ArticleBiotechnology and bioengineering2017
Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.
Article in Biotechnology and bioengineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Multi-Attribute Monitoring Method for Process Development of Engineered Antibody for Site-Specific Conjugation.Journal of the American Society for Mass Spectrometry · 2023Article
- Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics.Frontiers in bioengineering and biotechnology · 2023Article
- A decade in review: use of data analytics within the biopharmaceutical sector.Current opinion in chemical engineering · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (Ambr
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Registered trials
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