Application of near-infrared spectroscopy and class-modeling to antibiotic authentication

Nowadays, counterfeit medicines have become very popular due to the extension of the Internet. Broad-spectrum antibiotics with similar effect, but different prices, provide a gold opportunity for illegal traders to counterfeit. It is found that some genuine packaging of expensive brand drugs are recycled and then used to refill other kinds of cheap antibiotic tablets. It is of great importance to establish an effective antibiotic authentication method to check whether a product with a specific claim on its label is compatible with that declaration. In the present work, the feasibility of near-infrared (NIR) spectroscopy coupled with class-modeling for antibiotics authentication, i.e., counterfeiting between different antibiotics, is investigated. A total of 591 antibiotics samples of nine classes of different dosage forms were collected. Principal component analysis (PCA) was used for exploratory analysis. An effective model-independent filter method, i.e., relief, was used for feature selection and a novel class-modeling algorithm was used to construct authentication models. Three kinds of antibiotics were used as the target classes for experiments. The results confirmed that such a scheme is feasible and can be used in the screening of fake drug.