Laboratory of Analytical Chemistry, CIRM, University of Liège, 1 Avenue de l'Hôpital, 4000 Liège, Belgium.
Talanta. 2010 Mar 15;80(5):1750-7. doi: 10.1016/j.talanta.2009.10.019. Epub 2009 Oct 17.
A robust near infrared (NIR) method able to quantify the active content of pilot non-coated pharmaceutical pellets was developed. A protocol of calibration was followed, involving 2 operators, independent pilot batches of non-coated pharmaceutical pellets and two different NIR acquisition temperatures. Prediction models based on Partial Least Squares (PLS) regression were then carried out. Afterwards, the NIR method was fully validated for an active content ranging from 80 to 120% of the usual active content using new independent pilot batches to evaluate the adequacy of the method to its final purpose. Conventional criteria such as the R(2), the Root Mean Square Error of Calibration (RMSEC), the Root Mean Square Error of Prediction (RMSEP) and the number of PLS factors enabled the selection of models with good predictive potential. However, such criteria sometimes fail to choose the most fitted for purpose model. Therefore, a novel approach based on accuracy profiles of the validation results was used, providing a visual representation of the actual and future performances of the models. Following this approach, the prediction model using signal pre-treatment Multiplicative Scatter Correction (MSC) was chosen as it showed the best ability to quantify accurately the active content over the 80-120% active content range. The reliability of the NIR method was tested with new pilot batches of non-coated pharmaceutical pellets containing 90 and 110% of the usual active content, with blends of validation batches and industrial batches. All those batches were also analyzed by the HPLC reference method and relative errors were calculated: the results showed low relative errors in full accordance with the results obtained during the validation of the method, indicating the reliability of the NIR method and its interchangeability with the HPLC reference method.
开发了一种能够定量测定非包衣制药丸中活性成分含量的稳健近红外（NIR）方法。该方法遵循校准方案，涉及 2 名操作人员、独立的非包衣制药丸中试批次和两种不同的 NIR 采集温度。然后，基于偏最小二乘（PLS）回归进行预测模型的建立。之后，使用新的独立中试批评估方法的最终目的，对活性成分在通常活性成分的 80%至 120%范围内的 NIR 方法进行了全面验证。常规标准，如 R²、校正均方根误差（RMSEC）、预测均方根误差（RMSEP）和 PLS 因子数量，能够选择具有良好预测潜力的模型。然而，这些标准有时无法选择最适合目的的模型。因此，采用了一种基于验证结果准确度分布的新方法，为模型的实际和未来性能提供了直观的表示。采用信号预处理多元散射校正（MSC）的预测模型，能够在 80-120%的活性成分范围内准确地定量测定活性成分，显示出最佳的能力，因此被选为首选模型。采用新的非包衣制药丸中试批次（含 90%和 110%的通常活性成分）、验证批次和工业批次的混合物对 NIR 方法的可靠性进行了测试。所有批次均采用 HPLC 参考方法进行分析，并计算相对误差：结果表明，相对误差较低，完全符合方法验证期间获得的结果，表明 NIR 方法的可靠性及其与 HPLC 参考方法的可互换性。
