Pharmacokinetic mAb-mAb interaction: anti-VEGF mAb decreases the distribution of anti-CEA mAb into colorectal tumor xenografts

Integrated PK/PD Modeling Relates Smoothened Inhibitor Biomarkers to The Heterogeneous Intratumor Disposition of Cetuximab in Pancreatic Cancer Tumor Models

Therapeutic antibodies have shown little efficacy in the treatment of pancreatic ductal adenocarcinomas (PDAC). Tumor desmoplasia, hypovascularity, and poor perfusion result in insufficient tumor cell exposure, contributing to treatment failure. Smoothened inhibitors of hedgehog signaling (sHHi) increase PDAC tumor permeability, perfusion, and drug delivery, and provide a tool to develop a quantitative, mechanistic understanding as to how the temporal dynamics of tumor priming can impact intratumor distribution of monoclonal antibodies (mAb). A linked pharmacokinetic (PK)/pharmacodynamic (PD) model was developed to integrate the plasma and tumor PK of a sHHi priming agent with its effects upon downstream stromal biomarkers Gli1, hyaluronic acid, and interstitial fluid pressure in PDAC patient-derived xenograft (PDX) tumors. In parallel, in situ tumor concentrations of cetuximab (CTX: anti-epidermal growth factor receptor; EGFR) were quantified as a marker for tumor delivery of mAb or antibody-drug conjugates. A minimal, physiologically-based pharmacokinetic (mPBPK) model was constructed to link sHHi effects upon mechanistic effectors of tumor barrier compromise with the intratumor distribution of CTX, and CTX occupancy of EGFR in tumors. Integration of the mPBPK model of mAb deposition and intratumor distribution with the PK/PD model of tumor responses to priming not only identified physiological parameters that are critical for tumor antibody distribution, but also provides insight into dosing regimens that could achieve maximal tumor disposition of therapeutic antibodies under conditions of transient PDAC tumor permeability barrier compromise that mechanistically-diverse tumor priming strategies may achieve.

A Non-radiometric Approach to Determine Tissue Vascular Blood Volume in Biodistribution Studies

The aim of this research was to develop a reliable non-radiometric method to measure the residual blood in tissue without the need for perfusion or radiometric measurements in biodistribution studies. It was found that the perfusion method not only was ineffective in removing blood from tissue, but also introduced additional variability in the determination of tissue drug exposure and was not reproducible across studies. In addition, the use of hemoglobin as an endogenous protein and biomarker for tissue blood content was studied and it was found that hemoglobin measurement in tissue was not a reliable and effective approach for determination of residual blood level in tissue. To evaluate an alternative method for addressing the tissue blood level in biodistribution studies, animals were dosed with a Residual Blood Determinant Reagent (RBDR) 5 min prior to tissue harvesting. The level of RBDR, an exogenous protein, was measured in whole blood homogenate and in tissue lysate. Based on the level of the RBDR, the vascular blood volume (VBV) in tissue was calculated and then the tissue exposures were corrected based on the blood volumes. The tissue VBVs measured by the RBDR method were comparable with the literature values obtained by radiometric measurements.

IOLite: phase 1b trial of doublet/triplet combinations of dostarlimab with niraparib, carboplatin-paclitaxel, with or without bevacizumab in patients with advanced cancer

BACKGROUND

Doublet combination therapies targeting immune checkpoints have shown promising efficacy in patients with advanced solid tumors, but it is unknown if rational triplet combinations will be well tolerated and associated with improved antitumor activity. The objective of this trial was to determine the recommended phase 2 doses (RP2Ds) and to assess the safety and efficacy of the programmed cell death protein 1 (PD-1) inhibitor dostarlimab in combination with (1) the poly(ADP-ribose) polymerase inhibitor niraparib with or without vascular endothelial growth factor inhibitor bevacizumab or (2) carboplatin-paclitaxel chemotherapy with or without bevacizumab, in patients with advanced cancer.

METHODS

IOLite is a multicenter, open-label, multi-arm clinical trial. Patients with advanced solid tumors were enrolled. Patients received dostarlimab in combination with niraparib with or without bevacizumab or in combination with carboplatin-paclitaxel with or without bevacizumab until disease progression, unacceptable toxicity, or withdrawal from the study. Prespecified endpoints in all parts were to evaluate the dose-limiting toxicities (DLTs), RP2Ds, pharmacokinetics (PKs), and preliminary efficacy for each combination.

