Literature DB >> 18279794

A physiologically based pharmacokinetic (PBPK) model to characterize and predict the disposition of monoclonal antibody CC49 and its single chain Fv constructs.

Jasmine P Davda1, Maneesh Jain, Surinder K Batra, Peter R Gwilt, Dennis H Robinson.   

Abstract

Optimization of the use of monoclonal antibodies (MAbs) as diagnostic tools and therapeutic agents in the treatment of cancer is aided by quantitative characterization of the transport and tissue disposition of these agents in whole animals. This characterization may be effectively achieved by the application of physiologically based pharmacokinetic (PBPK) models. The purpose of this study was to develop a PBPK model to characterize the biodistribution of the pancarcinoma MAb CC49 IgG in normal and neoplastic tissues of nude mice, and to further apply the model to predict the disposition of multivalent single chain Fv (scFv) constructs in mice. Since MAbs are macromolecules, their transport is membrane-limited and a two-pore formalism is employed to describe their extravasation. The influence of binding of IgG to the protective neonatal Fc receptor (FcRn) on its disposition is also accounted for in the model. The model successfully described (131)I-CC49 IgG concentrations in blood, tumor and various organs/tissues in mice. Sensitivity analysis revealed the rate of transcapillary transport to be a critical determinant of antibody penetration and localization in the tumor. The applicability of the model was tested by predicting the disposition of di- and tetravalent scFv constructs of CC49 in mice. The model gave reasonably good predictions of the disposition of the scFv constructs. Since the model employs physiological parameters, it can be used to scale-up mouse biodistribution data to predict antibody distribution in humans. Therefore, the clinical utility of the model was tested with data for (131)I-CC49 obtained in patients, by scaling up murine parameter values according to known empirical relationships. The model gave satisfactory predictions of CC49 disposition and tumor uptake in man.

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Year:  2007        PMID: 18279794     DOI: 10.1016/j.intimp.2007.10.023

Source DB:  PubMed          Journal:  Int Immunopharmacol        ISSN: 1567-5769            Impact factor:   4.932


  44 in total

1.  Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human.

Authors:  Dhaval K Shah; Alison M Betts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-12-06       Impact factor: 2.745

2.  A new stochastic approach to multi-compartment pharmacokinetic models: probability of traveling route and distribution of residence time in linear and nonlinear systems.

Authors:  Liang Zhao; Na Li; Harry Yang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-12-17       Impact factor: 2.745

3.  Scale-up of a physiologically-based pharmacokinetic model to predict the disposition of monoclonal antibodies in monkeys.

Authors:  Patrick M Glassman; Yang Chen; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-09-12       Impact factor: 2.745

4.  Across-Species Scaling of Monoclonal Antibody Pharmacokinetics Using a Minimal PBPK Model.

Authors:  Jie Zhao; Yanguang Cao; William J Jusko
Journal:  Pharm Res       Date:  2015-05-05       Impact factor: 4.200

5.  Development of a physiologically based pharmacokinetic model for a domain antibody in mice using the two-pore theory.

Authors:  Armin Sepp; Alienor Berges; Andrew Sanderson; Guy Meno-Tetang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-01-11       Impact factor: 2.745

6.  A PBPK workflow for first-in-human dose selection of a subcutaneously administered pegylated peptide.

Authors:  Elliot Offman; Andrea N Edginton
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-02-04       Impact factor: 2.745

Review 7.  Physiologically Based Pharmacokinetic (PBPK) Modeling of Pharmaceutical Nanoparticles.

Authors:  Min Li; Peng Zou; Katherine Tyner; Sau Lee
Journal:  AAPS J       Date:  2016-11-10       Impact factor: 4.009

8.  Effects of the FcRn developmental pharmacology on the pharmacokinetics of therapeutic monoclonal IgG antibody in pediatric subjects using minimal physiologically-based pharmacokinetic modelling.

Authors:  Deni Hardiansyah; Chee Meng Ng
Journal:  MAbs       Date:  2018-07-30       Impact factor: 5.857

Review 9.  Pharmacokinetics, pharmacodynamics and physiologically-based pharmacokinetic modelling of monoclonal antibodies.

Authors:  Miroslav Dostalek; Iain Gardner; Brian M Gurbaxani; Rachel H Rose; Manoranjenni Chetty
Journal:  Clin Pharmacokinet       Date:  2013-02       Impact factor: 6.447

10.  Pulmonary pharmacodynamics of an anti-GM-CSFRα antibody enables therapeutic dosing that limits exposure in the lung.

Authors:  Jamie Campbell; Josquin Nys; Laura Eghobamien; E Suzanne Cohen; Matthew J Robinson; Matthew A Sleeman
Journal:  MAbs       Date:  2016-08-12       Impact factor: 5.857

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