ArticlePharmaceutical research2024
A survey of FDA Approved Monoclonal Antibodies and Fc-fusion Proteins for Manufacturing Changes and Comparability Assessment.
Article in Pharmaceutical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
4 citing papers in PubMed.
- Perspective on Pharmacokinetic Comparability for Biologics Development.Clinical pharmacology and therapeutics · 2026Article
- Host cell protein impurities in therapeutic proteins: overview of advances in detection, nonconventional removal technologies and immunogenicity assessment.Journal of biological engineering · 2026Review
- Investigating the impact of synonymous gene recoding on a recombinantly expressed monoclonal antibody under different process parameters.Bioengineering & translational medicine · 2025Article
- Unlocking the full potential of plant cell-based production for valuable proteins: Challenges and innovative strategies.Biotechnology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveManufacturing changes occur commonly throughout stages of biologics development and may result in product quality attribute changes. As changes in critical quality attributes have the potential to affect clinical safety and efficacy of products, it is imperative to ensure the quality and clinical performance before introducing the after-change products. Thus, we embarked on this project to understand what data have supported the manufacturing changes for licensed products with pre- and post-approval changes.
methodsWe surveyed the manufacturing changes of 85 monoclonal antibodies and 10 Fc fusion proteins approved by the Food and Drug Administration as of December 25, 2021. After collecting the type and timing of changes for these products, we investigated the approaches that provided supporting data for the changes. The source documents included reports submitted by applicants and FDA's regulatory reviews.
resultsAnalytical comparability was assessed to support all identified manufacturing changes. Supporting clinical data were available in 92% of these manufacturing changes; including data from pharmacokinetic comparability studies alone (3%), other studies on efficacy or safety (70%) and a combination of both (19%). Clinical pharmacokinetic comparability data contributed to supporting substantial changes, such as host cell type or master cell bank changes, concentration or formulation changes, and changes from pre-filled syringes to autoinjectors, especially when introduced after completing pivotal studies.
conclusionOur comprehensive retrospective analysis provides an understanding of the regulatory experience and industry practice, which could facilitate developing appropriate comparability approaches to support manufacturing changes in the future.
Indexed as
Identifiers
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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.