RESULTS

A total of 55 patients were enrolled; patients received dostarlimab and: (1) niraparib in part A (n=22); (2) carboplatin-paclitaxel in part B (n=14); (3) niraparib plus bevacizumab in part C (n=13); (4) carboplatin-paclitaxel plus bevacizumab in part D (n=6). The RP2Ds of all combinations were determined. All combinations were safe and tolerable, with no new safety signals observed. DLTs were reported in 2, 1, 2, and 0 patients, in parts A-D, respectively. Preliminary antitumor activity was observed, with confirmed Response Evaluation Criteria in Solid Tumors v1.1 complete/partial responses reported in 4 of 22 patients (18.2%), 6 of 14 patients (42.9%), 4 of 13 patients (30.8%), and 3 of 6 (50.0%) patients, in parts A-D, respectively. Disease control rates were 40.9%, 57.1%, 84.6%, and 83.3%, in parts A-D, respectively. Dostarlimab PK was unaffected by any combinations tested. Coadministration of bevacizumab showed no impact on niraparib PKs. The overall mean PD-1 receptor occupancy was 99.0%.

CONCLUSIONS

Dostarlimab was well tolerated in both doublet and triplet regimens tested, with promising antitumor activity observed with all combinations. We observed higher disease control rates in the triplet regimens than in doublet regimens.

TRIAL REGISTRATION NUMBER

NCT03307785.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

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.

Transient Competitive Inhibition Bypasses the Binding Site Barrier to Improve Tumor Penetration of Trastuzumab and Enhance T-DM1 Efficacy

Poor penetration of mAbs in solid tumors is explained, in part, by the binding site barrier hypothesis. Following extravasation, mAbs rapidly bind cellular antigens, leading to the observation that, at subsaturating doses, therapeutic antibody in solid tumors localizes around tumor vasculature. Here we report a unique strategy to overcome the binding site barrier through transient competitive inhibition of antibody-antigen binding. The anti-trastuzumab single domain antibody 1HE was identified through in vitro binding assays as a model inhibitor. Coadministration of 1HE did not alter the plasma pharmacokinetics of trastuzumab or ado-trastuzumab emtansine (T-DM1) in vivo. Administration of 1HE alone was rapidly eliminated with a terminal plasma half-life of 1.2 hours, while coadministrations of 1HE with trastuzumab had a terminal half-life of 56 hours. In mice harboring SKOV3 xenografts, coadministration of 1HE with trastuzumab led to significant increases in both penetration of trastuzumab from vasculature and the percentage of tumor area that stained positive for trastuzumab. 1HE coadministered with a single dose of T-DM1 to NCI-N87 xenograft-bearing mice significantly enhanced T-DM1 efficacy, increasing median survival. These results support the hypothesis that transient competitive inhibition can improve therapeutic antibody distribution in solid tumors and enhance antibody efficacy. SIGNIFICANCE: This study describes the development of a transient competitive inhibition strategy that enhances the tumor penetration and efficacy of anticancer antibodies.See related commentary by van Dongen, p. 3956.

Threshold Change in CEA as a Predictor of Non-Progression to First-Line Systemic Therapy in Metastatic Colorectal Cancer Patients With Elevated CEA

BACKGROUND

Carcinoembryonic antigen (CEA) levels are used in conjunction with imaging to monitor response to systemic therapy in metastatic colorectal cancer (mCRC). We sought to identify a threshold for CEA change from baseline to predict progressive disease (PD) in mCRC patients receiving first-line therapy.

METHODS

Patients from trials collected in the ARCAD database were included if baseline CEA was at least 10 ng/mL and repeat CEA was available within 14 days of first restaging scan. Optimal cutoffs for CEA change were identified by receiver operating characteristic analysis. Prediction performance of cutoffs was evaluated by sensitivity, specificity, and negative predictive value. Analyses were conducted by treatment class: chemotherapy alone, chemotherapy with anti-VEGF antibody, and chemotherapy with anti-EGFR antibody.

