Gregory Z. Ferl

A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn)

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.

A two-tiered physiologically based model for dually labeled single-chain Fv-Fc antibody fragments

Monoclonal antibodies (mAb) are being used at an increasing rate in the treatment of cancer, with current efforts focused on developing engineered antibodies that exhibit optimal biodistribution profiles for imaging and/or radioimmunotherapy. We recently developed the single-chain Fv-Fc (scFv-Fc) mAb, which consists of a single-chain antibody Fv fragment (light-chain and heavy-chain variable domains) coupled to the IgG1 Fc region. Point mutations that attenuate binding affinity to FcRn were introduced into the Fc region of the wild-type scFv-Fc mAb, resulting in several new antibodies, each with a different half-life. Here, we describe the construction of a two-tiered physiologically based pharmacokinetic model capable of simulating the apparent biodistribution of both 111In- and 125I-labeled scFv-Fc mAbs, where 111In-labeled metabolites from degraded 111In-labeled mAbs tend to become trapped within the lysosomal compartment, whereas free 125I from degraded 125I-labeled mAbs is quickly eliminated via the urinary pathway. The different concentration-time profiles of 111In- and 125I-labeled mAbs permits estimation of the degradation capacity of each organ and elucidates the dependence of cumulative degradation in liver, muscle, and skin on FcRn affinity and tumor mass. Liver is estimated to account for ∼50% of all degraded mAb when tumor is small (∼0.1 g) and drops to about 35% when tumor mass is larger (∼0.3 g). mAb degradation in residual carcass (primarily skin and muscle) decreases from ∼45% to 16% as FcRn affinity of the three mAb variants under consideration increases. In addition, elimination of a small amount of mAb in the kidneys is shown to be required for a successful fit of model to data. [Mol Cancer Ther 2006;5(6):1550–8]

An automated method for nonparametric kinetic analysis of clinical DCE-MRI data: application to glioblastoma treated with bevacizumab.

Here, we describe an automated nonparametric method for evaluating gadolinium‐diethylene triamine pentaacetic acid (Gd‐DTPA) kinetics, based on dynamic contrast‐enhanced–MRI scans of glioblastoma patients taken before and after treatment with bevacizumab; no specific model or equation structure is assumed or used. Tumor and venous blood concentration‐time profiles are smoothed, using a robust algorithm that removes artifacts due to patient motion, and then deconvolved, yielding an impulse response function. In addition to smoothing, robustness of the deconvolution operation is assured by excluding data that occur prior to the plasma peak; an exhaustive analysis was performed to demonstrate that exclusion of the prepeak plasma data does not significantly affect results. All analysis steps are executed by a single R script that requires blood and tumor curves as the sole input. Statistical moment analysis of the Impulse response function yields the area under the curve (AUC) and mean residence time (MRT). Comparison of deconvolution results to fitted Tofts model parameters suggests that

Effects of Anti-VEGF on Predicted Antibody Biodistribution: Roles of Vascular Volume, Interstitial Volume, and Blood Flow

{{AUC} \over {{\rm MRT}}}

Development and evaluation of a novel method for preclinical measurement of tissue vascular volume.

and AUC of the Impulse response function closely approximate fractional clearance from plasma to tissue (Ktrans) and fractional interstitial volume (ve) . Intervisit variability is shown to be comparable when using the deconvolution method (11% [

Physiologically based pharmacokinetic models of small molecules and therapeutic antibodies: a mini-review on fundamental concepts and applications

{{AUC} \over {{\rm MRT}}}

GPU-accelerated nonparametric kinetic analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab

] and 13%[AUC]) compared to the Tofts model (14%[Ktrans] and 24%[ve]). AUC and

Mixed-effects modeling of clinical DCE-MRI data: Application to colorectal liver metastases treated with bevacizumab

{{AUC} \over {{\rm MRT}}}

GPU-Accelerated Compartmental Modeling Analysis of DCE-MRI Data from Glioblastoma Patients Treated with Bevacizumab

both exhibit a statistically significant decrease (P < 0.005) 1 day after administration of bevacizumab. Magn Reson Med 63:1366–1375, 2010.

Site-specific conjugation allows modulation of click reaction stoichiometry for pretargeted SPECT imaging

Background The identification of clinically meaningful and predictive models of disposition kinetics for cancer therapeutics is an ongoing pursuit in drug development. In particular, the growing interest in preclinical evaluation of anti-angiogenic agents alone or in combination with other drugs requires a complete understanding of the associated physiological consequences. Methodology/Principal Findings Technescan™ PYP™, a clinically utilized radiopharmaceutical, was used to measure tissue vascular volumes in beige nude mice that were naïve or administered a single intravenous bolus dose of a murine anti-vascular endothelial growth factor (anti-VEGF) antibody (10 mg/kg) 24 h prior to assay. Anti-VEGF had no significant effect (p>0.05) on the fractional vascular volumes of any tissues studied; these findings were further supported by single photon emission computed tomographic imaging. In addition, apart from a borderline significant increase (p = 0.048) in mean hepatic blood flow, no significant anti-VEGF-induced differences were observed (p>0.05) in two additional physiological parameters, interstitial fluid volume and the organ blood flow rate, measured using indium-111-pentetate and rubidium-86 chloride, respectively. Areas under the concentration-time curves generated by a physiologically-based pharmacokinetic model changed substantially (>25%) in several tissues when model parameters describing compartmental volumes and blood flow rates were switched from literature to our experimentally derived values. However, negligible changes in predicted tissue exposure were observed when comparing simulations based on parameters measured in naïve versus anti-VEGF-administered mice. Conclusions/Significance These observations may foster an enhanced understanding of anti-VEGF effects in murine tissues and, in particular, may be useful in modeling antibody uptake alone or in combination with anti-VEGF.