Laboratory of Drug Analysis, Scientific Institute of Public Health, Brussels, Belgium.
Anal Chim Acta. 2011 Sep 9;701(2):224-31. doi: 10.1016/j.aca.2011.05.041. Epub 2011 Jun 22.
Most of the counterfeit medicines are manufactured in non good manufacturing practices (GMP) conditions by uncontrolled or street laboratories. Their chemical composition and purity of raw materials may, therefore, change in the course of time. The public health problem of counterfeit drugs is mostly due to this qualitative and quantitative variability in their formulation and impurity profiles. In this study, impurity profiles were treated like fingerprints representing the quality of the samples. A total of 73 samples of counterfeit and imitations of Viagra(®) and 44 samples of counterfeit and imitations of Cialis(®) were analysed on a HPLC-UV system. A clear distinction has been obtained between genuine and illegal tablets by the mean of a discriminant partial least squares analysis of the log transformed chromatograms. Following exploratory analysis of the data, two classification algorithms were applied and compared. In our study, the k-nearest neighbour classifier offered the best performance in terms of correct classification rate obtained with cross-validation and during external validation. For Viagra(®), both cross-validation and external validation sets returned a 100% correct classification rate. For Cialis(®) 92.3% and 100% correct classification rates were obtained from cross-validation and external validation, respectively.
大多数假药都是在非良好生产规范（GMP）条件下，由不受控制或街头实验室生产的。因此，其原材料的化学组成和纯度可能会随时间而变化。假药的公共卫生问题主要是由于其制剂和杂质谱的定性和定量可变性。在本研究中，杂质谱被视为代表样品质量的指纹。总共分析了 73 个假冒伟哥（Viagra(®)）和 44 个假冒希爱力（Cialis(®)）的样品，使用 HPLC-UV 系统进行分析。通过对对数转换的色谱图进行判别偏最小二乘分析，可以清楚地区分真假片剂。对数据进行探索性分析后，应用并比较了两种分类算法。在我们的研究中，k-最近邻分类器在交叉验证和外部验证时的正确分类率方面表现出最佳性能。对于伟哥（Viagra(®)），交叉验证和外部验证集的正确分类率均达到 100%。对于希爱力（Cialis(®)），交叉验证和外部验证分别获得了 92.3%和 100%的正确分类率。
