Drug detection and identification technology are of great significance in drug supervision and management. To determine the exact source of drugs, it is often necessary to directly identify multiple varieties of drugs produced by multiple manufacturers. Near-infrared spectroscopy (NIR) combined with chemometrics is generally used in these cases. However, existing NIR classification modeling methods have great limitations in dealing with a large number of categories and spectra, especially under the premise of insufficient samples, unbalanced samples, and sensitive identification error cost. Therefore, this paper proposes a NIR multi-classification modeling method based on a modified Bidirectional Generative Adversarial Networks (Bi-GAN). It makes full utilization of the powerful feature extraction ability and good sample generation quality of Bi-GAN and uses the generated samples with obvious features, an equal number between classes, and a sufficient number within classes to replace the unbalanced and insufficient real samples in the courses of spectral classification. 1721 samples of four kinds of drugs produced by 29 manufacturers were used as experimental materials, and the results demonstrate that this method is superior to other comparative methods in drug NIR classification scenarios, and the optimal accuracy rate is even more than 99% under ideal conditions.

Rifampicin is a first-line anti-tuberculosis drug. However, in August 2020, the presence of 1-methyl-4-nitrosopiperazine (MNP), a nitrosamine impurity, was detected by the United Stated Food and Drug Administration (US FDA) in rifampicin capsules. Consequently, the development of efficient methods for the detection of MNP is an important objective. In this study, the MNP present in rifampicin capsules was detected using LC-MS/MS. A total of 27 batches from nine manufacturers in the Chinese market were tested, with MNP (0.33–2.36 ppm) being detected in all samples at levels exceeding the maximum acceptable intake limit of 0.16 ppm initially set by the FDA. However, after considering the associated benefits and risks, the FDA-approved limit was revised to 5 ppm; hence, all the samples examined herein exhibited MNP levels well below the required limit. Furthermore, the results of forced degradation experiments suggest that MNP is formed by the thermal degradation of rifampicin.

Objective: To prepare and validate the chemical structure of the cefotaxime dimer and cefotaxime trimer impurities available from pharmaceutical industry.Methods: A polymer stock solution of cefotaxime sodium was obtained using a concentrated solution degradation method. The cefotaxime dimer and trimer impurities were separated and purified by preparative reversed-high-performance liquid chromatograph (RP-HPLC), and the pure cefotaxime dimer and trimer were obtained by a freeze-drying method. The two impurities were characterized by infrared (IR) spectroscopy, ultraviolet (UV) spectroscopy, mass spectroscopy, and nuclear magnetic resonance (NMR, including one-dimensional and two-dimensional NMR). The groups corresponding to the characteristic absorption peaks in the UV and IR spectra were analyzed, and the ¹H and ¹³C NMR signals were assigned.Results: The cefotaxime dimer was isolated and purified from the actual sample of industrial medicines, and chemical structure of the dimer is the same as in the dimers investigated earlier. The polymerization sites and stereoscopic configuration of trimer impurity was validated for the first time.Conclusion: This study is of great significance for the study of the structures and quality control of polymer impurities in cephalosporin drugs. Promoting the polymerization sites study and providing a technical basis for allergic study of polymer impurities.