4.7 Article

Fiber-based HIC capture loop for coupling of protein A and size exclusion chromatography in a two-dimensional separation of monoclonal antibodies

期刊

ANALYTICA CHIMICA ACTA
卷 1098, 期 -, 页码 190-200

出版社

ELSEVIER
DOI: 10.1016/j.aca.2019.11.023

关键词

Two-dimensional liquid chromatography; Antibodies; Capillary-channeled polymer fibers; Capture loop protein A; Size exclusion chromatography

资金

  1. National Science Foundation Division of Chemistry [CHE-1608663]
  2. Merck Sharp Dohme Corp.

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During process development and manufacturing of monoclonal antibodies (mAbs), it is critical to characterize structure-function relationships to properly control the levels of mAb aggregation and potency of the protein product. With two-dimensional high performance liquid chromatography (2D-HPLC) technology, protein A (ProA) affinity chromatography can be used in the first dimension to isolate and measure the concentration of mAb, with the effluent transferred to a second dimension of size exclusion chromatography (SEC) to measure purity (i.e. aggregation). Described here is a 2D-HPLC method for characterizing mAb concentration and aggregation level, combining ProA purification, a novel injector-loop capture step, and aggregation determination by SEC. Unique here, polyester capillarychanneled polymer (C-CP) fibers are packed into PEEK tubing and used as the inter-column injection loop, capturing and releasing the mAbs via a hydrophobic interaction chromatography (HIC) process. The applicability of the HIC capture method was investigated on three ProA columns, including a homemade C-CP fiber format, and commercial POROS (R) A 20 mu m and TSKgel Protein A-5PW columns. The HIC fiber capture loop was compared with standard, open sample loops in terms of solute recoveries, degree of affected aggregation, and chromatographic resolution. Advantages are seen in terms of limiting insystem mAb aggregation due to reduced low-pH solvent exposure, improved D-2 chromatographic resolution, better monomer/aggregate ratio fidelity, and enhanced quantitative figures of merit. (C) 2019 Elsevier B.V. All rights reserved.

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