ArticlemAbs
Comprehensive manipulation of glycosylation profiles across development scales.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed.
- Operationalizing digital twins in biomanufacturing through interoperable process analytical technology.Bioprocess and biosystems engineering · 2026Article
- Effects of sialylated oligosaccharides on the N- and O-glycosylation of etanercept in recombinant CHO cells.Applied microbiology and biotechnology · 2026Article
- Glycan Profiles of FDA-Approved Therapeutic Antibodies: Insights from Regulatory Submissions.The AAPS journal · 2026Article
- Industry-defined opportunities for advancing big data capabilities in biopharmaceutical manufacturing.Frontiers in bioengineering and biotechnology · 2026Review
- Targeting the Gut-Brain Axis Through Insulin-like Growth Factors: Therapeutic Implications and Future Directions.Journal of molecular neuroscience : MN · 2025Review
- Enhancing monoclonal antibody production efficiency using CHO-MK cells and specific media in a conventional fed-batch culture.Cytotechnology · 2025Article
- N-Glycosylation modulators for targeted manipulation of glycosylation for monoclonal antibodies.Applied microbiology and biotechnology · 2025Article
- Strategies to control therapeutic antibody glycosylation during bioprocessing: Synthesis and separation.Biotechnology and bioengineering · 2022Review
- Modular development enables rapid design of media for alternative hosts.Biotechnology and bioengineering · 2022Article
- Antibody Structure and Function: The Basis for Engineering Therapeutics.Antibodies (Basel, Switzerland) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The extent and pattern of glycosylation on therapeutic antibodies can influence their circulatory half-life, engagement of effector functions, and immunogenicity, with direct consequences to efficacy and patient safety. Hence, controlling glycosylation patterns is central to any drug development program, yet poses a formidable challenge to the bio-manufacturing industry. Process changes, which can affect glycosylation patterns, range from manufacturing at different scales or sites, to switching production process mode, all the way to using alternative host cell lines. In the emerging space of biosimilars development, often times all of these aspects apply. Gaining a deep understanding of the direction and extent to which glycosylation quality attributes can be modulated is key for efficient fine-tuning of glycan profiles in a stage appropriate manner, but establishment of such platform knowledge is time consuming and resource intensive. Here we report an inexpensive and highly adaptable screening system for comprehensive modulation of glycans on antibodies expressed in CHO cells. We characterize 10 media additives in univariable studies and in combination, using a design of experiments approach to map the design space for tuning glycosylation profile attributes. We introduce a robust workflow that does not require automation, yet enables rapid process optimization. We demonstrate scalability across deep wells, shake flasks, AMBR-15 cell culture system, and 2 L single-use bioreactors. Further, we show that it is broadly applicable to different molecules and host cell lineages. This universal approach permits fine-tuned modulation of glycan product quality, reduces development costs, and enables agile implementation of process changes throughout the product lifecycle.
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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.