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Updated: Jun 3, 2026

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
Published on: November 8, 2019
Blend uniformity end-point determination using near-infrared spectroscopy and multivariate calibration
Yusuf Sulub1, Michele Konigsberger, James Cheney
1Technical Research and Development, Novartis Pharmaceuticals Corporation, One Health Plaza, East Hanover, NJ 07936, United States. yusuf.sulub@novartis.com
Abstract:
A multivariate calibration approach using near-infrared (NIR) spectroscopy for determining blend uniformity end-point of a pharmaceutical solid dosage form containing 29.4% (w/w) drug load with three major excipients (crospovidone, lactose, and microcrystalline cellulose) is presented. A set of 21 off-line, static calibration samples were used to develop a multivariate partial least-squares (PLS) calibration model for on-line predictions of the API content during the blending process. The concentrations of the API and the three major excipients were varied randomly to minimize correlations between the components. A micro-electrical-mechanical-system (MEMS) based NIR spectrometer was used for this study. To minimize spectral differences between the static and dynamic measurement modes, the acquired NIR spectra were preprocessed using standard normal variate (SNV) followed by second derivative Savitsky-Golay using 21 points. The performance of the off-line PLS calibration model were evaluated in real-time on 67 production scale (750L bin size) blend experiments conducted over 3 years. The real-time API-NIR (%) predictions of all batches ranged from 93.7% to 104.8% with standard deviation ranging from 0.5% to 1.8%. These results showed the attainment of blend homogeneity and were confirmed with content uniformity by HPLC of respective manufactured tablets values ranging from 95.4% to 101.3% with standard deviation ranging from 0.5% to 2.1%. Furthermore, the performance of the PLS calibration model was evaluated against off-target batches manufactured with high and low amounts of water during the granulation phase of production. This approach affects the particle size and hence blending. All the off-target batches exhibited API-NIR (%) predictions of 94.6% to 103.5% with standard deviation ranging from 0.7% to 1.9%. Using off-target data, a systematic approach was developed to determine blend uniformity end-point. This was confirmed with 3 production scale batches whereby the blend uniformity end-point was determined using the PLS calibration model. Subsequently, the uniformity was also ascertained with conventional thief sampling followed by HPLC analysis and content uniformity by HPLC of the manufactured tablets.
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