US Food and Drug Administration, Center for Drug Evaluation and Research, Division of Pharmaceutical Analysis, St. Louis, Missouri 63101, USA.
Appl Spectrosc. 2011 Mar;65(3):334-41. doi: 10.1366/10-05976.
The transfer of a multivariate calibration model for quantitative determination of diethylene glycol (DEG) contaminant in pharmaceutical-grade glycerin between five portable Raman spectrometers was accomplished using piecewise direct standardization (PDS). The calibration set was developed using a multi-range ternary mixture design with successively reduced impurity concentration ranges. It was found that optimal selection of calibration transfer standards using the Kennard-Stone algorithm also required application of the algorithm to multiple successively reduced impurity concentration ranges. Partial least squares (PLS) calibration models were developed using the calibration set measured independently on each of the five spectrometers. The performance of the models was evaluated based on the root mean square error of prediction (RMSEP), calculated using independent validation samples. An F-test showed that no statistical differences in the variances were observed between models developed on different instruments. Direct cross-instrument prediction without standardization was performed between a single primary instrument and each of the four secondary instruments to evaluate the robustness of the primary instrument calibration model. Significant increases in the RMSEP values for the secondary instruments were observed due to instrument variability. Application of piecewise direct standardization using the optimal calibration transfer subset resulted in the lowest values of RMSEP for the secondary instruments. Using the optimal calibration transfer subset, an optimized calibration model was developed using a subset of the original calibration set, resulting in a DEG detection limit of 0.32% across all five instruments.
使用分段直接标准化（PDS）方法，实现了将用于定量测定医药级甘油中二甘醇（DEG）污染物的多元校准模型从五台便携式拉曼光谱仪之间转移。使用多范围三元混合物设计，成功地减少了杂质浓度范围，开发了校准集。研究发现，使用 Kennard-Stone 算法对校准转移标准进行最佳选择，还需要将该算法应用于多个逐渐降低的杂质浓度范围。使用在五台光谱仪上独立测量的校准集开发了偏最小二乘（PLS）校准模型。根据使用独立验证样本计算得出的预测均方根误差（RMSEP）评估模型的性能。F 检验表明，在不同仪器上开发的模型之间未观察到方差存在统计学差异。在单一主仪器和四个辅助仪器之间进行了无需标准化的直接仪器间交叉预测，以评估主仪器校准模型的稳健性。由于仪器变异性，次级仪器的 RMSEP 值显著增加。使用最优校准转移子集的分段直接标准化应用导致次级仪器的 RMSEP 值最低。使用最优校准转移子集，使用原始校准集的子集开发了优化的校准模型，使得所有五台仪器的 DEG 检测限均为 0.32%。
