Novel Native Reversed-Phase Liquid Chromatography (nRPLC)/MS for Antibody–Drug Conjugates (ADCs) Characterization and Drug–Antibody Ratio (DAR) Assessment

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Fengfei Ma*, A. Carl Sanchez, James Song, Esther Kofman, Daniela Tomazela, Laurence Fayadat-Dilman, Kanaka Hettiarachchi and Mohammad Ahmed Al-Sayah, 
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引用次数: 0

Abstract

Characterization of drug–antibody ratio (DAR) species in antibody–drug conjugates (ADCs) is crucial for assessing the developability/manufacturability and downstream development of drug candidates. Although hydrophobic interaction chromatography (HIC) is the gold standard for DAR analysis, elucidating DAR species within each HIC peak has historically been challenging. This is due to the nonvolatility and high ionic strength of conventional buffer systems, which necessitate labor-intensive offline fractionation, followed by MS analysis. To address these challenges, an innovative alternative strategy has been developed that directly couples native reversed-phase liquid chromatography (nRPLC) to high-resolution Orbitrap MS for online native MS analysis (nRPLC-MS). In collaboration with Phenomenex, two types of columns, each with a different hydrophobicity, were developed, allowing for elution with low concentration of MS-friendly salt and organic buffer. LC and MS parameters were optimized to enhance the detection of intact DAR species under high flow rate conditions. To demonstrate the feasibility of the platform for characterizing different types of ADCs, both interchain-linked (heterogeneous DAR of 0 to 8) and site-specific ADCs were evaluated. The method enables the nondenatured separation and simultaneous characterization of different DAR species, and strong correlation was observed between this approach and analysis by HIC. This integrated strategy allows unbiased characterization of DAR species without postcolumn flow splitting or peak fractionation. Furthermore, comparisons with two commonly used methods (native SEC-MS and RPLC-MS) have shown that superior separation in terms of selectivity and resolution is achieved with the nRPLC method. Notably, unconjugated antibody (DAR0) was successfully retained with a low-ionic-strength salt using this method. Moreover, the method facilitated the chromatographic separation of positional isomers of DAR4 species with different conjugation linkages, which was not achievable with traditional HIC. As a result, this method holds great promise for high-throughput screening and characterization of ADCs across conjugation methods and payload classes.

Abstract Image

用于抗体药物共轭物 (ADC) 表征和药物抗体比 (DAR) 评估的新型原生反相液相色谱 (nRPLC)/MS
抗体-药物偶联物(adc)中药物-抗体比(DAR)物种的表征对于评估候选药物的可开发性/可制造性和下游开发至关重要。尽管疏水相互作用色谱(HIC)是DAR分析的金标准,但在每个HIC峰中阐明DAR物种一直具有挑战性。这是由于传统缓冲体系的非挥发性和高离子强度,这需要劳动密集型的离线分馏,然后进行质谱分析。为了应对这些挑战,研究人员开发了一种创新的替代策略,将天然反相液相色谱(nRPLC)与高分辨率Orbitrap质谱直接耦合,用于在线天然质谱分析(nRPLC-MS)。与Phenomenex合作,开发了两种类型的柱,每种柱具有不同的疏水性,允许用低浓度的ms友好盐和有机缓冲液进行洗脱。优化了液相色谱和质谱参数,以提高在高流速条件下对完整DAR物种的检测。为了证明该平台表征不同类型adc的可行性,我们评估了互链(异质DAR为0至8)和位点特异性adc。该方法可以实现不同DAR物种的非变性分离和同时表征,并且该方法与HIC分析具有很强的相关性。这种综合策略允许DAR物种的无偏定性,而不需要柱后流分裂或峰分馏。此外,与两种常用的方法(天然SEC-MS和RPLC-MS)的比较表明,nRPLC方法在选择性和分辨率方面都取得了更好的分离效果。值得注意的是,使用这种方法,未偶联抗体(DAR0)成功地保留在低离子强度盐中。此外,该方法可以方便地分离具有不同共轭键的DAR4种的位置异构体,这是传统HIC无法实现的。因此,该方法在跨共轭方法和有效载荷类别的adc的高通量筛选和表征方面具有很大的前景。
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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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