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Purpose: CEA TCB (RG7802, RO6958688) is a novel T-cell bispecific antibody, engaging CD3ϵ upon binding to carcinoembryonic antigen (CEA) on tumor cells. Containing an engineered Fc region, conferring an extended blood half-life while preventing side effects due to activation of innate effector cells, CEA TCB potently induces tumor lysis in mouse tumors. Here we aimed to characterize the pharmacokinetic profile, the biodistribution, and the mode of action of CEA TCB by combining in vitro and in vivo fluorescence imaging readouts.Experimental Design: CEA-expressing tumor cells (LS174T) and human peripheral blood mononuclear cells (PBMC) were cocultured in vitro or cografted into immunocompromised mice. Fluorescence reflectance imaging and intravital 2-photon (2P) microscopy were employed to analyze in vivo tumor targeting while in vitro confocal and intravital time-lapse imaging were used to assess the mode of action of CEA TCB.Results: Fluorescence reflectance imaging revealed increased ratios of extravascular to vascular fluorescence signals in tumors after treatment with CEA TCB compared with control antibody, suggesting specific targeting, which was confirmed by intravital microscopy. Confocal and intravital 2P microscopy showed CEA TCB to accelerate T-cell–dependent tumor cell lysis by inducing a local increase of effector to tumor cell ratios and stable crosslinking of multiple T cells to individual tumor cells.Conclusions: Using optical imaging, we demonstrate specific tumor targeting and characterize the mode of CEA TCB–mediated target cell lysis in a mouse tumor model, which supports further clinical evaluation of CEA TCB. Clin Cancer Res; 22(17); 4417–27. ©2016 AACR.See related commentary by Teijeira et al., p. 4277

In vitro live cell confocal imaging of LS174T RFP cells co-cultured with CFSE-labeled T-cells (E:T = 3:1) in the presence of CEA or a control TCB, respectively.

Supplementary Figure S1. CEA TCB leads stimulates the expression of CD25, a T-cell activation marker, on both T-helper (CD4+) and cytotoxic T-cells (CD8+) after incubation with LS174T tumor cells. Supplementary Figure S2. CEA TCB induces efficient MKN45 tumor cell lysis and T-cell activation in the presence of these tumor cells. Supplementary Figure S3. Both CD4+ and CD8+ T-cells contribute to CEA-TCB mediated killing. Supplementary Figure S4. Ex vivo analysis of in vivo tumor targeting. Supplementary Figure S5. Analysis of T-cell migratory persistence index.

Supplementary Figure S1: Left: CEA expression by immuno-histochemistry in the LS174T tumor mouse model: homogeneous cytoplasmic antigen distribution. Right: CEA expression in one of the treated patients (colorectal cancer): heterogeneous cytoplasmic antigen distribution with polarized apical accumulation.

2P time-lapse acquisition of LS174T / human PBMC cografts on day 4 after implantation (baseline), 24 h after control and 24 h after CEA TCB treatment. LS174T RFP tumor cells (red), CFSE labeled T-cells (green). Scale bar indicates 50 μm.

Purpose: Optimal dosing is critical for immunocytokine-based cancer immunotherapy to maximize efficacy and minimize toxicity. Cergutuzumab amunaleukin (CEA-IL2v) is a novel CEA-targeted immunocytokine. We set out to develop a mathematical model to predict intratumoral CEA-IL2v concentrations following various systemic dosing intensities.Experimental Design: Sequential measurements of CEA-IL2v plasma concentrations in 74 patients with solid tumors were applied in a series of differential equations to devise a model that also incorporates the peripheral concentrations of IL2 receptor–positive cell populations (i.e., CD8+, CD4+, NK, and B cells), which affect tumor bioavailability of CEA-IL2v. Imaging data from a subset of 14 patients were subsequently utilized to additionally predict antibody uptake in tumor tissues.Results: We created a pharmacokinetic/pharmacodynamic mathematical model that incorporates the expansion of IL2R-positive target cells at multiple dose levels and different schedules of CEA-IL2v. Model-based prediction of drug levels correlated with the concentration of IL2R-positive cells in the peripheral blood of patients. The pharmacokinetic model was further refined and extended by adding a model of antibody uptake, which is based on drug dose and the biological properties of the tumor. In silico predictions of our model correlated with imaging data and demonstrated that a dose-dense schedule comprising escalating doses and shortened intervals of drug administration can improve intratumoral drug uptake and overcome consumption of CEA-IL2v by the expanding population of IL2R-positive cells.Conclusions: The model presented here allows simulation of individualized treatment plans for optimal dosing and scheduling of immunocytokines for anticancer immunotherapy. Clin Cancer Res; 24(14); 3325–33. ©2018 AACR.See related commentary by Ruiz-Cerdá et al., p. 3236

