Process Development , Amgen Inc. , One Amgen Center Drive , Thousand Oaks , California 91320 , United States.
Anal Chem. 2019 Apr 16;91(8):5252-5260. doi: 10.1021/acs.analchem.9b00027. Epub 2019 Apr 4.
A major challenge of a mass-spectrometry-based quantitative multiattribute method (MAM) for biotherapeutics is its high variability between instruments. For reproducible attribute measurements, not only is a similar instrument model required, but the instruments must also be tuned to the same condition. This poses great long-term challenges, considering the rapid development of new instrumentations. In addition, differences in digestion efficiency, peptide recovery, and artificial modifications during sample preparation also contribute to variability between laboratories. To overcome these challenges, new mathematical methods are developed to calculate the attribute abundance in the sample, using the reference standard (RS) material as calibrant. Most quality attributes in the RS remain constant throughout the life of the standard, and therefore, the RS can serve as a calibrant to correct for the difference between instruments or sample preparation procedures. Because RS data are usually collected in a MAM assay, no additional work is required from the analyst. Data from a large number of attributes demonstrated that these methodologies greatly reduced instrument-to-instrument and sample preparation variabilities. With these methodologies, a consistent instrument model and sample preparation procedure is no longer a requirement. As a result, changes in digestion procedure and advances in instrumentations will not significantly affect the assay result.
基于质谱的生物治疗剂定量多属性方法(MAM)的主要挑战是仪器之间的高度变异性。为了实现可重复的属性测量,不仅需要类似的仪器模型,而且还必须将仪器调整到相同的条件。考虑到新仪器的快速发展,这带来了巨大的长期挑战。此外,在样品制备过程中消化效率、肽回收率和人为修饰的差异也会导致实验室之间的差异。为了克服这些挑战,开发了新的数学方法来计算样品中属性的丰度,使用参考标准(RS)材料作为校准剂。在标准的整个生命周期中,RS 中的大多数质量属性保持不变,因此,RS 可以作为校准剂来校正仪器或样品制备程序之间的差异。因为 RS 数据通常在 MAM 测定中收集,所以分析师不需要额外的工作。大量属性的数据表明,这些方法大大降低了仪器之间和样品制备的变异性。有了这些方法,一致的仪器模型和样品制备程序不再是必需的。因此,消化程序的变化和仪器的进步不会对测定结果产生显著影响。