Comparison of near-infrared and laser-induced breakdown spectroscopy for determination of magnesium stearate in pharmaceutical powders and solid dosage forms.

Near-infrared (NIR) spectroscopy has become well established in both the pharmaceutical arena and other areas as a useful technique for rapid quantitative analysis of solid materials. Though laser-induced breakdown spectroscopy (LIBS) has not been widely applied in the pharmaceutical industry, the technique has been used for rapid quantitative analysis of solids in many other applications. One analysis amenable to each technique is the determination of magnesium stearate in solids during the lubrication blending unit operation of pharmaceutical processing. A comparative study of the utility of these two techniques for this application will be presented. Necessary sample preparations and the extent and type of matrix effects will be discussed. Additionally, it will be shown that NIR provides better accuracy and precision than LIBS with the experimental parameters used; however, LIBS showed superior selectivity as it was demonstrated to be more robust to sample matrix perturbations. Examples of blending applications will also be presented.

In-line monitoring of moisture content in fluid bed dryers using near-IR spectroscopy with consideration of sampling effects on method accuracy.

In-line near-IR moisture monitoring of the dynamic, fluid bed drying environment has been reported in recent years by several research groups; however, analytical figures of merit with regard to prediction accuracy are discussed in only a subset of this work, and issues with sampling and sample presentation are scarcely addressed at all. In this study, experiments were performed at 65-, 300-, and 600-L drying scales using several different sampling configurations in an effort to better understand and improve in-line near-IR method accuracy. Findings from this work demonstrate that process heterogeneity plays a major role in determination of apparent prediction accuracy. This aspect is general to all in-line measurements and plays an especially important role in solids and slurry systems that are prone to heterogeneity. In addition to experimental results, simulations based on these findings and sampling theory demonstrate an interesting paradox: depending on the sampling configuration employed, the method with the smallest apparent error is not necessarily optimal for process monitoring and control. Furthermore, sampling configuration influences the number of samples necessary to define an adequate calibration set. Finally, process understanding that was gained as a result of temporally rich, in-line measurements will be presented.