This study aims to develop a rapid and non-destructive method to identify counterfeit and substandard drugs, addressing the critical need for better quality control in drug production. According to the reasons for counterfeit products in actual production, the commonly used solid preparation excipients such as HPMC, MCC, Mg-St and Pregelatinized Starch, as well as three chemical drugs with similar efficacy to Guizhi-Fuling (GZFL) Capsule as adulterants, including Aspirin, Ibuprofen and Sinomenine Hydrochloride were selected and designed as adulteration samples with different levels of adulteration. NIR spectra were collected in a non-invasive mode and analyzed by one-class classification methods. The feasibility of using Near-infrared (NIR) spectroscopy as a detection method to qualitatively identify adulterated samples was explored at three packaging levels of powder, intact capsules and capsules in PVC. The differences between the samples were analyzed by NIR spectra comparison, cluster analysis and principal component analysis. The performance of SVM, OCPLS and DD-SIMCA models in dealing with the authentication of genuine and counterfeit products was established and compared. The results show that the spectra contain sample information and the adulterated samples could be discriminated correctly by established models. Moreover, applying appropriate spectral preprocessing methods can further improve the model's performance. In addition, a PLS regression model was developed to predict the adulteration levels of the three packing level samples, which yielded satisfactory results. This study highlights the potential of NIR spectroscopy combined with Chemometrics as a rapid and non-destructive testing analysis method to accurately identify counterfeit and substandard drugs, thereby ensuring drug quality.
Keywords: Adulteration discrimination; Chemometrics; Guizhi-Fuling Capsule; Near-infrared spectroscopy.
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