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Strategies for Generating Diverse Antibody Repertoires Using Transgenic Animals Expressing Human Antibodies

Overview of attention for article published in Frontiers in immunology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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1 news outlet
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3 X users
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6 patents

Citations

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33 Dimensions

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93 Mendeley
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Title
Strategies for Generating Diverse Antibody Repertoires Using Transgenic Animals Expressing Human Antibodies
Published in
Frontiers in immunology, March 2018
DOI 10.3389/fimmu.2018.00460
Pubmed ID
Authors

Weihsu C. Chen, Christopher M. Murawsky

Abstract

Therapeutic molecules derived from antibodies have become a dominant class of drugs used to treat human disease. Increasingly, therapeutic antibodies are discovered using transgenic animal systems that have been engineered to express human antibodies. While the engineering details differ, these platforms share the ability to raise an immune response that is comprised of antibodies with fully human idiotypes. Although the predominant transgenic host species has been mouse, the genomes of rats, rabbits, chickens, and cows have also been modified to express human antibodies. The creation of transgenic animal platforms expressing human antibody repertoires has revolutionized therapeutic antibody drug discovery. The observation that the immune systems of these animals are able to recognize and respond to a wide range of therapeutically relevant human targets has led to a surge in antibody-derived drugs in current development. While the clinical success of fully human monoclonal antibodies derived from transgenic animals is well established, recent trends have seen increasingly stringent functional design goals and a shift in difficulty as the industry attempts to tackle the next generation of disease-associated targets. These challenges have been met with a number of novel approaches focused on the generation of large, high-quality, and diverse antibody repertoires. In this perspective, we describe some of the strategies and considerations we use for manipulating the immune systems of transgenic animal platforms (such as XenoMouse®) with a focus on maximizing the diversity of the primary response and steering the ensuing antibody repertoire toward a desired outcome.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 93 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 19%
Student > Ph. D. Student 14 15%
Student > Bachelor 11 12%
Other 8 9%
Student > Doctoral Student 4 4%
Other 6 6%
Unknown 32 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 26%
Agricultural and Biological Sciences 16 17%
Immunology and Microbiology 7 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Medicine and Dentistry 2 2%
Other 8 9%
Unknown 32 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2023.
All research outputs
#1,917,385
of 26,243,859 outputs
Outputs from Frontiers in immunology
#1,811
of 32,885 outputs
Outputs of similar age
#39,823
of 351,824 outputs
Outputs of similar age from Frontiers in immunology
#57
of 684 outputs
Altmetric has tracked 26,243,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 32,885 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 351,824 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 684 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.