RESULTS

A total of 2643 mCRC patients treated with systemic therapy were included. Median percent change of CEA from baseline to first restaging for patients with complete response, partial response, or stable disease (non-PD) and PD was -53.1% and +23.6% for chemotherapy alone (n = 957) and -71.7% and -45.3% for chemotherapy with anti-VEGF antibody (n = 1355). The optimal area under the curve cutoff for differentiating PD from non-PD on first restaging was -7.5% for chemotherapy alone and -62.0% for chemotherapy with anti-VEGF antibody; chemotherapy alone, adjusted odds ratio = 6.51 (95% CI = 3.31 to 12.83, P < .001), chemotherapy with anti-VEGF antibody, adjusted odds ratio = 3.45 (95% CI = 1.93 to 6.18, P < .001). A 99% negative predictive value clinical cutoff for prediction of non-PD would avoid CT scan at first restaging in 21.0% of chemotherapy alone and 16.2% of chemotherapy with anti-VEGF antibody-treated patients. Among patients with stable disease on first restaging, those with decreased CEA from baseline had statistically significantly improved progression-free and overall survival.

CONCLUSIONS

Change in CEA from baseline to first restaging can accurately predict non-progression and correlates with long-term outcomes in patients receiving systemic chemotherapy.

Understanding Inter-Individual Variability in Monoclonal Antibody Disposition

Monoclonal antibodies (mAbs) are currently the largest and most dominant class of therapeutic proteins. Inter-individual variability has been observed for several mAbs; however, an understanding of the underlying mechanisms and factors contributing to inter-subject differences in mAb disposition is still lacking. In this review, we analyze the mechanisms of antibody disposition and the putative mechanistic determinants of inter-individual variability. Results from in vitro, preclinical, and clinical studies were reviewed evaluate the role of the neonatal Fc receptor and Fc gamma receptors (expression and polymorphism), target properties (expression, shedding, turnover, internalization, heterogeneity, polymorphism), and the influence of anti-drug antibodies. Particular attention is given to the influence of co-administered drugs and disease, and to the physiological relevance of covariates identified by population pharmacokinetic modeling, as determinants of variability in mAb pharmacokinetics.

Physiologically Based Modeling of the Pharmacokinetics of "Catch-and-Release" Anti-Carcinoembryonic Antigen Monoclonal Antibodies in Colorectal Cancer Xenograft Mouse Models

Engineered monoclonal antibodies (mAbs) with pH-sensitive target release, or "catch-and-release" (CAR) binding, have shown promise in decreasing the extent of target-mediated mAb elimination, increasing mAb exposure, and increasing dose potency. This study developed a mechanistic physiologically based pharmacokinetic (PBPK) model to evaluate the effects of pH-sensitive CAR target binding on the disposition of anti-carcinoembryonic antigen (CEA) mAbs in mouse models of colorectal cancer. The PBPK model was qualified by comparing model-predicted plasma concentration-time data with data observed in tumor-bearing mice following the administration of T84.66, a "standard" anti-CEA mAb that demonstrates strong binding at pH 7.4 and 5.5. Further simulations evaluated the effects CAR pH-dependent binding, with decreasing CEA affinity with decreasing pH, on anti-CEA mAb plasma pharmacokinetics. Simulated data were compared with data observed for a novel CAR mAb, 10H6. The PBPK model provided precise parameter estimates, and excellent data characterization (median prediction error 18.4%) following fitting to T84.66 data. Simulations well predicted 10H6 data (median prediction error 21.4%). Sensitivity analyses demonstrated that key determinants of the disposition of CAR mAbs include the following: antigen binding affinity, the rate constant of mAb-CEA dissociation in acidified endosomes, antigen concentration, and the tumor vasculature reflection coefficient.

"Catch-and-Release" Anti-Carcinoembryonic Antigen Monoclonal Antibody Leads to Greater Plasma and Tumor Exposure in a Mouse Model of Colorectal Cancer