Ex vivo analysis of the CEA TCB (magenta) mediated cross-linking of CFSE labeled T-cells (green) to tumor cells. 3D reconstructions of confocal z-stacks acquired on tumor sections obtained from huPBMC (CFSE labeled T-cells)/LS174T RFP co-grafts, 24 h after intravenous A647 labeled CEA TCB injections are shown. Bar, 10 μm. Cell nuclei (DAPI) are shown in blue.

Supplemental Table S2: Model parameter estimates. For model equations, refer to supplemental material.

Immunogenicity against therapeutic proteins frequently causes attrition owing to its potential impact on pharmacokinetics, pharmacodynamics, efficacy, and safety. Predicting immunogenicity is complex because of its multifactorial drivers, including compound properties, subject characteristics, and treatment parameters. To integrate these, the Immunogenicity Simulator was developed using published, predominantly late-stage trial data from 15 therapeutic proteins. This single-blinded evaluation with subject-level data from 10 further monoclonals assesses the Immunogenicity Simulator's credibility for application during the drug development process.

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.

The pharmacokinetics (PK) of the anti-CD20 monoclonal antibody obinutuzumab was assessed after single intravenous dosing to cynomolgus monkeys. In addition, the pharmacokinetic-pharmacodynamic (PKPD) relationship for B-cell depletion was characterized. The PKPD model was used to estimate the B-cell repopulation during the recovery phase of chronic toxicology studies, thereby supporting the study design, in particular planning the recovery phase duration. Marked immunogenicity against obinutuzumab was observed approximately 10 days after single dose, leading to an up to ∼30-fold increase in obinutuzumab clearance in the affected monkeys. Despite this accelerated clearance, the PK could be characterized, either by disregarding the clearance in noncompartmental PK analysis or by capturing it explicitly as an additional time-dependent clearance process in compartmental modeling. This latter step was crucial to model the PKPD of B-cells as an indirect response to obinutuzumab exposure, showing that-without immune response-the limiting factor is obinutuzumab elimination with concentrations below 0.02 μg/mL required for initiation of B-cell recovery. Overall, the results demonstrate that despite a marked anti-drug antibody response in the nonclinical animal species, the PK and PKPD of obinutuzumab could be characterized successfully by appropriately addressing the immune-modulated clearance pathway in data analysis and modeling.

Purpose: Optimal dosing is critical for immunocytokine-based cancer immunotherapy to maximize efficacy and minimize toxicity. Cergutuzumab amunaleukin (CEA-IL2v) is a novel CEA-targeted immunocytokine. We set out to develop a mathematical model to predict intratumoral CEA-IL2v concentrations following various systemic dosing intensities. Experimental Design: Sequential measurements of CEA-IL2v plasma concentrations in 74 patients with solid tumors were applied in a series of differential equations to devise a model that also incorporates the peripheral concentrations of IL2 receptor–positive cell populations (i.e., CD8+, CD4+, NK, and B cells), which affect tumor bioavailability of CEA-IL2v. Imaging data from a subset of 14 patients were subsequently utilized to additionally predict antibody uptake in tumor tissues. Results: We created a pharmacokinetic/pharmacodynamic mathematical model that incorporates the expansion of IL2R-positive target cells at multiple dose levels and different schedules of CEA-IL2v. Model-based prediction of drug levels correlated with the concentration of IL2R-positive cells in the peripheral blood of patients. The pharmacokinetic model was further refined and extended by adding a model of antibody uptake, which is based on drug dose and the biological properties of the tumor. In silico predictions of our model correlated with imaging data and demonstrated that a dose-dense schedule comprising escalating doses and shortened intervals of drug administration can improve intratumoral drug uptake and overcome consumption of CEA-IL2v by the expanding population of IL2R-positive cells. Conclusions: The model presented here allows simulation of individualized treatment plans for optimal dosing and scheduling of immunocytokines for anticancer immunotherapy. Clin Cancer Res; 24(14); 3325–33. ©2018 AACR. See related commentary by Ruiz-Cerdá et al., p. 3236

