ArticleBiotechnology and bioengineering2022
Rapid cGMP manufacturing of COVID-19 monoclonal antibody using stable CHO cell pools.
Article in Biotechnology and bioengineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 31 citations in OpenAlex.
- Recombinant Protein Drugs: A 2025 Update.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026Review
- Discovery of a chimeric transposase-transposon system for advanced genome engineering.iScience · 2026Article
- A comprehensive proteome and phosphoproteome atlas across nine organs of the Chinese hamster.Animal models and experimental medicine · 2026Article
- A comprehensive strategy for pandemic preparedness with neutralizing monoclonal antibodies.mAbs · 2025Article
- Utilizing non-clonal CHO cell derived materials for preclinical studies of complex molecules.BMC biotechnology · 2025Article
- Utilizing Stable Gene-Edited Knockout Pools for Genetic Screening and Engineering in Chinese Hamster Ovary Cells.Biotechnology journal · 2025Article
- Rapid and Scalable Production of Functional SARS-CoV-2 Virus-like Particles (VLPs) by a Stable HEK293 Cell Pool.Vaccines · 2024Article
- Further accelerating biologics development from DNA to IND: the journey from COVID-19 to non-COVID-19 programs.Antibody therapeutics · 2024Review
- CMC Strategies and Advanced Technologies for Vaccine Development to Boost Acceleration and Pandemic Preparedness.Vaccines · 2023Review
- Monoclonal antibody therapies for COVID-19: lessons learned and implications for the development of future products.Current opinion in biotechnology · 2022Review
- Rapid cGMP manufacturing of COVID-19 monoclonal antibody using stable CHO cell pools.Biotechnology and bioengineering · 2022Article
- Progress of Transposon Vector System for Production of Recombinant Therapeutic Proteins in Mammalian Cells.Frontiers in bioengineering and biotechnology · 2022Review
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Corrections and comments
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Authors and funding
17 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Therapeutic proteins, including monoclonal antibodies, are typically manufactured using clonally derived, stable host cell lines, since consistent and predictable cell culture performance is highly desirable. However, selecting and preparing banks of stable clones takes considerable time, which inevitably extends overall development timelines for new therapeutics by delaying the start of subsequent activities, such as the scale-up of manufacturing processes. In the context of the coronavirus disease 2019 (COVID-19) pandemic, with its intense pressure for accelerated development strategies, we used a novel transposon-based Leap-In Transposase® system to rapidly generate high-titer stable pools and then used them directly for large scale-manufacturing of an anti-severe acute respiratory syndrome coronavirus 2 monoclonal antibody under cGMP. We performed the safety testing of our non-clonal cell bank, then used it to produce material at a 200L-scale for preclinical safety studies and formulation development work, and thereafter at 2000L scale for supply of material for a Phase 1 clinical trial. Testing demonstrated the comparability of critical product qualities between the two scales and, more importantly, that our final clinical trial product met all pre-set product quality specifications. The above expediated approach provided clinical trial material within 4.5 months, in comparison to 12-14 months for production of clinical trial material via the conventional approach.
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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.