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Development and evaluation of a pharmacokinetic model for prediction of radioimmunotherapy based on pretherapy data.

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Author

Summary, in English

The aim of this work was to develop a pharmacokinetic model for the analysis of the pharmacokinetics of (111)Inlabeled monoclonal antibodies (mAbs) in B-cell lymphoma patients and to evaluate the model's ability to predict a subsequent radioimmunotherapy by (90)Y-labeled mAbs. Data from quantified scintillation camera images and blood samples were used to fit a compartment model. The modeling included two steps: 1) a two-compartment model describing the total-body kinetics for the estimation of a set of global parameters and 2) a multicompartment model for estimating the model parameters for organs. In both steps, a correction for radiochemical impurity in the form of (111)In-DTPA (diethylene triamine pentaacetic acid) was included. The model was found to describe all patient data with good accuracy. From the model, the time-activity data of all organs could be separated into extravascular and vascular components, where the estimates of the regional vascular volumes were found to be in close agreement with literature data. A significant improvement of the model fit to total-body activity data was obtained by correcting for radiochemical impurity. The therapy kinetics area under the curves (AUCs) predicted from pretherapy data were in good agreement with the measured therapy AUCs. The good correlation between the model estimates and measured data, the accurate prediction of the therapy kinetics, and the good estimates of regional vascular volumes demonstrates the reliability of the model. These findings also indicate that the model can be useful for individual optimization of the amount of activity to be administered with respect to patient dosimetry.

Publishing year

2009

Language

English

Pages

111-121

Publication/Series

Cancer Biotherapy & Radiopharmaceuticals

Volume

24

Issue

1

Document type

Journal article

Publisher

Mary Ann Liebert, Inc.

Topic

  • Cancer and Oncology

Status

Published

ISBN/ISSN/Other

  • ISSN: 1557-8852