Evidence map›Paper›PMID 39459229›Full record

ArticleMolecules (Basel, Switzerland)2024

Development of an LC-TOF/MS Method to Quantify Camrelizumab in Human Serum.

Li Song, Yan Liang, Yilin Li, Tingting Guo, Hui Li, Shuxuan Liang

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Li SongCollege of Chemistry and Materials Science, Hebei University, Baoding 071000, China.
Yan LiangCollege of Pharmacy, Hebei Medical University, Shijiazhuang 050000, China.ORCID 0009-0004-5270-797X
Yilin LiCollege of Chemistry and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China.
Tingting GuoCollege of Chemistry and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China.
Hui LiHebei Institute of Drug and Medical Device Inspection, Shijiazhuang 050000, China.
Shuxuan LiangCollege of Chemistry and Materials Science, Hebei University, Baoding 071000, China.ORCID 0000-0003-4159-4004

Funding

Natural Science Foundation of Hebei Province H2022329002
6 · The paper itself

Abstract

With the advantages of a high specificity, a long half-life, and a high safety, the use of antibody biologic drugs, including camrelizumab, has been rapidly increasing in clinical practice. Camrelizumab, an immune checkpoint inhibitor and humanized monoclonal antibody, is used to treat several advanced solid cancers. Measuring its concentration supports personalized dosage adjustments, influences treatment decisions for patients, strengthens the control of disease activity through therapeutic drug monitoring, and helps evaluate and prevent drug interactions in combination therapy. Because antibodies are present in complex biological matrices, quantifying monoclonal antibody drugs is challenging, and must rely on precise, selective, and reliable analytical methods. In this study, a quadrupole time-of-flight mass spectrometry TripleTOF 6600+ (AB SCIEX, Framingham, MA, USA) system equipped with a Turbo V ion source was used for the qualitative analysis of monoclonal antibodies using the data-dependent acquisition (IDA) MS/MS mode, followed by quantitative analysis using a targeted MRMHR workflow. This method showed a good linear relationship within the range of 4-160 μg/mL, with a correlation coefficient of R

Indexed as

Antibodies, Monoclonal, HumanizedChromatography, LiquidDrug MonitoringHumansTandem Mass SpectrometryAntibodies, Monoclonal, HumanizedcamrelizumabcamrelizumabLC-TOF/MSmonoclonal antibodyPD-1 inhibitorserum

Identifiers

PMID39459229
PMCPMC11510712

What OpenQuestion holds

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LicenceCC BY
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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.