Extending Calibrations for Near Infrared Assay of Tablets Using Synthetic Modeling and Variance from Placebos

The authors extend the range of a near-infrared calibration model for tablet assay using production 'seed' spectra and synthetic spectra generated from placebos and 'pure' active pharmaceutical ingredient spectra.
Mar 02, 2009
Volume 33, Issue 3

The US Food and Drug Administration initiative for process analytical technology (PAT) has created interest in measuring pharmaceutical products upstream during processing for better quality and process control (1). Near infrared (NIR) spectroscopy has been a major analytical tool designated for PAT analysis because it is fast, accurate, nondestructive and requires no sample preparation. At-line solid dosage form analysis has become important for tablet assay and content uniformity because pharmaceutical manufacturers would like to measure more frequently than the 10 tablets per batch specified by US Pharmacopeia General Chapter ‹905› on content uniformity.

Laboratory methods for tablet assay and content uniformity are routinely performed with high-performance liquid chromatography (HPLC) and are usually time-consuming because they require lengthy calibration runs, the mixing of buffers, and the procurement and disposal of hazardous solvents. The analysis of 10 tablets for content uniformity could take hours and the results may not be available to the tablet press operators or for batch release for many days or even weeks after the tablets are compressed.

Figure 2
NIR spectroscopic analysis is an empirically based technique that requires the prediction method developer to analyze a calibration set of samples that represent the natural variation in the solid dosage form (2). It is often difficult to obtain the proper range of samples that would include slightly more than ±15% of the label claim. The process produces tablets normally distributed around the label claim, and the model developer cannot obtain tablets that are more than a few percent away from the nominal value. Therefore, to empirically develop a prediction model that can predict samples that may be ±15% of the label claim without extrapolation, synthetic methods are investigated.

Figure 3
This article discusses a method of obtaining a prediction method that uses only placebo tablets and samples containing an active pharmaceutical ingredient (API) from the product line. The natural variation range in the product line is extended with synthetic samples created by adding varying amounts of the pure-active spectrum to the placebos. Purely synthetic spectra lack the scattering variance of real tablets and would not create a robust prediction model. The placebos, which are often available from clinical studies, provide the real scattering and spectral variance seen in a calibration set.

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