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

• 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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

Publication and Content Type

art (subject category)

ref (subject category)