Analytical Sciences, Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Analytical Sciences, Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, Maryland, USA.
J Pharm Biomed Anal. 2021 May 10;198:113988. doi: 10.1016/j.jpba.2021.113988. Epub 2021 Feb 24.
The multi-attribute method (MAM) based on liquid chromatography (LC)-tandem mass spectrometry is emerging as a powerful tool to directly monitor multiple product quality attributes simultaneously. To better implement MAM, either for product characterization or for quality control (QC), there is a need for a robust, universal, and high-throughput workflow that can be broadly adopted in different laboratories with minimal barriers to implementation. Manual preparation of samples for MAM, however, is labor intensive and produces nontrivial variations across analysts and laboratories. We describe the development of a fully automated peptide mapping procedure with a high-throughput robotic liquid handling system to improve sample handling capacity and outcome reproducibility while saving analyst hands-on time. Our procedure features the automation of a "microdialysis" step, an efficient desalting approach prior to proteolytic digestion that optimizes digestion completeness and consistency each time. The workflow is completely hands-free and requires the analyst only to pre-normalize the sample concentrations and to load buffers and reagents at their designated positions on the robotic deck. The robotic liquid handler performs all the subsequent preparation steps and stores the digested samples on a chiller unit to await retrieval for further analysis. We also demonstrate that the manual and automated procedures are comparable with regard to protein sequence coverage, digestion completeness and consistency, and quantification of posttranslational modifications. Notably, in contrast to a previously reported automated sample preparation protocol that relied on customized accessories, all components in our automation procedure are commercial products that are readily available. In addition, we also present the high-throughput data analysis workflow by using Protein Metrics. The automation procedure can be applied cross-functionally in the biopharmaceutical industry and, given its practicality and reproducibility, can pave the way for MAM implementation in QC laboratories.
基于液相色谱（LC）-串联质谱的多属性方法（MAM）正在成为一种强大的工具，可用于直接同时监测多个产品质量属性。为了更好地实施 MAM，无论是用于产品表征还是质量控制（QC），都需要一种稳健、通用且高通量的工作流程，该流程可以在不同的实验室中广泛采用，实施门槛低。然而，MAM 的手动样品制备既费力又会导致分析人员和实验室之间产生显著差异。我们描述了一种使用高通量机器人液体处理系统的全自动肽图分析程序的开发，以提高样品处理能力和结果重现性，同时节省分析人员的手工操作时间。我们的程序具有“微透析”步骤的自动化功能，这是一种在酶解之前进行高效脱盐的方法，每次都能优化酶解的完全性和一致性。该工作流程完全无需人工干预，仅需要分析人员预先对样品浓度进行归一化，并在机器人甲板上的指定位置加载缓冲液和试剂。机器人液体处理机执行所有后续的制备步骤，并将消化后的样品存储在冷却器单元中，以备进一步分析。我们还证明了手动和自动程序在蛋白质序列覆盖率、酶解完全性和一致性以及翻译后修饰的定量方面具有可比性。值得注意的是，与之前报道的依赖定制附件的自动化样品制备方案相比，我们自动化程序中的所有组件均为商业产品，随时可用。此外，我们还展示了使用 Protein Metrics 的高通量数据分析工作流程。该自动化程序可以在生物制药行业中跨功能应用，并且由于其实用性和重现性，可以为 QC 实验室中的 MAM 实施铺平道路。
