(116aa) Analysis of Low Content Drug Tablets by Transmission near Infrared Spectroscopy. Selection of Calibration Ranges According to Multivariate Detection and Quantitation Limits of PLS Models

Near infrared spectroscopy (NIR) may be used to support the design and optimization of potent drug manufacturing processes through the analysis of blends and tablets, saving significant amounts of time. This study uses a strategy for the selection of concentration ranges in the development of multivariate calibration by evaluating the detection and quantitation limits of the multivariate models created. This strategy has been applied to pharmaceutical tablets of low concentrations ranging from 5.0% to 0.02% (w/w). Multiple formulations were created for each concentration level and varied in the proportion of lactose and cellulose, in order to break the correlation of excipients among them and increase ruggedness. Transmission NIR spectra were obtained for tablets of each different concentration level. The spectra were recorded in a multipurpose analyzer (MPA) Fourier transform near infrared (FT-NIR) spectrometer (Bruker Optics, Billerica, MA) equipped with a room temperature-indium gallium arsenide (RT-InGaAs) external detector positioned above the tablet. Each spectrum was an average of 128 scans at a resolution of 16 cm-1. The models included the spectral range from 11,216 to 8,030 cm-1, where ibuprofen shows most of its bands. In the models created, quantitation and detection limits decreased significantly as the concentration range of the calibration models was narrowed. Only 2 to 4 PLS factors were needed to explain the high variance (<99%). All the calibration models allowed the determination of the drug content with error of less than 7% (RSEP). Via multivariate detection and quantitation limit analysis, very robust models can be obtained. For the quantitation of analytes at minor levels (< 1% w/w), the selection of wide concentration ranges is not recommended. NIR can be used effectively to detect and quantify low drug content in pharmaceutical formulations.