Preclinical development of ZED8, an 89Zr immuno-PET reagent for monitoring tumor CD8 status in patients undergoing cancer immunotherapy.

BACKGROUND: ZED8 is a novel monovalent antibody labeled with zirconium-89 for the molecular imaging of CD8. This work describes nonclinical studies performed in part to provide rationale for and to inform expectations in the early clinical development of ZED8, such as in the studies outlined in clinical trial registry NCT04029181 [1]. METHODS: Surface plasmon resonance, X-ray crystallography, and flow cytometry were used to characterize the ZED8-CD8 binding interaction, its specificity, and its impact on T cell function. Immuno-PET with ZED8 was assessed in huCD8+ tumor-bearing mice and in non-human primates. Plasma antibody levels were measured by ELISA to determine pharmacokinetic parameters, and OLINDA 1.0 was used to estimate radiation dosimetry from image-derived biodistribution data. RESULTS: ZED8 selectively binds to human CD8α at a binding site approximately 9 Å from that of MHCI making mutual interference unlikely. The equilibrium dissociation constant (KD) is 5 nM. ZED8 binds to cynomolgus CD8 with reduced affinity (66 nM) but it has no measurable affinity for rat or mouse CD8. In a series of lymphoma xenografts, ZED8 imaging was able to identify different CD8 levels concordant with flow cytometry. In cynomolgus monkeys with tool compound 89Zr-aCD8v17, lymph nodes were conspicuous by imaging 24 h post-injection, and the pharmacokinetics suggested a flat-fixed first-in-human dose of 4 mg per subject. The whole-body effective dose for an adult human was estimated to be 0.48 mSv/MBq, comparable to existing 89Zr immuno-PET reagents. CONCLUSION: 89Zr immuno-PET with ZED8 appears to be a promising biomarker of tissue CD8 levels suitable for clinical evaluation in cancer patients eligible for immunotherapy.

Automated segmentation of lungs and lung tumors in mouse micro-CT scans.

Here, we have developed an automated image processing algorithm for segmenting lungs and individual lung tumors in in vivo micro-computed tomography (micro-CT) scans of mouse models of non-small cell lung cancer and lung fibrosis. Over 3000 scans acquired across multiple studies were used to train/validate a 3D U-net lung segmentation model and a Support Vector Machine (SVM) classifier to segment individual lung tumors. The U-net lung segmentation algorithm can be used to estimate changes in soft tissue volume within lungs (primarily tumors and blood vessels), whereas the trained SVM is able to discriminate between tumors and blood vessels and identify individual tumors. The trained segmentation algorithms (1) significantly reduce time required for lung and tumor segmentation, (2) reduce bias and error associated with manual image segmentation, and (3) facilitate identification of individual lung tumors and objective assessment of changes in lung and individual tumor volumes under different experimental conditions.

Effect of molecular size on interstitial pharmacokinetics and tissue catabolism of antibodies.

Advances in antibody engineering have enabled the construction of novel molecular formats in diverse shapes and sizes, providing new opportunities for biologic therapies and expanding the need to understand how various structural aspects affect their distribution properties. To assess the effect of antibody size on systemic pharmacokinetics (PK) and tissue distribution with or without neonatal Fc receptor (FcRn) binding, we evaluated a series of non-mouse-binding anti-glycoprotein D monoclonal antibody formats, including IgG [~150 kDa], one-armed IgG [~100 kDa], IgG-HAHQ (attenuated FcRn binding) [~150 kDa], F(ab')2 [~100 kDa], and F(ab) [~50 kDa]. Tissue-specific concentration-time profiles were corrected for blood content based on vascular volumes and normalized based on interstitial volumes to allow estimation of interstitial concentrations and interstitial:serum concentration ratios. Blood correction demonstrated that the contribution of circulating antibody on total uptake was greatest at early time points and for highly vascularized tissues. Tissue interstitial PK largely mirrored serum exposure profiles. Similar interstitial:serum ratios were obtained for the two FcRn-binding molecules, IgG and one-armed IgG, which reached pseudo-steady-state kinetics in most tissues. For non-FcRn-binding molecules, interstitial:serum ratios changed over time, suggesting that these molecules did not reach steady-state kinetics during the study. Furthermore, concentration-time profiles of both intact and catabolized molecule were measured by a dual tracer approach, enabling quantification of tissue catabolism and demonstrating that catabolism levels were highest for IgG-HAHQ. Overall, these data sets provide insight into factors affecting preclinical distribution and may be useful in estimating interstitial concentrations and/or catabolism in human tissues.

