Department of Chemistry, Science College, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh 11451, Saudi Arabia.
Molecules. 2023 Oct 12;28(20):7044. doi: 10.3390/molecules28207044.
The classical least squares (CLS) model and three augmented CLS models are adopted and validated for the analysis of pyridoxine HCl (PYR), cyclizine HCl (CYC), and meclizine HCl (MEC) in a quinary mixture with two related impurities: the CYC main impurity, Benzhydrol (BEH), which has carcinogenic and hepatotoxic effects, and the MEC official impurity, 4-Chlorobenzophenone (BEP). The proposed augmented CLS models are orthogonal signal correction CLS (OSC-CLS), direct orthogonal signal correction CLS (DOSC-CLS), and net analyte processing CLS (NAP-CLS). These models were applied to quantify the three active constituents in their raw materials and their corresponding dosage forms using their UV spectra. To evaluate the CLS-based models sensibly, we design a comparative study involving two sets: the training set to construct models and the validation set to assess the prediction abilities of these models. A five-level, five-factor calibration design was established to produce 25 mixtures for the calibration set. In addition, 16 experiments were performed for a test set distributed equally between the in-space and out-space samples. The primary criterion for comparing the models' performance was the validation set's root mean square error of prediction (RMSEP) value. Finally, augmented CLS models showed acceptable results for assaying the three analytes. The results were compared statistically with the reported HPLC methods; however, the DOSC-CLS model proved the best for assaying the dosage forms.
采用经典最小二乘法 (CLS) 模型和三种增强型 CLS 模型，对包含两种相关杂质的五元混合物中的盐酸吡哆醇 (PYR)、盐酸环嗪 (CYC) 和盐酸美西律 (MEC) 进行分析，这两种杂质分别为：CYC 的主要杂质苯甲醇 (BEH)，它具有致癌和肝毒性；MEC 的官方杂质 4-氯二苯甲酮 (BEP)。所提出的增强型 CLS 模型是正交信号校正 CLS (OSC-CLS)、直接正交信号校正 CLS (DOSC-CLS) 和净分析物处理 CLS (NAP-CLS)。这些模型用于使用它们的紫外光谱定量分析三种原料药及其相应剂型中的三种活性成分。为了合理评估基于 CLS 的模型，我们设计了一项包括两组的对比研究：一组用于构建模型的训练集，另一组用于评估这些模型的预测能力的验证集。建立了一个五水平、五因素的校准设计，为校准集生成 25 种混合物。此外，还进行了 16 项实验，其中测试集在空间内和空间外样本之间平均分布。比较模型性能的主要标准是验证集的预测均方根误差 (RMSEP) 值。最后，增强型 CLS 模型在测定三种分析物方面表现出可接受的结果。结果与报道的 HPLC 方法进行了统计学比较；然而，DOSC-CLS 模型在测定剂型方面表现最佳。