Monoclonal antibodies are an important therapeutic entity, and knowledge of antibody pharmacokinetics has steadily increased over the years. Despite this effort, little is known about the extent of IgG antibody degradation in different tissues of the body. While studies have been published identifying sites of degradation with the use of residualizing and non-residualizing radiolabels, quantitative tissue clearances have not yet been derived. Here, we show that in physiologically-based pharmacokinetic (PBPK) models we can combine mouse data of Indium-111 and Iodine-125 labeled antibodies with prior physiologic knowledge to determine tissue-specific intrinsic clearances. Unspecific total tissue clearance (mL/day) in the mouse was estimated to be: liver = 4.75; brain = 0.02; gut = 0.40; heart = 0.07; kidney = 0.97; lung = 0.20; muscle = 3.02; skin = 3.89; spleen = 0.45; rest of body = 2.16. The highest catabolic activity (per g tissue) was in spleen for an FcRn wild-type antibody, but shifts to the liver for an antibody with reduced FcRn affinity. In the model developed, this shift can be explained by the liver having a greater FcRn-mediated protection capacity than the spleen. The quantification of tissue intrinsic clearances and FcRn salvage capacity increases our understanding of quantitative processes that drive the therapeutic responses of antibodies. This knowledge is critical, for instance to estimate the non-specific cellular uptake and degradation of antibodies used for targeted delivery of payloads.

Minipigs have been proposed as animal model to study the subcutaneous (SC) absorption of monoclonal antibodies (mAb), because they are more translatable to humans than other species. However, the minipig SC tissue structure differs markedly depending on its location. This study explored different SC administration sites for mAb SC administration, to explore which site translates best to humans. The study assessed the SC absorption of tocilizumab (Actemra®) following administration at several injection sites: Inguinal area, flank, caudal to the ear, and interscapular area, in comparison with an IV group. After SC administration, tocilizumab absorption was most rapid from the inguinal administration site, and slowest after administration behind the ear, with absorption from the other sites in between. Tocilizumab bioavailability was 98.6, 88.3, 74.1, and 86.3% after administration in inguinal area, flank, behind the ear, and interscapular area, as determined by non-compartmental analysis. Fitting of a single first-order absorption rate constant by compartmental analysis was dissatisfactory. A combined fitting of all data was done assuming two different kinds of SC depots, one undergoing fast absorption, the other undergoing a slower absorption. The split between these absorption depots differed across administration sites, with absorption from "fast depot" in inguinal area > flank > interscapular area > behind the ear. Comparisons with clinical data show that tocilizumab PK after SC administration behind the ear translates best to humans, considering both bioavailability and rate of absorption. Whether this translation from minipigs to humans is prototypic for other mAb remains to be confirmed.

Purpose: CEA TCB (RG7802, RO6958688) is a novel T-cell bispecific antibody, engaging CD3ϵ upon binding to carcinoembryonic antigen (CEA) on tumor cells. Containing an engineered Fc region, conferring an extended blood half-life while preventing side effects due to activation of innate effector cells, CEA TCB potently induces tumor lysis in mouse tumors. Here we aimed to characterize the pharmacokinetic profile, the biodistribution, and the mode of action of CEA TCB by combining in vitro and in vivo fluorescence imaging readouts. Experimental Design: CEA-expressing tumor cells (LS174T) and human peripheral blood mononuclear cells (PBMC) were cocultured in vitro or cografted into immunocompromised mice. Fluorescence reflectance imaging and intravital 2-photon (2P) microscopy were employed to analyze in vivo tumor targeting while in vitro confocal and intravital time-lapse imaging were used to assess the mode of action of CEA TCB. Results: Fluorescence reflectance imaging revealed increased ratios of extravascular to vascular fluorescence signals in tumors after treatment with CEA TCB compared with control antibody, suggesting specific targeting, which was confirmed by intravital microscopy. Confocal and intravital 2P microscopy showed CEA TCB to accelerate T-cell–dependent tumor cell lysis by inducing a local increase of effector to tumor cell ratios and stable crosslinking of multiple T cells to individual tumor cells. Conclusions: Using optical imaging, we demonstrate specific tumor targeting and characterize the mode of CEA TCB–mediated target cell lysis in a mouse tumor model, which supports further clinical evaluation of CEA TCB. Clin Cancer Res; 22(17); 4417–27. ©2016 AACR. See related commentary by Teijeira et al., p. 4277

