Near-infrared spectroscopy is evaluated as an on-line technique for monitoring the homogeneity of a pharmaceutical blend during the blending process. Blends containing 10% sodium benzoate (model active), which provided an aromatic functionality typical of many pharmaceutical compounds, 39% microcrystalline cellulose (Avicel PH102), 50% lactose, and 1% magnesium stearate were developed to mimic the properties of an actual pharmaceutical blend. A twin-shell V-blender was modified to allow installation of a diffuse reflectance fiber-optic probe at the axis of rotation, and spectra were collected during three experiments using a commercially available near-infrared spectrophotometer. In each experiment, blender control and spectral data collection were controlled by a compilation of software packages. The experiments detected spectral changes which eventually converged to a point of constant variance. Further analysis of the spectral data showed the blend is homogeneous long before a typical blending period is complete. Near-infrared spectroscopy has proven to be a feasible and effective method for the "real time" noninvasive determination of homogeneity in a pharmaceutical blend.

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The synthesis of three chiral calixarene derivatives is described. One of these, an (S)-di-2-naphthylprolinol tetramer, is shown to exhibit significant ability to discriminate between enantiomers of 1-phenylethylamine (PEA) and norephedrine on the basis of the quenching of the (S)-di-2-naphthylprolinol fluorescence emission in chloroform. The chiral discrimination appears to arise from preorganization of the four (S)-di-2-naphthylprolinol substituents on the calixarene, which define a three-dimensional chiral space. The ability to measure the enantiomeric composition of PEA and norephedrine to within an error of 4.1% and 2.6%, respectively, on the basis of a single fluorescence measurement is demonstrated.

Powder blending was monitored on-line by taking near-infrared measurements at regular time intervals during the mixing process. The average standard deviation between the measurements taken at each time and the dissimilarity between each mixture spectrum and the ideal mixture spectrum were used to monitor the changes in the powder blend over time. The distribution of the pure compounds in the blend can be investigated by looking at the score plot for the first two principal components (PCs), the contribution of each variable to the dissimilarity and, in particular, the contrasts between two characteristic wavelengths for each compound. Statistical process monitoring charts were used to determine the blending time at which the mixture was within (spectroscopic) specifications. Shewhart charts monitor the blend at characteristic wavelengths for each substance separately. The Hotelling's T2 test defines a multivariate confidence interval. For spectral data, feature reduction is needed. This procedure is accomplished by using characteristic wavelengths for the pure compounds or the significant PCs after performing principal components analysis (PCA).

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