Evidence map›Paper›PMID 32458729›Full record

ArticleSLAS technology2020

High-Throughput Analysis of Fluorescently Labeled N-Glycans Derived from Biotherapeutics Using an Automated LC-MS-Based Solution.

Ximo Zhang, Corey E Reed, Robert E Birdsall, Ying Qing Yu, Weibin Chen

Open access · bronzeAbstract read
In one paragraph

Article in SLAS technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. High-Throughput Glycomic Methods.Chemical reviews · 2022
    Review
  2. Article
  3. Article
  4. Automation of Immunoglobulin Glycosylation Analysis.Experientia supplementum (2012) · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Ximo ZhangScientific Operations, Waters Corporation, Milford, MA, USA.
Corey E ReedScientific Operations, Waters Corporation, Milford, MA, USA.
Robert E BirdsallScientific Operations, Waters Corporation, Milford, MA, USA.
Ying Qing YuScientific Operations, Waters Corporation, Milford, MA, USA.
Weibin ChenScientific Operations, Waters Corporation, Milford, MA, USA.
Waters (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein glycosylation can impact the efficacy and safety of biotherapeutics and therefore needs to be well characterized and monitored throughout the drug product life cycle. Glycosylation is commonly assessed by fluorescent labeling of released glycans, which provides comprehensive information of the glycoprofile but can be resource-intensive regarding sample preparation, data acquisition, and data analysis. In this work, we evaluate a comprehensive solution from sample preparation to data reporting using a liquid chromatography-mass spectrometry (LC-MS)-based analytical platform for increased productivity in released glycan analysis. To minimize user intervention and improve assay robustness, a robotic liquid handling platform was used to automate the release and labeling of N-glycans within 2 h. To further increase the throughput, a 5 min method was developed on a liquid chromatography-fluorescence-mass spectrometry (LC-FLR-MS) system using an integrated glycan library based on retention time and accurate mass. The optimized method was then applied to 48 released glycan samples derived from six batches of infliximab to mimic comparability testing encountered in the development of biopharmaceuticals. Consistent relative abundance of critical species such as high mannose and sialylated glycans was obtained for samples within the same batch (mean percent relative standard deviation [RSD] = 5.3%) with data being acquired, processed, and reported in an automated manner. The data acquisition and analysis of the 48 samples were completed within 6 h, which represents a 90% improvement in throughput compared with conventional LC-FLR-based methods. Together, this workflow facilitates the rapid screening of glycans, which can be deployed at various stages of drug development such as process optimization, bioreactor monitoring, and clone selections, where high-throughput and improved productivity are particularly desired.

Indexed as

Staining and LabelingTandem Mass SpectrometryAutomationChromatography, LiquidFluorescent DyesHigh-Throughput Screening AssaysInfliximabPolysaccharidesSolutionsFluorescent DyesInfliximabPolysaccharidesSolutionsautomationhigh-throughput screeningLC-MSN-glycan analysisprocess development

Identifiers

PMID32458729
PMCPMC7372583
OpenAlexW3029969422

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.