Impurity analysis in drug testing plays a crucial role. It can identify and control harmful impurities, ensuring drug purity, stability, and safety while guaranteeing efficacy. Currently, various techniques and methods are employed for impurity analysis, including chromatographic techniques such as ion chromatography, gas chromatography, and high-performance liquid chromatography, as well as mass spectrometry techniques like liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry, and spectrophotometric methods like UV-visible spectrophotometry. However, impurity analysis techniques face challenges, including the need to improve sensitivity and accuracy, overcome difficulties in analyzing complex sample impurities, and address method reproducibility issues. Optimizing impurity analysis involves introducing advanced techniques like ultra-high-performance liquid chromatography and chromatography-mass spectrometry, establishing standardized processes, strengthening personnel training, and utilizing artificial intelligence and automation technology. These efforts enhance drug quality control levels, ensuring safe and effective medications.
Zhong et al. (Wed,) studied this question.
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