We constructed a novel physiologically-based pharmacokinetic (PBPK) model for predicting interactions between the neonatal Fc receptor (FcRn) and anti-carcinoembryonic antigen (CEA) monoclonal antibodies (mAbs) with varying affinity for FcRn. Our new model, an integration and extension of several previously published models, includes aspects of mAb-FcRn dynamics within intracellular compartments not represented in previous PBPK models. We added mechanistic structure that details internalization of class G immunoglobulins by endothelial cells, subsequent FcRn binding, recycling into plasma of FcRn-bound IgG and degradation of free endosomal IgG. Degradation in liver is explicitly represented along with the FcRn submodel in skin and muscle. A variable tumor mass submodel is also included, used to estimate the growth of an avascular, necrotic tumor core, providing a more realistic picture of mAb uptake by tumor. We fitted the new multiscale model to published anti-CEA mAb biodistribution data, i.e. concentration-time profiles in tumor and various healthy tissues in mice, providing new estimates of mAb-FcRn related kinetic parameters. The model was further validated by successful prediction of F(ab')2 mAb fragment biodistribution, providing additional evidence of its potential value in optimizing intact mAb and mAb fragment dosing for clinical imaging and immunotherapy applications.

Derivation of the plasma time-activity curve in murine small-animal PET studies is a challenging task when tracers that are sequestered by the myocardium are used, because plasma time-activity curve estimation usually involves drawing a region of interest within the area of the reconstructed image that corresponds to the left ventricle (LV) of the heart. The small size of the LV relative to the resolution of the small-animal PET system, coupled with spillover effects from adjacent myocardial pixels, makes this method reliable only for the earliest frames of the scan. We sought to develop a method for plasma time-activity curve estimation based on a model of tracer kinetics in blood, muscle, and liver. Methods: Sixteen C57BL/6 mice were injected with 18 F-FDG, and approximately 15 serial blood samples were taken from the femoral artery via a surgically inserted catheter during 60-min small-animal PET scans. Image data were reconstructed by use of filtered backprojection with CT-based attenuation correction. We constructed a 5-compartment model designed to predict the plasma time-activity curve of 18 F-FDG by use of data from a minimum of 2 blood samples and the dynamic smallanimal PET scan. The plasma time-activity curve (TACp) was assumed to have 4 exponential components ðTAC P 5 A 1 e l1t 1 A 2 e l2t 1 A 3 e l3t 2 ðA 1 1 A 2 1 A 3 Þe l4t Þ based on the serial blood samples. Using Bayesian constraints, we fitted 2-compartment submodels of muscle and liver to small-animal PET data for these organs and simultaneously fitted the input (forcing) function to early small-animal PET LV data and 2 blood samples (;10 min and ;1 h). Results: The area under the estimated plasma time-activity curve had an overall Spearman correlation of 0.99 when compared with the area under the gold standard plasma time-activity curve calculated from multiple blood samples. Calculated organ uptake rates (Patlak K i ) based on the predicted plasma time-activity curve had a correlation of approximately 0.99 for liver, muscle, myocardium, and brain when compared with those based on the gold standard plasma time-activity curve. The model was also able to accurately predict the plasma time-activity curve under experimental conditions that resulted in different rates of clearance of the tracer from blood. Conclusion: We have developed a robust method for accurately estimating the plasma time-activity curve of 18 F-FDG by use of dynamic small-animal PET data and 2 blood samples.

The biodistribution of the drug analogue [(18)F]gefitinib suggests that it may be used to assess noninvasively the pharmacokinetics of gefitinib in patients by PET imaging. This is of clinical relevance, as insufficient intratumoral drug concentrations are considered to be a factor for resistance to gefitinib therapy. However, the highly nonspecific cellular binding of [(18)F]gefitinib may preclude the use of this imaging probe for noninvasive assessment of EGFR receptor status in patients.

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