ArticleJournal of pharmaceutical sciences2018
Flow Microscopy Imaging Is Sensitive to Characteristics of Subvisible Particles in Peginesatide Formulations Associated With Severe Adverse Reactions.
Article in Journal of pharmaceutical sciences, 2018. 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, 17 citations in OpenAlex.
- Modulation of Intravenous Immunoglobulin Aggregation, Subvisible Particle Formation, and Viscosity by Acetylated Amino Acids.Pharmaceutics · 2026Article
- Optical imaging and spectroscopic characterization of subvisible particles in protein therapeutics.Advanced drug delivery reviews · 2026Review
- Immunogenicity Risk Assessment of Spontaneously Occurring Therapeutic Monoclonal Antibody Aggregates.Frontiers in immunology · 2022Article
- Oil-Immersion Flow Imaging Microscopy for Quantification and Morphological Characterization of Submicron Particles in Biopharmaceuticals.The AAPS journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The presence of subvisible particles in formulations of therapeutic proteins is a risk factor for adverse immune responses. Although the immunogenic potential of particulate contaminants likely depends on particle structural characteristics (e.g., composition, size, and shape), exact structure-immunogenicity relationships are unknown. Images recorded by flow imaging microscopy reflect information about particle morphology, but flow microscopy is typically used to determine only particle size distributions, neglecting information on particle morphological features that may be immunologically relevant. We recently developed computational techniques that utilize the Kullback-Leibler divergence and multidimensional scaling to compare the morphological properties of particles in sets of flow microscopy images. In the current work, we combined these techniques with expectation maximization cluster analyses and used them to compare flow imaging microscopy data sets that had been collected by the U.S. Food and Drug Administration after severe adverse drug reactions (including 7 fatalities) were observed in patients who had been administered some lots of peginesatide formulations. Flow microscopy images of particle populations found in the peginesatide lots associated with severe adverse reactions in patients were readily distinguishable from images of particles in lots where severe adverse reactions did not occur.
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What OpenQuestion holds
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.