The neonatal Fc receptor (FcRn) has been demonstrated to contribute to a high bioavailability of monoclonal antibodies (mAbs). In this study, we explored the cellular sites of FcRn-mediated protection after subcutaneous (SC) and intravenous (IV) administration. SC absorption and IV disposition kinetics of a mAb were studied in hFcRn transgenic (Tg) bone marrow chimeric mice in which hFcRn was restricted to radioresistant cells or hematopoietic cells. SC bioavailabilities close to 90% were observed in hFcRn Tg mice and chimeric mice with hFcRn expression in hematopoietic cells, whereas SC bioavailabilities were markedly lower when FcRn was missing in hematopoietic cells. Our study demonstrates: 1) FcRn in radiosensitive hematopoietic cells is required for high SC bioavailability, indicating first-pass catabolism after SC administration by hematopoietic cells; 2) FcRn-mediated transcytosis or recycling by radioresistent cells is not required for high SC bioavailability; and 3) after IV administration hematopoietic and radioresistent cells contribute about equally to clearance of the mAb. A pharmacokinetic model was devised to describe a mixed elimination via radioresistent and hematopoietic cells from vascular and extravascular compartments, respectively. Overall, the study indicates a relevant role of hematopoietic cells for first-pass clearance of mAbs after SC administration and confirms their role in the overall clearance of mAbs.

Drug absorption is a complex process involving dissolution and precipitation, along with other kinetic processes. The purpose of this work was to (1) establish an in vitro methodology to study dissolution and precipitation in early stages of drug development where low compound consumption and high throughput are necessary, (2) develop a mathematical model for a mechanistic explanation of generated in vitro dissolution and precipitation data, and (3) extrapolate in vitro data to in vivo situations using physiologically based models to predict oral drug absorption. Small-scale pH-shift studies were performed in biorelevant media to monitor the precipitation of a set of poorly soluble weak bases. After developing a dissolution-precipitation model from this data, it was integrated into a simplified, physiologically based absorption model to predict clinical pharmacokinetic profiles. The model helped explain the consequences of supersaturation behavior of compounds. The predicted human pharmacokinetic profiles closely aligned with the observed clinical data. In summary, we describe a novel approach combining experimental dissolution/precipitation methodology with a mechanistic model for the prediction of human drug absorption kinetics. The approach unifies the dissolution and precipitation theories and enables accurate predictions of in vivo oral absorption by means of physiologically based modeling.

CD81 is an essential receptor for hepatitis C virus (HCV). K21 is a novel high affinity anti-CD81 antibody with potent broad spectrum anti-HCV activity in vitro. The pharmacokinetics (PK), pharmacodynamics and liver distribution of K21 were characterized in cynomolgus monkeys after intravenous (i.v.) administration of K21. Characteristic target-mediated drug disposition (TMDD) was shown based on the PK profile of K21 and a semi-mechanistic TMDD model was used to analyze the data. From the TMDD model, the estimated size of the total target pool at baseline (V(c) • R(base)) is 16 nmol/kg and the estimated apparent Michaelis-Menten constant (KM) is 4.01 nM. A simulation using estimated TMDD parameters indicated that the number of free receptors remains below 1% for at least 3 h after an i.v. bolus of 7 mg/kg. Experimentally, the availability of free CD81 on peripheral lymphocytes was measured by immunostaining with anti-CD81 antibody JS81. After K21 administration, a dose- and time-dependent reduction in free CD81 on peripheral lymphocytes was observed. Fewer than 3% of B cells could bind JS81 3 h after a 7 mg/kg dose. High concentrations of K21 were found in liver homogenates, and the liver/serum ratio of K21 increased time-dependently and reached ~160 at 168 h post-administration. The presence of K21 bound to hepatocytes was confirmed by immunohistochemistry. The fast serum clearance of K21 and accumulation in the liver are consistent with TMDD. The TMDD-driven liver accumulation of the anti-CD81 antibody K21 supports the further investigation of K21 as a therapeutic inhibitor of HCV entry.

