The prediction of
monoclonal antibody (mAb) disposition within solid
tumors for individual patients is difficult due to inter-patient variability in
tumor physiology. Improved a priori prediction of mAb pharmacokinetics in
tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-
cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with
tumor penetration of the
contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of
cetuximab pharmacokinetics in
epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the
contrast agent gadobutrol, followed by intravenous dosing of an 125Iodine-labeled, non-binding mAb (8C2).
Tumor concentrations of 8C2 were determined following the
euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter Ktrans alone or Ktrans in combination with the DCE-MRI parameter Vp on the PBPK parameters for
tumor blood flow (QTU) and
tumor vasculature permeability (σTUV) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual
tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity
tumor binding, a second group of
tumor-bearing mice underwent DCE-MRI imaging with
gadobutrol, followed by the administration of 125Iodine-labeled
cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and
cetuximab-EGFR interaction to predict the disposition of
cetuximab in individual
tumors (a priori). The incorporation of the Ktrans MRI parameter as a covariate on the PBPK parameters QTU and σTUV decreased the PBPK model prediction error for
cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid
tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.