Valency of HER2 Targeting Antibodies Influences Tumor Cell Internalization and Penetration.

T-cell-dependent bispecific antibodies (TDB) have been a major advancement in the treatment of cancer, allowing for improved targeting and efficacy for large molecule therapeutics. TDBs are comprised of one arm targeting a surface antigen on a cancer cell and another targeting an engaging surface antigen on a cytotoxic T cell. To impart this function, the antibody must be in a bispecific format as opposed to the more conventional bivalent format. Through in vitro and in vivo studies, we sought to determine the impact of changing antibody valency on solid tumor distribution and catabolism. A bivalent anti-HER2 antibody exhibited higher catabolism than its full-length monovalent binding counterpart in vivo by both invasive tissue harvesting and noninvasive single photon emission computed tomography/X-ray computed tomography imaging despite similar systemic exposures for the two molecules. To determine what molecular factors drove in vivo distribution and uptake, we developed a mechanistic model for binding and catabolism of monovalent and bivalent HER2 antibodies in KPL4 cells. This model suggests that observed differences in cellular uptake of monovalent and bivalent antibodies are caused by the change in apparent affinity conferred by avidity as well as differences in internalization and degradation rates of receptor bound antibodies. To our knowledge, this is the first study to directly compare the targeting abilities of monovalent and bivalent full-length antibodies. These findings may inform diverse antibody therapeutic modalities, including T-cell-redirecting therapies and drug delivery strategies relying upon receptor internalization.

Imaging Reveals Importance of Shape and Flexibility for Glomerular Filtration of Biologics.

Advances in antibody engineering have enabled the construction of novel molecular formats in diverse shapes and sizes, providing new opportunities for cancer immunotherapeutic drug discovery while also revealing limitations in knowledge of structure-activity relationships. The current understanding of renal filtration originates largely from data reported for dextrans, IgG, albumin, and selected globular proteins. For a one-armed IgG-based T-cell imaging agent, we observed higher renal signal than typically observed for bivalent IgGs, prompting us to explore the factors governing renal filtration of biologics. We constructed a small representative library of IgG-like formats with varied shapes and hinge flexibilities falling broadly into two categories: branched molecules including bivalent IgG and (scFv)2Fc, and nonbranched molecules including one-armed IgG, one-armed IgG with stacked Fab, and one-armed IgG with a rigid IgA2 hinge. Transmission electron microscopy revealed Y-shaped structures for the branched molecules and pseudo-linear structures for the nonbranched molecules. Single-photon emission CT imaging, autoradiography, and tissue harvest studies demonstrated higher renal uptake and catabolism for nonbranched molecules relative to branched molecules. Among the nonbranched molecules, the one-armed IgG with rigid IgA2 hinge molecule demonstrated higher kidney uptake and decreased systemic exposure relative to molecules with a more flexible hinge. Our results show that differences in shape and hinge flexibility drive the increased glomerular filtration of one-armed relative to bivalent antibodies and highlight the practical advantages of using imaging to assess renal filtration properties. These findings are particularly relevant for T-cell-dependent bispecific molecules, many of which have nonstandard antibody structures.

Mechanistic Modeling of Soluble Aß Dynamics and Target Engagement in the Brain by Anti-Aß mAbs in Alzheimer's Disease.