In this study, we examined the effects of target expression, neonatal Fc receptor (FcRn) expression in tumors, and pH-dependent target binding on the disposition of monoclonal antibodies (mAbs) in murine models of colorectal cancer. A panel of anti-carcinoembryonic antigen (CEA) mAbs was developed via standard hybridoma technology and then evaluated for pH-dependent CEA binding. Binding was assessed via immunoassay and radioligand binding assays. 10H6, a murine IgG1 mAb with high affinity for CEA at pH = 7.4 (K_D = 12.6 ± 1.7 nM) and reduced affinity at pH = 6.0 (K_D = 144.6 ± 21.8 nM), and T84.66, which exhibits pH-independent CEA binding (K_D = 1.1 ± 0.11 and 1.4 ± 0.16 nM at pH 7.4 and 6.0), were selected for pharmacokinetic investigations. We evaluated pharmacokinetics after intravenous administration to control mice and to mice bearing tumors with (MC38^CEA+, LS174T) and without (MC38^CEA-) CEA expression and with or without expression of murine FcRn, at doses of 0.1, 1, and 10 mg/kg. 10H6 displayed linear pharmacokinetics in mice bearing MC38^CEA+ or MC38^CEA- tumors. T84.66 displayed linear pharmacokinetics in mice with MC38^CEA- tumors but dose-dependent nonlinear pharmacokinetics in mice bearing MC38^CEA+ In addition to the improved plasma pharmacokinetic profile (i.e., linear pharmacokinetics, longer terminal half-life), 10H6 exhibited improved exposure in MC38^CEA+ tumors relative to T84.66. In mice bearing tumors with CEA expression, but lacking expression of murine FcRn (LS174T), 10H6 demonstrated nonlinear pharmacokinetics, with rapid clearance at low dose. These data are consistent with the hypothesis that pH-dependent CEA binding allows mAb dissociation from target in acidified endosomes, enabling FcRn-mediated protection from target-mediated elimination in mice bearing MC38^CEA+ tumors.

Tumor-Specific Labeling of Pancreatic Cancer Using a Humanized Anti-CEA Antibody Conjugated to a Near-Infrared Fluorophore

BACKGROUND/PURPOSE

Development of a humanized fluorophore-conjugated antibody that can improve contrast for fluorescence-guided oncologic surgeries.

METHODS

BxPC-3-GFP pancreatic cancer cells were injected into flanks of nude mice. Fragments of subcutaneous tumors were grafted onto the pancreatic tail of recipient mice to create orthotopic xenograft models of pancreatic cancer. After tumors developed for 4 weeks, a humanized anti-carcinoembryonic antigen antibody conjugated to an 800 nm near-infrared fluorescent dye (hM5A-IR800) was injected intravenously. Mice were imaged at 6, 12, 24, 48, and 72 h after injection.

RESULTS

Fluorescence imaging showed that hM5A-IR800 specifically localized to BxPC-3 human pancreatic cancer cells. The fluorescent probe localized to cell surfaces in vitro and specifically co-localized with green fluorescent protein-labeled tumors in an orthotopic pancreatic xenograft model in vivo. Serial imaging at specific time points showed peak signal intensity of the orthotopic pancreatic tumor at 48 h; this time point corresponded with a maximal tumor-to-background ratio (TBR) of 16.6 at 48 h.

DISCUSSION

hM5A-IR800 was successfully able to specifically label orthotopic pancreatic tumors in situ. The longer wavelength allowed deeper tissue penetration, particularly in tumor areas covered by normal pancreatic parenchyma. The probe had expected kinetics for an antibody-fluorophore conjugate, with the peak signal intensity reached at 48 h. A clear tumor signal was observed with a TBR > 5 at all time points, with high contrast (TBR of 16.6) at 48 h.

CONCLUSION

hM5A-IR800 demonstrated excellent tumor localization and a very bright signal. It is a promising agent for future clinical fluorescence-guided surgery applications.

Potential Sources of Inter-Subject Variability in Monoclonal Antibody Pharmacokinetics

Understanding inter-subject variability in drug pharmacokinetics and pharmacodynamics is important to ensure that all patients attain suitable drug exposure to achieve efficacy and avoid toxicity. Inter-subject variability in the pharmacokinetics of therapeutic monoclonal antibodies (mAbs) is generally moderate to high; however, the factors responsible for the high inter-subject variability have not been comprehensively reviewed. In this review, the extent of inter-subject variability for mAb pharmacokinetics is presented and potential factors contributing to this variability are explored and summarised. Disease status, age, sex, ethnicity, body size, genetic polymorphisms, concomitant medication, co-morbidities, immune status and multiple other patient-specific details have been considered. The inter-subject variability for mAb pharmacokinetics most likely depends on the complex interplay of multiple factors. However, studies aimed at investigating the reasons for the inter-subject variability are sparse. Population pharmacokinetic models and physiologically based pharmacokinetic models are useful tools to identify important covariates, aiding in the understanding of factors contributing to inter-subject variability. Further understanding of inter-subject variability in pharmacokinetics should aid in development of dosing regimens that are more appropriate.