Interleukin-6 (IL-6) is involved in the pathogenesis of multiple disorders, including juvenile autoimmune diseases. IL-6 participates in a broad spectrum of physiological events, and the IL-6 receptor (IL-6R) is widely distributed across multiple organs. The interrelationship of development phases in juveniles together with organs involved in IL-6 signaling called for evaluations of anti-IL-6R antibody induced effects in a juvenile mouse model to assess the safety of such an approach in human juvenile arthritis. Here we show that naive mice in which IL-6 signals have been transiently blocked during the juvenile period develop normally. The fatal immunogenic reactions recorded earlier by repeated administration of the chosen rat anti-mouse IL-6R antibody, MR16-1, to mice were avoided successfully by application of a high loading dose followed by lower maintenance doses, with the support of modeling data. The high loading-dose regimen enabled us to conduct assessments without any major interference due to immunogenicity. Transient and complete inhibition of IL-6 signals from postnatal days 22 to 79 in mice exhibited no biologically important changes in sexual maturation or development of immune and skeletal systems. Although tendencies toward reductions of peripheral blood T-cell counts were observed, normal levels of antigen-specific IgG/IgM antibody productions indicating sufficient immunological functions were confirmed. Our results demonstrate that blockage of IL-6R by the neutralizing antibody does not affect juvenile development. This may be in part due to the generation or existence of compensatory pathways in the whole body system.

Subcutaneous (SC) delivery is a common route of administration for therapeutic monoclonal antibodies (mAbs) with pharmacokinetic (PK)/pharmacodynamic (PD) properties requiring long-term or frequent drug administration. An ideal in vivo preclinical model for predicting human PK following SC administration may be one in which the skin and overall physiological characteristics are similar to that of humans. In this study, the PK properties of a series of therapeutic mAbs following intravenous (IV) and SC administration in Göttingen minipigs were compared with data obtained previously from humans. The present studies demonstrated: (1) minipig is predictive of human linear clearance; (2) the SC bioavailabilities in minipigs are weakly correlated with those in human; (3) minipig mAb SC absorption rates are generally higher than those in human and (4) the SC bioavailability appears to correlate with systemic clearance in minipigs. Given the important role of the neonatal Fc-receptor (FcRn) in the PK of mAbs, the in vitro binding affinities of these IgGs against porcine, human and cynomolgus monkey FcRn were tested. The result showed comparable FcRn binding affinities across species. Further, mAbs with higher isoelectric point tended to have faster systemic clearance and lower SC bioavailability in both minipig and human. Taken together, these data lend increased support for the use of the minipig as an alternative predictive model for human IV and SC PK of mAbs.

Target-mediated drug disposition (TMDD) is frequently reported for therapeutic monoclonal antibodies and is linked to the high affinity and high specificity of antibody molecules for their target. Understanding TMDD of a monoclonal antibody should go beyond the empirical description of its non-linear PK since valuable insights on the antibody-target interaction itself can be gained. This makes its mechanistic understanding precious for the drug development process, in particular for the optimization of new antibody molecules, for the design and interpretation of pharmacokinetic studies, and possibly even for the evaluation of efficacy and dose selection of drug candidates. Using the observation that the molecular (microscopic) processes are usually much more rapid than the pharmacokinetic (macroscopic) processes, a series of quasi-steady-state conditions on the microscopic level is proposed to bridge the gap between simple empirical and complex mechanistic descriptions of TMDD. These considerations show the impact of parameters such as target turnover, target expression, and target accessibility on the pharmacokinetics and pharmacodynamics of monoclonal antibodies.