BACKGROUND: Anti-amyloid-ß (Aß) monoclonal antibodies (mAbs) are currently in development for treating Alzheimer's disease. OBJECTIVES: To address the complexity of Aß target engagement profiles, improve the understanding of crenezumab Pharmacokinetics (PK) and Aß Pharmacodynamics (PD) in the brain, and facilitate comparison of anti-Aß therapies with different binding characteristics. METHODS: A mechanistic mathematical model was developed describing the distribution, elimination, and binding kinetics of anti-Aß mAbs and Aß (monomeric and oligomeric forms of Aß1-40 and Aß1-42) in the brain, Cerebrospinal Fluid (CSF), and plasma. Physiologically meaningful values were assigned to the model parameters based on the previous data, with remaining parameters fitted to clinical measurements of Aß concentrations in CSF and plasma, and PK/PD data of patients undergoing anti-Aß therapy. Aß target engagement profiles were simulated using a Monte Carlo approach to explore the impact of biological uncertainty in the model parameters. RESULTS: Model-based estimates of in vivo affinity of the antibody to monomeric Aß were qualitatively consistent with the previous data. Simulations of Aß target engagement profiles captured observed mean and variance of clinical PK/PD data. CONCLUSION: This model is useful for comparing target engagement profiles of different anti-Aß therapies and demonstrates that 60 mg/kg crenezumab yields a significant increase in Aß engagement compared with lower doses of solanezumab, supporting the selection of 60 mg/kg crenezumab for phase 3 studies. The model also provides evidence that the delivery of sufficient quantities of mAb to brain interstitial fluid is a limiting step with respect to the magnitude of soluble Aß oligomer neutralization.

Effect of Modulating FcRn Binding on Direct and Pretargeted Tumor Uptake of Full-length Antibodies.

Full-length antibodies lack ideal pharmacokinetic properties for rapid targeted imaging, prompting the pursuit of smaller peptides and fragments. Nevertheless, studying the disposition properties of antibody-based imaging agents can provide critical insight into the pharmacology of their therapeutic counterparts, particularly for those coupled with potent payloads. Here, we evaluate modulation of binding to the neonatal Fc receptor (FcRn) as a protein engineering-based pharmacologic strategy to minimize the overall blood pool background with directly labeled antibodies and undesirable systemic click reaction of radiolabeled tetrazine with circulating pretargeted trans-cyclooctene (TCO)-modified antibodies. Noninvasive SPECT imaging of mice bearing HER2-expressing xenografts was performed both directly (111In-labeled antibody) and indirectly (pretargeted TCO-modified antibody followed by 111In-labeled tetrazine). Pharmacokinetic modulation of antibodies was achieved by two distinct methods: Fc engineering to reduce binding affinity to FcRn, and delayed administration of an antibody that competes with binding to FcRn. Tumor imaging with directly labeled antibodies was feasible in the absence of FcRn binding, rapidly attaining high tumor-to-blood ratios, but accompanied by moderate liver and spleen uptake. Pretargeted imaging of tumors with non-FcRn-binding antibody was also feasible, but systemic click reaction still occurred, albeit at lower levels than with parental antibody. Our findings demonstrate that FcRn binding impairment of full-length IgG antibodies moderately lowers tumor accumulation of radioactivity, and shifts background activity from blood pool to liver and spleen. Furthermore, reduction of FcRn binding did not eliminate systemic click reaction, but yielded greater improvements in tumor-to-blood ratio when imaging with directly labeled antibodies than with pretargeting.

Biodistribution and efficacy of an anti-TENB2 antibody-drug conjugate in a patient-derived model of prostate cancer.

TENB2, a transmembrane proteoglycan protein, is a promising target for antibody drug conjugate (ADC) therapy due to overexpression in human prostate tumors and rapid internalization. We previously characterized how predosing with parental anti-TENB2 monoclonal antibody (mAb) at 1 mg/kg in a patient-derived LuCap77 explant model with high (3+) TENB2 expression could (i) block target-mediated intestinal uptake of tracer (& 0.1 mg/kg) levels of radiolabeled anti-TENB2-monomethyl auristatin E ADC while preserving tumor uptake, and (ii) maintain efficacy relative to ADC alone. Here, we systematically revisit this strategy to evaluate the effects of predosing on tumor uptake and efficacy in LuCap96.1, a low TENB2-expressing (1+) patient-derived model that is more responsive to ADC therapy than LuCap77. Importantly, rather than using tracer (& 0.1 mg/kg) levels, radiolabeled ADC tumor uptake was assessed at 1 mg/kg - one of the doses evaluated in the tumor growth inhibition study - in an effort to bridge tissue distribution (PK) with efficacy (PD). Predosing with mAb up to 1 mg/kg had no effect on efficacy. These findings warrant further investigations to determine whether predosing prior to ADC therapy might improve therapeutic index by preventing ADC disposition and possible toxicological liabilities in antigen-expressing healthy tissues.

