目的 以丹参注射液为研究对象，建立基于¹H-NMR指纹图谱分区相似度的质量一致性评价方法。方法 采集81批丹参注射液的¹H-NMR光谱，根据代谢物信号的分布规律，将光谱分为氨基酸区、糖类区和酚酸区，分别计算各区光谱的夹角余弦与标准化欧氏距离2种相似度指标，并评价丹参注射液批次质量一致性的性能，并与基于全¹H-NMR谱的相似度计算结果进行对比。结果 不同批次丹参注射液间氨基酸、糖类及酚酸的组成均存在一定差异，其中氨基酸、糖类的批间差异较大；同时，欧式距离对成分的批间波动更为敏感。此外，基于全谱的相似度分析结果受糖区特征峰影响极大，对酚酸及氨基酸类成分的批间差异辨识能力较差。结论 基于¹H-NMR光谱分区相似度计算法可以更好地辨识不同类别成分的批间波动，较全谱相似度计算法更适用于丹参注射液的一致性评价，为进一步提升中药制剂的质量一致性提供参考。

Objective To establish a quality consistency evaluation method for Danshen Injection (丹参注射液) based on the similarity of sectionalized ¹H-NMR fingerprint. Methods The ¹H-NMR spectra of 81 batches of Danshen Injection were obtained. According to the distribution of various metabolite signals, the spectra were sectionalized into three regions, which were the amino acid region, sugar region, and phenolic acid region, respectively. Then, cosine similarities and standardized Euclidean distances of each region for each spectrum were calculated respectively as the consistency evaluation indexes for Danshen Injection. In addition, the evaluation method results aforementioned was compared with the similarity calculation results based on the full ¹H-NMR spectra. Results The results showed that certain fluctuations did exist in the composition of amino acids, carbohydrates, and phenolic acids among different batches of Danshen Injection. Among them, the differences in amino acids and carbohydrates between batches were bigger than those in phenolic acids. At the same time, the Euclidean distance was a more sensitive index to the metabolite fluctuations than cosine similarity. In addition, similarity analysis based on the full ¹H-NMR spectrum was significantly affected by the sugar region, and so its ability to distinguish differences in phenolic acids and amino acids was weak. Conclusion Similarities based on sectionalized ¹H-NMR spectra can identify the fluctuations of different types of metabolites better. The method proposed in this study is more appropriate for quality control of Danshen Injection than that based on full-spectrum, which will help to provide reference ideas for further improving the quality control level of traditional Chinese medicine preparations.

R283.6

国家“重大新药创制”科技重大专项（2018ZX09201011-002）