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. 2008 Mar;8(3):401-13.
doi: 10.1016/j.intimp.2007.10.023. Epub 2007 Nov 26.

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

Jasmine P Davda  1 , Maneesh Jain, Surinder K Batra, Peter R Gwilt, Dennis H Robinson
Affiliations

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

Jasmine P Davda et al. Int Immunopharmacol. 2008 Mar.

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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