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Rational Selection, Criticality Assessment, and Tiering of Quality Attributes and Test Methods for Analytical Similarity Evaluation of Biosimilars

Overview of attention for article published in The AAPS Journal, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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1 news outlet
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3 X users

Citations

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34 Dimensions

Readers on

mendeley
72 Mendeley
Title
Rational Selection, Criticality Assessment, and Tiering of Quality Attributes and Test Methods for Analytical Similarity Evaluation of Biosimilars
Published in
The AAPS Journal, May 2018
DOI 10.1208/s12248-018-0230-9
Pubmed ID
Authors

Kristof Vandekerckhove, Andreas Seidl, Hiten Gutka, Manish Kumar, Gyöngyi Gratzl, David Keire, Todd Coffey, Henriette Kuehne

Abstract

Leading regulatory agencies recommend biosimilar assessment to proceed in a stepwise fashion, starting with a detailed analytical comparison of the structural and functional properties of the proposed biosimilar and reference product. The degree of analytical similarity determines the degree of residual uncertainty that must be addressed through downstream in vivo studies. Substantive evidence of similarity from comprehensive analytical testing may justify a targeted clinical development plan, and thus enable a shorter path to licensing. The importance of a careful design of the analytical similarity study program therefore should not be underestimated. Designing a state-of-the-art analytical similarity study meeting current regulatory requirements in regions such as the USA and EU requires a methodical approach, consisting of specific steps that far precede the work on the actual analytical study protocol. This white paper discusses scientific and methodological considerations on the process of attribute and test method selection, criticality assessment, and subsequent assignment of analytical measures to US FDA's three tiers of analytical similarity assessment. Case examples of selection of critical quality attributes and analytical methods for similarity exercises are provided to illustrate the practical implementation of the principles discussed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 24%
Student > Master 13 18%
Student > Ph. D. Student 9 13%
Student > Bachelor 4 6%
Other 3 4%
Other 8 11%
Unknown 18 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 19%
Pharmacology, Toxicology and Pharmaceutical Science 13 18%
Agricultural and Biological Sciences 6 8%
Chemical Engineering 3 4%
Unspecified 2 3%
Other 9 13%
Unknown 25 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 17 May 2018.
All research outputs
#4,075,041
of 23,053,613 outputs
Outputs from The AAPS Journal
#208
of 1,296 outputs
Outputs of similar age
#79,249
of 326,011 outputs
Outputs of similar age from The AAPS Journal
#3
of 16 outputs
Altmetric has tracked 23,053,613 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,296 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done well, scoring higher than 83% 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 326,011 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 75% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.