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OBJECTIVE To develop and validate a peptide mapping method of an anti-CD33 monoclonal antibody. METHODS Different types of chromatographs (HPLC, UPLC) and different mobile phase systems (formic acid, trifluoroacetic acid) were used for peptide map detection of anti-CD33 antibody. The signature peptide segments were localized using synthetic CDR peptide of the antibody and the localization results were confirmed by mass spectrometry. Based on the relative retention time (RRT), the specificity, precision, and robustness of the method were validated according to the Pharmacopoeia of the People's Republic of China (ChP, 2020). RESULTS The separation time of the peptides by UPLC was shorter than that by HPLC, and the degrees of separation with trifluoroacetic acid in the mobile phase were higher than that with formic acid. The identification results of the signature peptide segment using the maps of synthetic peptide segments were consistent with the results of mass spectrometry. The specificity validation demonstrated that the formulation blank and sample solution blank did not interfere with the detection of signature peptide segments, and there were significant differences between peptide mapping results of different antibodies. The repeatability validation showed that the RSDs (RRT) of signature peptide segments between six parallel samples were 0.01%-0.05%; the intermediate precision validation proved that the RSDs (RRT) of signature peptide segments for different analysts were 0.04%-0.32%; the robustness validation exhibited that the RSDs (RRT) of signature peptide segments were 0.02%-0.09% under different enzyme treatment conditions and 0.36%-1.43% under different chromatographic conditions. Within 25 h in detection, the RSDs (RRT) of the signature peptide segments were 0.01%-0.04%. CONCLUSION This study uses synthetic peptide segments for peptide localization in peptide mapping detection and uses relative retention time to determine the results, which provide a new approach for biopharmaceutical peptide mapping detection.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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