Evidence map›Paper›PMID 38932846›Full record

ReviewJournal of diabetes and metabolic disorders2024

A mini review on recent progress of microfluidic systems for antibody development.

Kobra Omidfar, Sohiela Kashanian

Abstract readReview
In one paragraph

Review in Journal of diabetes and metabolic disorders, 2024. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

2 authors.

Kobra OmidfarBiosensor Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, P.O. Box 14395/1179, Tehran, IR Iran.ORCID 0000-0002-8831-6936
Sohiela KashanianFaculty of Chemistry, Razi University, Kermanshah, 6714414971 Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Antibody is specific reagent that be utilized in various field of biomedical research. Monoclonal antibodies are mostly produced using two common techniques namely hybridoma and antibody engineering, which suffer from some limitations such as boring screening procedures, long production time, low efficacy and a degree of automation. To address these limitations, various microfluidics techniques have been developed for the antibody isolation and screening. Methods: This study specifically investigates nearly recent reports published in peer-reviewed journals indexed in various databases including Web of Science, Scopus, PubMed, Google Scholar, and Science Direct. Results: In this study, we identified a total of seventy papers from a pool of 130 articles. These papers focus on the application of three major groups of microfluidic platforms, namely valves, microwells, and droplets, in the development of antibodies using hybridoma method and phage display technology. We provide a summary of these applications and also discuss the key findings in this field. Additionally, we illustrate our discussion with several examples to enhance understanding. Conclusions: Microfluidics has the potential to serve as a valuable tool in streamlining complex laboratory procedures involved in antibody discovery. However, it is important to note that microfluidics is limited to laboratory settings. Further enhancements are needed to address existing challenges and to make microfluidics a reliable, accurate, and cost-effective tool for antibody discovery.

Indexed as

Antibody developmentHybridoma technologyMicrofluidic platformPhage display technology

Identifiers

PMID38932846
PMCPMC11196548

What OpenQuestion holds

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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.