To ensure a high quality pharmaceutical product, the concentration of active pharmaceutical ingredient (API) must be monitored. Near infrared spectroscopy (NIRS) has been previously used to effectively quantify API concentration in tablets. NIRS is a non-destructive, and cost-effective technique that provides physical and chemical information with a single measurement. Multivariate analysis and proper selection of representative samples are essential for the construction of accurate calibration models from NIR spectra. The development of the calibration set should meet the following two criteria: possess the same characteristics as the samples to be predicted, and include all potential variability. In this work, we compared the effectiveness of two methodologies to obtain the calibration set: pilot plant samples and calculation/addition of the process spectrum. The models were evaluated in terms of lowest root mean square error of prediction (RMSEP), and in terms of bias and repeatability. The process spectrum enables the incorporation of all sources of variability, undergone by the samples in each step of the production process, into the calibration set. This method was used to develop partial least squares (PLS) models without using a reference method to quantify API concentration. The model constructed with 3 factors exhibited good predictive ability (RMSEP=3.56 % w/w), with a bias of -0.83 % (w/w).

Development of NIRS calibration models for pharmaceutical quality control analysis

253rd National Meeting (2017)

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