The use of in vitro data for quantitative predictions of transporter-mediated elimination in vivo requires an accurate estimation of the transporter Michaelis-Menten parameters, V(max) and K(m), as a first step. Therefore, the experimental conditions of in vitro studies used to assess hepatic uptake transport were optimized regarding active transport processes, nonspecific binding, and passive diffusion (P(dif)). A mechanistic model was developed to analyze and accurately describe these active and passive processes. This two-compartmental model was parameterized to account for nonspecific binding, bidirectional passive diffusion, and active uptake processes based on the physiology of the cells. The model was used to estimate kinetic parameters of in vitro transport data from organic anion-transporting peptide model substrates (e.g., cholecystokinin octapeptide deltorphin II, fexofenadine, and pitavastatin). Data analysis by this mechanistic model significantly improved the accuracy and precision in all derived parameters [mean coefficient of variations (CVs) for V(max) and K(m) were 19 and 23%, respectively] compared with the conventional kinetic method of transport data analysis (mean CVs were 58 and 115%, respectively, using this method). Furthermore, permeability was found to be highly temperature-dependent in Chinese hamster ovary (CHO) control cells and artificial membranes (parallel artificial membrane permeability assay). Whereas for some compounds (taurocholate, estrone-3-sulfate, and propranolol) the effect was moderate (1.5-6-fold higher permeability at 37 degrees C compared with that at 4 degrees C), for fexofenadine a 16-fold higher passive permeability was seen at 37 degrees C. Therefore, P(dif) was better predicted if it was evaluated under the same experimental conditions as V(max) and K(m), i.e., in a single incubation of CHO overexpressed cells or rat hepatocytes at 37 degrees C, instead of a parallel control evaluation at 4 degrees C.

The consideration of drug metabolism and pharmacokinetics (DMPK) and physicochemical properties as part of the drug discovery and development process has substantially improved the quality of drug candidates with respect to pharmacokinetic properties. The main reason for attrition in development is now related to safety and efficacy, and the current challenge is to establish a relationship between pharmacokinetic and pharmacological/safety endpoints starting from early discovery stages. Mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling for both efficacy and safety assessment is being successfully employed throughout all discovery and drug development stages for data interpretation, study design, and enhanced decision making. Mechanismbased PK/PD models range from simple PK/PD models to physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, as well as more complex systems biology. Because the models are developed to describe the underlying biology and pathways, they provide the opportunity to separate systemspecific parameters from compound-specific parameters [1,2]. They also enable extrapolation from in vitro to in vivo settings, from animals to humans, from healthy volunteers to a disease population, and from one compound to other similar compound. In addition, unlike empirical models, the model parameters in a mechanism-based PK/PD model can be experimentally measured and in some cases estimated in silico. The specific set of questions to be addressed using PK/PD modeling depends on the stage of drug development. For late-stage preclinical and clinical development, PK/PD modeling is used to impact selection of dose regimens and more generally to support optimal study design for preclinical (e.g., toxicology) and clinical studies. For the discovery and early development stages, the understanding of the PK/PD relationship helps to better define the target profile and support the selection of lead compounds to advance into clinical studies based on the separation between efficacy and safety, the estimation of 53

Interleukin-6 (IL-6) is involved in the pathogenesis of multiple disorders, including juvenile autoimmune diseases. IL-6 participates in a broad spectrum of physiological events, and the IL-6 receptor (IL-6R) is widely distributed across multiple organs. The interrelationship of development phases in juveniles together with organs involved in IL-6 signaling called for evaluations of anti-IL-6R antibody induced effects in a juvenile mouse model to assess the safety of such an approach in human juvenile arthritis. Here we show that naive mice in which IL-6 signals have been transiently blocked during the juvenile period develop normally. The fatal immunogenic reactions recorded earlier by repeated administration of the chosen rat anti-mouse IL-6R antibody, MR16-1, to mice were avoided successfully by application of a high loading dose followed by lower maintenance doses, with the support of modeling data. The high loading-dose regimen enabled us to conduct assessments without any major interference due to immunogenicity. Transient and complete inhibition of IL-6 signals from postnatal days 22 to 79 in mice exhibited no biologically important changes in sexual maturation or development of immune and skeletal systems. Although tendencies toward reductions of peripheral blood T-cell counts were observed, normal levels of antigen-specific IgG/IgM antibody productions indicating sufficient immunological functions were confirmed. Our results demonstrate that blockage of IL-6R by the neutralizing antibody does not affect juvenile development. This may be in part due to the generation or existence of compensatory pathways in the whole body system.

