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The Utility of Modeling and Simulation Approaches to Evaluate Immunogenicity Effect on the Therapeutic Protein Pharmacokinetics

Overview of attention for article published in The AAPS Journal, November 2012
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Title
The Utility of Modeling and Simulation Approaches to Evaluate Immunogenicity Effect on the Therapeutic Protein Pharmacokinetics
Published in
The AAPS Journal, November 2012
DOI 10.1208/s12248-012-9424-8
Pubmed ID
Authors

Juan Jose Perez Ruixo, Peiming Ma, Andrew T. Chow

Abstract

While therapeutic proteins (TP), particularly recombinant human proteins and fully human monoclonal antibodies, are designed to have a low immunogenic potential in humans, a clinical immune response does sometimes occur and cannot be predicted from preclinical studies. Changes in TP pharmacokinetics may be perceived as an early indication of antibody formation and serve as a surrogate for later changes in efficacy and safety in individual subjects. Given the substantial increase in number of biological products, including biosimilars, there is an urgent need to quantitatively predict and quantify the immune response and any consequential changes in TP pharmacokinetics. The purpose of this communication is to review the utility of population-based modeling and simulation approaches developed to date for investigating the development of an immune response and assessing its impact on TP pharmacokinetics. Two examples of empirical modeling approaches for pharmacokinetic assessment are presented. The first example presents methods to analyze pharmacokinetic data in the presence of anti-drug antibody (ADA) and confirm the effect of immunogenicity on TP pharmacokinetics in early phases of drug development. The second example provides a framework to analyze pharmacokinetic data in the absence or with very low incidence of ADA and confirm with enough power the lack of an immunogenicity effect on TP pharmacokinetics in late phases of drug development. Finally, a theoretical mechanism-based modeling framework is presented to mathematically relate the complex interaction among TP, their targets, and ADA.

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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 %
Netherlands 1 1%
France 1 1%
United Kingdom 1 1%
Belgium 1 1%
United States 1 1%
Unknown 67 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 33%
Student > Ph. D. Student 11 15%
Other 9 13%
Student > Master 6 8%
Student > Doctoral Student 3 4%
Other 7 10%
Unknown 12 17%
Readers by discipline Count As %
Medicine and Dentistry 19 26%
Pharmacology, Toxicology and Pharmaceutical Science 11 15%
Agricultural and Biological Sciences 10 14%
Chemistry 4 6%
Computer Science 3 4%
Other 9 13%
Unknown 16 22%