VCAM-1 Density and Tumor Perfusion Predict T-cell Infiltration and Treatment Response in Preclinical Models.

Cancer immunotherapies have demonstrated durable responses in a range of different cancers. However, only a subset of patients responds to these therapies. We set out to test if non-invasive imaging of tumor perfusion and vascular inflammation may be able to explain differences in T-cell infiltration in pre-clinical tumor models, relevant for treatment outcomes. Tumor perfusion and vascular cell adhesion molecule (VCAM-1) density were quantified using magnetic resonance imaging (MRI) and correlated with infiltration of adoptively transferred and endogenous T-cells. MRI biomarkers were evaluated for their ability to detect tumor rejection 3 days after T-cell transfer. Baseline levels of these markers were used to assess their ability to predict PD-L1 treatment response. We found correlations between MRI-derived VCAM-1 density and infiltration of endogenous or adoptively transferred T-cells in some preclinical tumor models. Blocking T-cell binding to endothelial cell adhesion molecules (VCAM-1/ICAM) prevented T-cell mediated tumor rejection. Tumor rejection could be detected 3 days after adoptive T-cell transfer prior to tumor volume changes by monitoring the extracellular extravascular volume fraction. Imaging tumor perfusion and VCAM-1 density before treatment initiation was able to predict the response of MC38 tumors to PD-L1 blockade. These results indicate that MRI based assessment of tumor perfusion and VCAM-1 density can inform about the permissibility of the tumor vasculature for T-cell infiltration which may explain some of the observed variance in treatment response for cancer immunotherapies.

Tissue Physiology of Cynomolgus Monkeys: Cross-Species Comparison and Implications for Translational Pharmacology.

We previously performed a comparative assessment of tissue-level vascular physiological parameters in mice and rats, two of the most commonly utilized species in translational drug development. The present work extends this effort to non-human primates by measuring tissue- and organ-level vascular volumes (Vv), interstitial volumes (Vi), and blood flow rates (Q) in cynomolgus monkeys. These measurements were accomplished by red blood cell labeling, extracellular marker infusion, and rubidium chloride bolus distribution, respectively, the same methods used in previous rodent measurements. In addition, whole-body blood volumes (BV) were determined across species. The results demonstrate that Vv, Vi, and Q, measured using our methods scale approximately by body weight across mouse, rat, and monkey in the tissues considered here, where allometric analysis allowed extrapolation to human parameters. Significant differences were observed between the values determined in this study and those reported in the literature, including Vv in muscle, brain, and skin and Q in muscle, adipose, heart, thymus, and spleen. The impact of these differences for selected tissues was evaluated via sensitivity analysis using a physiologically based pharmacokinetic model. The blood-brain barrier in monkeys was shown to be more impervious to an infused radioactive tracer, indium-111-pentetate, than in mice or rats. The body weight-normalized total BV measured in monkey agreed well with previously measured value in rats but was lower than that in mice. These findings have important implications for the common practice of scaling physiological parameters from rodents to primates in translational pharmacology.