Pharmacokinetic Considerations for Antibody-Drug Conjugates against Cancer

Antibody-drug conjugates (ADCs) are ushering in the next era of targeted therapy against cancer. An ADC for cancer therapy consists of a potent cytotoxic payload that is attached to a tumour-targeted antibody by a chemical linker, usually with an average drug-to-antibody ratio (DAR) of 3.5-4. The theory is to deliver potent cytotoxic payloads directly to tumour cells while sparing healthy cells. However, practical application has proven to be more difficult. At present there are only two ADCs approved for clinical use. Nevertheless, in the last decade there has been an explosion of options for ADC engineering to optimize target selection, Fc receptor interactions, linker, payload and more. Evaluation of these strategies requires an understanding of the mechanistic underpinnings of ADC pharmacokinetics. Development of ADCs for use in cancer further requires an understanding of tumour properties and kinetics within the tumour environment, and how the presence of cancer as a disease will impact distribution and elimination. Key pharmacokinetic considerations for the successful design and clinical application of ADCs in oncology are explored in this review, with a focus on the mechanistic determinants of distribution and elimination.

Therapeutic protein-drug interactions: plausible mechanisms and assessment strategies

INTRODUCTION

Over the last three decades, therapeutic proteins have played an increasingly important role in pharmacotherapy. Owing to an expected significant increase in the coadministration of biotherapeutics with established pharmacotherapy regimens or even with other biotherapeutic agents, there is an increasing likelihood for the occurrence of clinically relevant drug interactions, so called therapeutic protein-drug interactions (TP-DIs). Areas covered: Our current understanding of TP-DIs and recent collaborations among industry, academia and regulatory agencies are reviewed in this article. Although most of the observed TP-DIs are mediated by disease states, immune status, and/or target physiology, TP-DI assessments are still done empirically. Plausible mechanisms of major TP-DIs involving therapeutic proteins (primarily monoclonal antibodies), either as victims or as perpetrators, are proposed, with mechanism-based strategies and assessment approaches to better evaluate their propensity are recommended. Expert opinion: Our current understanding of the mechanisms of TP-DIs is in its infancy. Much of the basic research needs to be conducted to verify existing TP-DI hypotheses or help predict and manage potential ones, whose efforts are not considered trivial and may be better achieved through close collaborations among scientists from academia, industry, and regulatory agencies.

Sorafenib Decreases Tumor Exposure to an Anti-carcinoembryonic Antigen Monoclonal Antibody in a Mouse Model of Colorectal Cancer

In this investigation, we test the hypothesis that treatment with sorafenib, an anti-angiogenic agent, decreases tumor vascularization and, consequently, hinders the delivery of monoclonal antibodies (mAb) to xenograft tumors. Severe combined immunodeficiency mice bearing carcinoembryonic antigen (CEA) expressing tumor xenografts were divided into control and sorafenib-treated groups. Sorafenib was administered to the latter group at 50 mg/kg IP every 48 h, starting 4 days post-tumor implantation. When tumors attained a size of 200-300 mm(3), mice were evaluated for (a) tumor microvessel density (using immunohistochemical analysis), (b) tumor macromolecular extravasation (using Evans Blue Dye (EBD)), (c) pharmacokinetics of an anti-CEA mAb, T84.66, following an intravenous dose of 10 mg/kg, and (d) intra-tumoral spatial distribution of T84.66 (using autoradiography). Sorafenib treatment resulted in a substantial reduction in tumor growth rate, a visible reduction in tumor microvessel density, and in a 46.4% decrease in EBD extravasation in tumor tissue (p < 0.0455). For control and treated mice, no significant difference was found for the area under the mAb plasma concentration-time curve (AUC(0-7d): 1.67 × 10(3) ± 1.28 × 10(2) vs. 1.76 × 10(3) ± 1.75 × 10(2) nM × day, p = 0.51). However, tumor AUC(0-7d) was reduced by 40.8% in sorafenib-treated mice relative to that observed in control mice (5.61 × 10(2) ± 4.27 × 10(1) vs. 9.48 × 10(2) ± 5.61 × 10(1) nM × day, p < 0.001). Sorafenib therapy was also found to markedly alter mAb tumor spatial distribution. The results collectively suggest that sorafenib treatment causes a significant reduction in mAb delivery to, and distribution within, solid tumors.

