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A near-infrared (NIR) spectroscopic method based on the use of a fiber optical probe for the analysis of a commercially available pharmaceutical preparation is proposed. The analyte is identified by comparison with a second-derivative spectral library, using the correlation coefficient as the discriminating parameter. Once a sample has been positively identified, the active principle is quantified with partial least-squares (PLS) calibration. The proposed method was validated for use as a control method; to this end, the selectivity of the identification process, and the repeatability, intermediate precision, accuracy, linearity, and robustness of the active principle quantitation, were assessed.

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Production batch samples of paracetamol tablets and specially prepared out-of-specification batches covering the range 90-110% of the stated amount (500 mg) were analysed by the BP official UV assay and by NIR transmittance spectroscopy. NIR measurements were made on 20 intact tablets from each batch, scanned five times each (10 min measurement time per batch) over the spectral range 6000-11,520 cm-1. An average spectrum was calculated for each batch. Partial least squares (PLS) regression models were set up using a calibration set (20 batches) between the NIR response and the reference tablet paracetamol content (UV). Various pre-treatments of the spectra were examined; the smallest relative standard error of prediction (0.73%) was obtained using the first derivative of the absorbance over the full spectrum. Only two principal components were required for the PLS model to give a good relationship between the spectral information and paracetamol content. Applying this model to the validation set (15 batches) gave a mean bias of -0.08% and a mean accuracy of 0.59% with relative standard deviations of 0.75 and 0.44%, respectively. The proposed method is non-destructive and therefore lends itself to on-line/at-line production control purposes. The method is easy to use and does not require a knowledge of the mass of the tablets.