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

Antibody pretargeting is a promising strategy for improving molecular imaging, wherein the separation in time of antibody targeting and radiolabeling can lead to rapid attainment of high contrast, potentially increased sensitivity, and reduced patient radiation exposure. The inverse electron demand Diels-Alder 'click' reaction between trans-cyclooctene (TCO) conjugated antibodies and radiolabeled tetrazines presents an ideal platform for pretargeted imaging due to rapid reaction kinetics, bioorthogonality, and potential for optimization of both slow and fast clearing components. Herein, we evaluated a series of anti-human epidermal growth factor receptor 2 (HER2) pretargeting antibodies containing distinct molar ratios of site-specifically incorporated TCO. The effect of stoichiometry on tissue distribution was assessed for pretargeting TCO-modified antibodies (monitored by 125I) and subsequent accumulation of an 111In-labeled tetrazine in a therapeutically relevant HER2+tumor-bearing mouse model. Single photon emission computed tomography (SPECT) imaging was also employed to assess tumor imaging at various TCO-to-monoclonal antibody (mAb) ratios. Increasing TCO-to-mAb molar ratios correlated with increased in vivo click reaction efficiency evident by increased tumor distribution and systemic exposure of 111In-labeled tetrazines. The pharmacokinetics of TCO-modified antibodies did not vary with stoichiometry. Pretargeted SPECT imaging of HER2-expressing tumors using 111In-labeled tetrazine demonstrated robust click reaction with circulating antibody at ~2 hours and good tumor delineation for both the 2 and 6 TCO-to-mAb ratio variants at 24 hours, consistent with a limited cell-surface pool of pretargeted antibody and benefit from further distribution and internalization. To our knowledge, this represents the first reported systematic analysis of how pretargeted imaging is affected solely by variation in click reaction stoichiometry through site-specific conjugation chemistry.

A Preclinical Population Pharmacokinetic Model for Anti-CD20/CD3 T-Cell-Dependent Bispecific Antibodies.

CD20 is a cell-surface receptor expressed by healthy and neoplastic B cells and is a well-established target for biologics used to treat B-cell malignancies. Pharmacokinetic (PK) and pharmacodynamic (PD) data for the anti-CD20/CD3 T-cell-dependent bispecific antibody BTCT4465A were collected in transgenic mouse and nonhuman primate (NHP) studies. Pronounced nonlinearity in drug elimination was observed in the murine studies, and time-varying, nonlinear PK was observed in NHPs, where three empirical drug elimination terms were identified using a mixed-effects modeling approach: i) a constant nonsaturable linear clearance term (7 mL/day/kg); ii) a rapidly decaying time-varying, linear clearance term (t½  = 1.6 h); and iii) a slowly decaying time-varying, nonlinear clearance term (t½  = 4.8 days). The two time-varying drug elimination terms approximately track with time scales of B-cell depletion and T-cell migration/expansion within the central blood compartment. The mixed-effects NHP model was scaled to human and prospective clinical simulations were generated.

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

The mechanisms of absorption, distribution, metabolism and elimination of small and large molecule therapeutics differ significantly from one another and can be explored within the framework of a physiologically based pharmacokinetic (PBPK) model. This paper briefly reviews fundamental approaches to PBPK modeling, in which drug kinetics within tissues and organs are explicitly represented using physiologically meaningful parameters. The differences in PBPK models applied to small/large molecule drugs are highlighted, thus elucidating differences in absorption, distribution and elimination properties between these two classes of drugs in a systematic manner. The absorption of small and large molecules differs with respect to their common extravascular routes of delivery (oral versus subcutaneous). The role of the lymphatic system in drug distribution, and the involvement of tissues as sites of elimination (through catabolism and target mediated drug disposition) are unique features of antibody distribution and elimination that differ from small molecules, which are commonly distributed into the tissues but are eliminated primarily by liver metabolism. Fundamental differences exist in the ability to predict human pharmacokinetics based upon preclinical data due to differing mechanisms governing small and large molecule disposition. These differences have influence on the evolving utilization of PBPK modeling in the discovery and development of small and large molecule therapeutics.

GPU-accelerated compartmental modeling analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab.

The compartment model analysis using medical imaging data is the well-established but extremely time consuming technique for quantifying the changes in microvascular physiology of targeted organs in clinical patients after antivascular therapies. In this paper, we present a first graphics processing unit-accelerated method for compartmental modeling of medical imaging data. Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing accuracy. This approach reduced the computation time by more than 120-fold comparing to a central processing unit-based method that performed the analogous analysis steps in serial and more than 17-fold comparing to the algorithm that optimized for central processing unit computation. The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data in preclinical and clinical development of antivascular therapies and related fields.