Pharmacokinetic and pharmacodynamic considerations for the next generation protein therapeutics

Increasingly sophisticated protein engineering efforts have been undertaken lately to generate protein therapeutics with desired properties. This has resulted in the discovery of the next generation of protein therapeutics, which include: engineered antibodies, immunoconjugates, bi/multi-specific proteins, antibody mimetic novel scaffolds, and engineered ligands/receptors. These novel protein therapeutics possess unique physicochemical properties and act via a unique mechanism-of-action, which collectively makes their pharmacokinetics (PK) and pharmacodynamics (PD) different than other established biological molecules. Consequently, in order to support the discovery and development of these next generation molecules, it becomes important to understand the determinants controlling their PK/PD. This review discusses the determinants that a PK/PD scientist should consider during the design and development of next generation protein therapeutics. In addition, the role of systems PK/PD models in enabling rational development of the next generation protein therapeutics is emphasized.

Dynamic contrast-enhanced micro-computed tomography correlates with 3-dimensional fluorescence ultramicroscopy in antiangiogenic therapy of breast cancer xenografts

OBJECTIVES

Dynamic contrast-enhanced (DCE) micro-computed tomography (micro-CT) has emerged as a valuable imaging tool to noninvasively obtain quantitative physiological biomarkers of drug effect in preclinical studies of antiangiogenic compounds. In this study, we explored the ability of DCE micro-CT to assess the antiangiogenic treatment response in breast cancer xenografts and correlated the results to the structural vessel response obtained from 3-dimensional (3D) fluorescence ultramicroscopy (UM).

MATERIAL AND METHODS

Two groups of tumor-bearing mice (KPL-4) underwent DCE micro-CT imaging using a fast preclinical dual-source micro-CT system (TomoScope Synergy Twin, CT Imaging GmbH, Erlangen, Germany). Mice were treated with either a monoclonal antibody against the vascular endothelial growth factor or an unspecific control antibody. Changes in vascular physiology were assessed measuring the mean value of the relative blood volume (rBV) and the permeability-surface area product (PS) in different tumor regions of interest (tumor center, tumor periphery, and total tumor tissue). Parametric maps of rBV were calculated of the tumor volume to assess the intratumoral vascular heterogeneity. Isotropic 3D UM vessel scans were performed from excised tumor tissue, and automated 3D segmentation algorithms were used to determine the microvessel density (MVD), relative vessel volume, and vessel diameters. In addition, the accumulation of coinjected fluorescence-labeled trastuzumab was quantified in the UM tissue scans to obtain an indirect measure of vessel permeability. Results of the DCE micro-CT were compared with corresponding results obtained by ex vivo UM. For validation, DCE micro-CT and UM parameters were compared with conventional histology and tumor volume.

RESULTS

Examination of the parametric rBV maps revealed significantly different patterns of intratumoral blood supply between treated and control tumors. Whereas control tumors showed a characteristic vascular rim pattern with considerably elevated rBV values in the tumor periphery, treated tumors showed a widely homogeneous blood supply. Compared with UM, the physiological rBV maps showed excellent agreement with the spatial morphology of the intratumoral vascular architecture. Regional assessment of mean physiological values exhibited a significant decrease in rBV (P < 0.01) and PS (P < 0.05) in the tumor periphery after anti-vascular endothelial growth factor treatment. Structural validation with UM showed a significant reduction in reduction of relative vessel volume (rVV) (P < 0.01) and MVD (P < 0.01) in the corresponding tumor region. The reduction in rBV correlated well with the rVV (R = 0.73 for single values and R = 0.95 for mean values). Spatial maps of antibody penetration showed a significantly reduced antibody accumulation (P < 0.01) in the tumor tissue after treatment and agreed well with the physiological change of PS. Examination of vessel diameters revealed a size-dependent antiangiogenic treatment effect, which showed a significant reduction in MVD (P < 0.001) for vessels with diameters smaller than 25 μm. No treatment effect was observed by tumor volume.

CONCLUSIONS

Noninvasive DCE micro-CT provides valuable physiological information of antiangiogenic drug effect in the intact animal and correlates with ex vivo structural analysis of 3D UM. The combined use of DCE micro-CT with UM constitutes a complementary imaging toolset that can help to enhance our understanding of antiangiogenic drug mechanisms of action in preclinical drug research.

