ArticlemAbs2019
Charge variants characterization and release assay development for co-formulated antibodies as a combination therapy.
Article in mAbs, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 37 citations in OpenAlex.
- Article
- Developments in Ion Exchange Chromatography-Mass Spectrometry for the Characterization of Intact Proteins and Proteoforms.Journal of separation science · 2025Review
- Charge Variants Characterization of Co-Formulated Antibodies by Three-Dimensional Liquid Chromatography-Mass Spectrometry.Biomolecules · 2024Article
- Basic regulatory science behind drug substance and drug product specifications of monoclonal antibodies and other protein therapeutics.Journal of pharmaceutical analysis · 2024Review
- Identification of Hetero-aggregates in Antibody Co-formulations by Multi-dimensional Liquid Chromatography Coupled to Mass Spectrometry.Analytical chemistry · 2023Article
- Improved process intermediate stability through the identification and elimination of reactive glycation residues - a monoclonal antibody case study.Bioengineered · 2022Article
- Application of Affinity-Capture Self-Interaction Nanoparticle Spectroscopy in Predicting Protein Stability, Especially for Co-Formulated Antibodies.Pharmaceutical research · 2021Article
- Characterization of Co-Formulated High-Concentration Broadly Neutralizing Anti-HIV-1 Monoclonal Antibodies for Subcutaneous Administration.Antibodies (Basel, Switzerland) · 2020Article
- Review
- Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Combination therapy is a fast-growing strategy to maximize therapeutic benefits to patients. Co-formulation of two or more therapeutic proteins has advantages over the administration of multiple medications, including reduced medication errors and convenience for patients. Characterization of co-formulated biologics can be challenging due to the high degree of similarity in the physicochemical properties of co-formulated proteins, especially at different concentrations of individual components. We present the results of a deamidation study of one monoclonal antibody component (mAb-B) in co-formulated combination antibodies (referred to as COMBO) that contain various ratios of mAb-A and mAb-B. A single deamidation site in the complementarity-determining region of mAb-B was identified as a critical quality attribute (CQA) due to its impact on biological activity. A conventional charge-based method of monitoring mAb-B deamidation presented specificity and robustness challenges, especially when mAb-B was a minor component in the COMBO, making it unsuitable for lot release and stability testing. We developed and qualified a new, quality-control-friendly, single quadrupole Dalton mass detector (QDa)-based method to monitor site-specific deamidation. Our approach can be also used as a multi-attribute method for monitoring other quality attributes in COMBO. This analytical paradigm is applicable to the identification of CQAs in combination therapeutic molecules, and to the subsequent development of a highly specific, highly sensitive, and sufficiently robust method for routine monitoring CQAs for lot release test and during stability studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.