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Esmolol hydrochloride injection is indicated for the rapid control of ventricular rate in patients with atrial fibrillation or atrial flutter in perioperative, postoperative, or other emergent circumstances where short term control of ventricular rate with a short-acting agent is desirable. The potential toxic impurities in pharmaceuticals at micro levels or trace levels are of increasing concern to both pharmaceutical industries and regulatory agencies, due to their potential risk to human health. The impurity investigation of esmolol remains incomplete. Thereby, efficient impurities monitoring and potential toxicity assessment should be emphasized to assure drug safety. Impurity profiling methods of esmolol were developed using ultraperformance liquid chromatography plus Q-Exactive Orbitrap tandem mass spectrometry (UPLC-QE-MS) based multiple mass defect filter and chemometrics. Impurities were characterized by both UPLC-QE-MS and reference substance comparison. The toxicities of esmolol impurities were predicted by employing quantitative structure–activity relationship. The results showed that a total of 20 impurities were detected and identified using the above integrated strategy, 14 impurities (EP2-3, EP5-6, EP8-9, EP12-13, EP15-20) have firstly found. EP20 was predicted as hepatotoxic and mutagenic using QSAR model, and its hepatotoxicity were verified in vivo. The EP1 contents showed maximum volatility in all batches, and varied by sample. EP1 and its accompanying product of methanol were measured. This UPLC-MS/MS based chemometrics strategy is useful for monitoring the manufacturing process and quality control of esmolol hydrochloride injection.

Quality control of traditional Chinese medicine (TCM) should be linked with the authentication and efficacy of TCM. Selaginella tamariscina is a frequently used traditional Chinese herbal medicine. However, its quality control is still difficult due to its multiple adulterants. We established quality markers (Q-markers) of S. tamariscina by using metabolomics, molecular networking and network pharmacology to improve the authenticity study and quality control of S. tamariscina. In this study, ultra high performance liquid chromatography-mass spectrum (UHPLC-MS) coupled with multivariate statistical analyses was applied to distinguish between S. tamariscina samples and their confusing adulterants. Principal component analysis, hierarchical clustering analysis (PCA), hierarchical clustering analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were employed to screen the distinguishing markers from S. tamariscina samples and their adulterants. The top-2 distinguishing markers were isolated from S. tamariscina and identified by molecular networking together with nuclear magnetic resonance spectroscopy (NMR). Network pharmacology predicted the bioactivity and cytotoxicity of the top-2 distinguishing markers. The top-2 distinguishing markers were adopted as Q-markers of S. tamariscina for content determination. Based on the results of ultra performance liquid chromatography-quardrupole-time of flight mass spectrometry (UHPLC-QTOF-MS) metabolomics, we revealed that selaginellins could only be detected in S. tamariscina samples and contributed greatly to discriminating S. tamariscina samples from their confused species. The top-2 distinguishing markers were isolated and purified from S. tamariscina extract. Then, they were further identified as selaginellin and selaginellin A by molecular networking and NMR. Network pharmacology predicted the antitumor activity of selaginellin and selaginellin A, while the cytotoxicity assay verified their bioactivity. In conclusion, selaginellin and selaginellin A were selected as Q-markers for the determination and quality evaluation of S. tamariscina based on ultra performance liquid chromatography-triple quadrupole tandem mass spectrometry (UHPLC-QQQ-MS). The ranges of the concentrations of selaginellin and selaginellin A were 41.57–44.89 μg/g and 15.09–16.75 μg/g, respectively. This study provides a novel strategy combining Ultra performance liquid chromatography mass spectrometry based (UHPLC-MS-based) metabolomics with molecular networking for rapid species identification of S. tamariscina and discovery of the Q-markers of TCM.