Sulub Yusuf, LoBrutto Rosario, Vivilecchia Richard, Wabuyele Busolo Wa
Analytical Research and Development, Novartis Pharmaceutical Corporation, East Hanover, NJ 07936, United States.
Anal Chim Acta. 2008 Mar 24;611(2):143-50. doi: 10.1016/j.aca.2008.02.016. Epub 2008 Feb 16.
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.
针对两种规格（X和Y）、含药量为29.4%的药片片剂含量均匀度测定，开发了近红外校准模型。两种规格片剂均为圆形，唯一区别在于尺寸和重量。X规格样品重约425毫克，直径12毫米；Y规格样品重约1700毫克，直径20毫米。本研究中使用的数据来自两家不同供应商生产的五台近红外仪器。其中一台光谱仪是基于色散的近红外系统，另外四台是基于傅里叶变换（FT）的。使用从二级仪器B、C、D和E获取的光谱数据，评估在位于研究机构的主仪器（A）上开发的优化偏最小二乘（PLS）校准模型的可转移性。仪器B和E与光谱仪A位于同一研究机构，而仪器C和D位于35英里外的生产机构。使用同一组片剂样品从所有仪器获取光谱数据。这种情况模拟了从研发到生产的传统制药技术转移。在主仪器和各二级仪器之间进行未经标准化的直接跨仪器预测，以评估主仪器校准模型的稳健性。对于Y规格样品，这种方法对于在仪器B、C和D上获取的数据是成功的，预测均方根误差（RMSEP）分别为1.05%、1.05%和1.22%。然而对于仪器E的数据，这种方法不成功，RMSEP值为3.40%。对于X规格样品也观察到类似的恶化情况，对应于在仪器B、C、D和E上获取的光谱数据，RMSEP值分别为2.78%、5.54%、3.40%和5.78%。为了最小化仪器变异性的影响，使用了校准转移技术，如分段直接标准化（PDS）和小波混合直接标准化（WHDS）。采用PDS方法时，X规格样品在仪器B、C、D和E上的RMSEP值分别降至1.22%、1.12%、1.19%和1.08%。使用WHDS方法也获得了类似的改进，对应于仪器B、C、D和E的RMSEP值分别为1.36%、1.42%、1.36%和0.98%。
