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Updated: Jul 6, 2026

Application and Methodology of the Non-destructive 19F Time-domain NMR Technique to Measure the Content in Fluorine-containing Drug Products
Published on: August 22, 2017
Content uniformity determination of pharmaceutical tablets using five near-infrared reflectance spectrometers: a
Yusuf Sulub1, Rosario LoBrutto, Richard Vivilecchia
1Analytical Research and Development, Novartis Pharmaceutical Corporation, East Hanover, NJ 07936, United States. yusuf.sulub@novartis.com
Abstract:
Near-infrared calibration models were developed for the determination of content uniformity of pharmaceutical tablets containing 29.4% drug load for two dosage strengths (X and Y). Both dosage strengths have a circular geometry and the only difference is the size and weight. Strength X samples weigh approximately 425 mg with a diameter of 12 mm while strength Y samples, weigh approximately 1700 mg with a diameter of 20mm. Data used in this study were acquired from five NIR instruments manufactured by two different vendors. One of these spectrometers is a dispersive-based NIR system while the other four were Fourier transform (FT) based. The transferability of the optimized partial least-squares (PLS) calibration models developed on the primary instrument (A) located in a research facility was evaluated using spectral data acquired from secondary instruments B, C, D and E. Instruments B and E were located in the same research facility as spectrometer A while instruments C and D were located in a production facility 35 miles away. The same set of tablet samples were used to acquire spectral data from all instruments. This scenario mimics the conventional pharmaceutical technology transfer from research and development to production. Direct cross-instrument prediction without standardization was performed between the primary and each secondary instrument to evaluate the robustness of the primary instrument calibration model. For the strength Y samples, this approach was successful for data acquired on instruments B, C, and D producing root mean square error of prediction (RMSEP) of 1.05, 1.05, and 1.22%, respectively. However for instrument E data, this approach was not successful producing an RMSEP value of 3.40%. A similar deterioration was observed for the strength X samples, with RMSEP values of 2.78, 5.54, 3.40, and 5.78% corresponding to spectral data acquired on instruments B, C, D, and E, respectively. To minimize the effect of instrument variability, calibration transfer techniques such as piecewise direct standardization (PDS) and wavelet hybrid direct standardization (WHDS) were used. The PDS approach, the RMSEP values for strength X samples were lowered to 1.22, 1.12, 1.19, and 1.08% for instruments B, C, D, and E, respectively. Similar improvements were obtained using the WHDS approach with RMSEP values of 1.36, 1.42, 1.36, and 0.98% corresponding to instruments B, C, D, and E, respectively.
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