Shaaban Heba, Mostafa Ahmed, Al-Zahrani Bushra, Al-Jasser Bushra, Al-Ghamdi Raghad
Department of Pharmaceutical Chemistry, College of Clinical Pharmacy, Imam Abdulrahman Bin Faisal University, King Faisal Road, P.O. Box 1982, Dammam 31441, Saudi Arabia.
J Anal Methods Chem. 2020 Feb 11;2020:1684172. doi: 10.1155/2020/1684172. eCollection 2020.
The quality of medications is important to maintain the overall health care of patients. This study aims to develop and validate a spectrophotometric method using multivariate curve resolution-alternating least squares (MCR-ALS) with correlation constraint for simultaneous resolution and quantification of selected drugs affecting the central nervous system (imipramine, carbamazepine, chlorpromazine, haloperidol, and phenytoin) in different pharmaceutical dosage forms. Figures of merit such as root-mean-square error of prediction, bias, standard error of prediction, and relative error of prediction for the developed method were calculated. High values of correlation coefficients ranged between 0.9993 and 0.9998 reflected high predictive ability of the developed method. The results are linear in the concentration range of 0.3-5 g/mL for carbamazepine, 0.3-15 g/mL for chlorpromazine, 0.5-10 g/mL for haloperidol, 0.5-10 g/mL for imipramine, and 3-20 g/mL for phenytoin. The optimized method was successfully applied for the analysis of the studied drugs in their pharmaceutical products without any separation step. The optimized method was also compared with a reported HPLC method using Student's test and ratio at 95% confidence level, and the results showed no significant difference regarding accuracy and precision. The proposed chemometric method is fast, reliable, and cost-effective and can be used as an eco-friendly alternative to chromatographic techniques for the analysis of the studied drugs in commercial pharmaceutical products.
药物质量对于维持患者的整体医疗保健至关重要。本研究旨在开发并验证一种采用具有相关约束的多元曲线分辨-交替最小二乘法(MCR-ALS)的分光光度法,用于同时分辨和定量不同药物剂型中影响中枢神经系统的选定药物(丙咪嗪、卡马西平、氯丙嗪、氟哌啶醇和苯妥英)。计算了所开发方法的预测均方根误差、偏差、预测标准误差和预测相对误差等品质因数。相关系数的高值在0.9993至0.9998之间,反映了所开发方法的高预测能力。结果表明,卡马西平在0.3 - 5 μg/mL浓度范围内呈线性,氯丙嗪在0.3 - 15 μg/mL浓度范围内呈线性,氟哌啶醇在0.5 - 10 μg/mL浓度范围内呈线性,丙咪嗪在0.5 - 10 μg/mL浓度范围内呈线性,苯妥英在3 - 20 μg/mL浓度范围内呈线性。该优化方法成功应用于所研究药物制剂的分析,无需任何分离步骤。还将该优化方法与报道的高效液相色谱法在95%置信水平下进行了学生t检验和F检验比较,结果表明在准确性和精密度方面无显著差异。所提出的化学计量学方法快速、可靠且具有成本效益,可作为一种环保的替代色谱技术,用于分析市售药品中的所研究药物。