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

PURPOSE: Most dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort. MATERIALS AND METHODS: Data from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K(trans) were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K(trans) by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients. RESULTS: The typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%. CONCLUSION: The MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K(trans) arising from therapy induced changes in the volume of enhancing tumor.

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

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is often used to examine vascular function in malignant tumors and noninvasively monitor drug efficacy of antivascular therapies in clinical studies. However, complex numerical methods used to derive tumor physiological properties from DCE-MRI images can be time-consuming and computationally challenging. Recent advancement of computing technology in graphics processing unit (GPU) makes it possible to build an energy-efficient and high-power parallel computing platform for solving complex numerical problems. This study develops the first reported fast GPU-based method for nonparametric kinetic analysis of DCE-MRI data using clinical scans of glioblastoma patients treated with bevacizumab (Avastin®). In the method, contrast agent concentration-time profiles in arterial blood and tumor tissue are smoothed using a robust kernel-based regression algorithm in order to remove artifacts due to patient motion and then deconvolved to produce the impulse response function (IRF). The area under the curve (AUC) and mean residence time (MRT) of the IRF are calculated using statistical moment analysis, and two tumor physiological properties that relate to vascular permeability, volume transfer constant between blood plasma and extravascular extracellular space (K(trans)) and fractional interstitial volume (ve) are estimated using the approximations AUC/MRT and AUC. The most significant feature in this method is the use of GPU-computing to analyze data from more than 60,000 voxels in each DCE-MRI image in parallel fashion. All analysis steps have been automated in a single program script that requires only blood and tumor data as the sole input. The GPU-accelerated method produces K(trans) and ve estimates that are comparable to results from previous studies but reduces computational time by more than 80-fold compared to a previously reported central processing unit-based nonparametric method. Furthermore, it is at least several orders of magnitudes faster than standard parametric methods that perform compartmental modeling. This finding indicates that the GPU-based method can significantly shorten the computational times required to assess tumor physiology from DCE-MRI data in preclinical and clinical development of antivascular therapies.

Effects of anti-VEGF on predicted antibody biodistribution: roles of vascular volume, interstitial volume, and blood flow.

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.

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

Identification of clinically predictive models of disposition kinetics for antibody therapeutics is an ongoing pursuit in drug development. To encourage translation of drug candidates from early research to clinical trials, clinical diagnostic agents may be used to characterize antibody disposition in physiologically relevant preclinical models. TechneScan PYP was employed to measure tissue vascular volumes (V(v)) in healthy mice. Two methods of red blood cell (RBC) labeling were compared: a direct in vivo method that is analogous to a clinical blood pool imaging protocol, and an indirect method in which radiolabeled blood was transfused from donor mice into recipient mice. The indirect method gave higher precision in RBC labeling yields, lower V(v) values in most tissues, and lower (99m)Tc uptake in kidneys and bladder by single photon emission computed tomographic (SPECT) imaging relative to the direct method. Furthermore, the relative influence of each method on the calculated area under the first 7 days of the concentration-time curve (AUC(0-7)) of an IgG in nude mice was assessed using a physiologically based pharmacokinetic model. The model was sensitive to the source of V(v) values, whether obtained from the literature or measured by either method, when used to predict experimental AUC(0-7) values for radiolabeled trastuzumab in healthy murine tissues. In summary, a novel indirect method for preclinical determination of V(v) offered higher precision in RBC labeling efficiency and lower renal uptake of (99m)Tc than the direct method. In addition, these observations emphasize the importance of obtaining accurate physiological parameter values for modeling antibody uptake.

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 AUCMRT and AUC of the Impulse response function closely approximate fractional clearance from plasma to tissue (K(trans)) and fractional interstitial volume (v(e)). Intervisit variability is shown to be comparable when using the deconvolution method (11% [AUCMRT] and 13%[AUC]) compared to the Tofts model (14%[K(trans)] and 24%[v(e)]). AUC and AUCMRT both exhibit a statistically significant decrease (P < 0.005) 1 day after administration of bevacizumab.