Therapeutic protein drug-drug interactions: navigating the knowledge gaps-highlights from the 2012 AAPS NBC Roundtable and IQ Consortium/FDA workshop

The investigation of therapeutic protein drug-drug interactions has proven to be challenging. In May 2012, a roundtable was held at the American Association of Pharmaceutical Scientists National Biotechnology Conference to discuss the challenges of preclinical assessment and in vitro to in vivo extrapolation of these interactions. Several weeks later, a 2-day workshop co-sponsored by the U.S. Food and Drug Administration and the International Consortium for Innovation and Quality in Pharmaceutical Development was held to facilitate better understanding of the current science, investigative approaches and knowledge gaps in this field. Both meetings focused primarily on drug interactions involving therapeutic proteins that are pro-inflammatory cytokines or cytokine modulators. In this meeting synopsis, we provide highlights from both meetings and summarize observations and recommendations that were developed to reflect the current state of the art thinking, including a four-step risk assessment that could be used to determine the need (or not) for a dedicated clinical pharmacokinetic interaction study.

Antibody biodistribution coefficients: inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human

Tissue vs. plasma concentration profiles have been generated from a physiologically-based pharmacokinetic model of monoclonal antibody (mAb). Based on the profiles, we hypothesized that a linear relationship between the plasma and tissue concentrations of non-binding mAbs could exist; and that the relationship may be generally constant irrespective of the absolute mAb concentration, time, and animal species being analyzed. The hypothesis was verified for various tissues in mice, rat, monkey, and human using mAb or antibody-drug conjugate tissue distribution data collected from diverse literature. The relationship between the plasma and various tissue concentrations was mathematically characterized using the antibody biodistribution coefficient (ABC). Estimated ABC values suggest that typically the concentration of mAb in lung is 14.9%, heart 10.2%, kidney 13.7%, muscle 3.97%, skin 15.7%, small intestine 5.22%, large intestine 5.03%, spleen 12.8%, liver 12.1%, bone 7.27%, stomach 4.98%, lymph node 8.46%, adipose 4.78%, brain 0.351%, pancreas 6.4%, testes 5.88%, thyroid 67.5% and thymus is 6.62% of the plasma concentration. The validity of using the ABC to predict mAb concentrations in different tissues of mouse, rat, monkey, and human species was evaluated by generating validation data sets, which demonstrated that predicted concentrations were within 2-fold of the observed concentrations. The use of ABC to infer tissue concentrations of mAbs and related molecules provides a valuable tool for investigating preclinical or clinical disposition of these molecules. It can also help eliminate or optimize biodistribution studies, and interpret efficacy or toxicity of the drug in a particular tissue.

Application of PBPK modeling to predict monoclonal antibody disposition in plasma and tissues in mouse models of human colorectal cancer

This investigation evaluated the utility of a physiologically based pharmacokinetic (PBPK) model, which incorporates model parameters representing key determinants of monoclonal antibody (mAb) target-mediated disposition, to predict, a priori, mAb disposition in plasma and in tissues, including tumors that express target antigens. Monte Carlo simulation techniques were employed to predict the disposition of two mAbs, 8C2 (as a non-binding control mouse IgG1 mAb) and T84.66 (a high-affinity murine IgG1 anti-carcinoembryonic antigen mAb), in mice bearing no tumors, or bearing colorectal HT29 or LS174T xenografts. Model parameters were obtained or derived from the literature. (125)I-T84.66 and (125)I-8C2 were administered to groups of SCID mice, and plasma and tissue concentrations were determined via gamma counting. The PBPK model well-predicted the experimental data. Comparisons of the population predicted versus observed areas under the plasma concentration versus time curve (AUC) for T84.66 were 95.4 ± 67.8 versus 84.0 ± 3.0, 1,859 ± 682 versus 2,370 ± 154, and 5,930 ± 1,375 versus 5,960 ± 317 (nM × day) at 1, 10, and 25 mg/kg in LS174T xenograft-bearing SCID mice; and 215 ± 72 versus 233 ± 30, 3,070 ± 346 versus 3,120 ± 180, and 7,884 ± 714 versus 7,440 ± 626 in HT29 xenograft-bearing mice. Model predicted versus observed 8C2 plasma AUCs were 312.4 ± 30 versus 182 ± 7.6 and 7,619 ± 738 versus 7,840 ± 24.3 (nM × day) at 1 and 25 mg/kg. High correlations were observed between the predicted median plasma concentrations and observed median plasma concentrations (r (2) = 0.927, for all combinations of treatment, dose, and tumor model), highlighting the utility of the PBPK model for the a priori prediction of in vivo data.