium cromoglycate (DSCG). Analysis of the AFM and in vitro data suggested good correlations, with the separation energy being related inversely to the aerosolization performance (measured as fine particle fraction, FPF(LD)). In addition, the relationship between, cohesion, RH, and aerosolization performance was drug specific. For example, an increase in RH between 15% and 75% resulted in increased cohesion and decreased FPF(LD) for SS and DSCG. In comparison, for TAA, a decrease in cohesion and increased FPF(LD) was observed when RH was increased (15-75%). Linear regression analysis comparing AFM with in vitro data indicated R(2) values > 0.80, for all data sets, suggesting the AFM could be used to indicate in vitro aerosolization performance.

A review of the terms agglomerate and aggregate with a recommendation for nomenclature used in powder and particle characterization.

The terms "agglomerate" and "aggregate" are widely used by powder technologists to describe assemblages of particles that are found in dry powders and powders in liquid suspensions. Each term has a specific meaning but, unfortunately, they are frequently interchanged at will and this has resulted in universal confusion. This confusion is perpetuated by conflicting definitions in national and international standards and this presents problems when describing powder properties or communicating results in reports and research papers. This paper reviews the current status of the definitions, with particular emphasis on their use in the pharmaceutical industry. It is proposed that just one term, agglomerate, should be used to describe an assemblage of particles in a powder and that the term aggregate should be confined to pre-nucleation structures.