Inhibition of the enzyme(s) that produce the Amyloid beta (Aβ) peptide, namely BACE and γ-secretase, is considered an attractive target for Alzheimer’s disease therapy. However, the optimal pharmacokinetic–pharmacodynamic modelling method to describe the changes in Aβ levels after drug treatment is unclear. In this study, turnover models were employed to describe Aβ levels following treatment with the γ-secretase inhibitor RO5036450, in the wild type rat. Initially, Aβ level changes in the brain, cerebral spinal fluid (CSF) and plasma were modeled as separate biological compartments, which allowed the estimation of a compound IC 50 and Aβ turnover. While the data were well described, the model did not take into consideration that the CSF pool of Aβ most likely originates from the brain via the CSF drainage pathway. Therefore, a separate model was carried out, with the assumption that CSF Aβ levels originated from the brain. The optimal model that described the data involved two brain Aβ 40 sub-compartments, one with a rapid turnover, from which CSF Aβ 40 is derived, and a second quasi-static pool of ~20%. Importantly, the estimated in vivo brain IC 50 was in a good range of the in vitro IC 50 (ratio, 1.4). In conclusion, the PK/PD models presented here are well suited for describing the temporal changes in Aβ levels that occur after treatment with an Aβ lowering drug, and identifying physiological parameters.

This chapter aims to illustrate the ability of physiologically based mechanistic mathematical models to predict pharmacokinetics and toxicity across species. The underlying principle is that toxicity must be interpreted in the physiological context where it is measured. Various methodologies for predicting the pharmacokinetics, QT prolongation and proarrhythmic risk are evaluated. Finally an integration of both pharmacokinetics and toxicokinetics in chemotherapy-induced neutropenia is discussed. It is believed that the methodologies presented for integrating available knowledge across experiments to predict toxicology in humans will ultimately make drug development more efficient, cost cost-effective, and socially more acceptable. Keywords: pharmacokinetics; PBPK; toxicokinetics; QT prolongation; cardiac; electrophysiology; myelosuppression; neutropenia

The volume of distribution at steady state (Vss) of therapeutic proteins is usually assessed by non-compartmental or compartmental pharmacokinetic (PK) analysis wherein errors may arise due to the elimination of therapeutic proteins from peripheral tissues that are not in rapid equilibrium with the sampling compartment (usually blood). Here we explored another potential source of error in the estimation of Vss that is linked to the heterogeneity of therapeutic proteins which may consist of components (e.g. glycosylation variants) with different elimination rates. PK simulations were performed with such hypothetical binary protein mixtures where elimination was assumed to be exclusively from the central compartment. The simulations demonstrated that binary mixtures containing a rapid-elimination component can give rise to pronounced bi-phasic concentration–time profiles. Apparent Vss observed with both non-compartmental and 2-compartmental PK analysis, increased with increasing fraction as well as with increasing elimination rate k 10 of the rapid-elimination component. Simulation results were complemented by PK analysis of an in vivo study in cynomolgus monkeys with different lots of lenercept, a tumor necrosis factor receptor-immunoglobulin G1 fusion protein, with different heterogeneities. The comparative Vss data for the three lenercept lots with different amounts of rapidly cleared components were consistent with the outcome of our simulations. Both lots with a higher fraction of rapidly cleared components had a statistically significant higher Vss as compared to the reference lot. Overall our study demonstrates that Vss of a therapeutic protein may be overestimated in proteins with differently eliminated components.

In order to support the toxicological risk assessment for the ethyl methanesulfonate (EMS) exposure of patients ingesting contaminated Viracept tablets (Muller and Singer, 2009), there was a need to correlate the effects observed in in vivo genotoxicity studies with mice to EMS exposure and to estimate human exposure to EMS at the level of contamination of Viracept tablets. The species differences in volume of distribution of EMS, a key factor for determination of its C(max), were small in the species investigated (mouse, rat, monkey), the species differences in clearance, the key factor involved in AUC assessment, were large (Lave et al., 2009). Because of this uncertainty in extrapolation of clearance across species we used a conservative approach for human exposure predictions in terms of AUC where clearance was assumed to solely reflect the chemical stability of EMS neglecting additional clearance pathways such as metabolism and exhalation. This approach was compared to the estimates obtained from allometric scaling based on rat clearance, the species leading to the lowest clearance predicted in man. We found that both approaches led to nearly identical predictions of the human AUC. Thus, we predict a human AUC of 13 microM h for patients ingesting the most contaminated Viracept tablets, corresponding to a maximal daily intake of 0.055 mg/kg of EMS. The C(max) of EMS in these patients is predicted to be 0.85 microM. In order to provide a basis for toxicological risk assessment, these maximal human AUC and C(max) values are to be compared to the AUC and C(max) values in mice at the EMS dose of 25mg/kg which was found to be the threshold dose for induction of mutagenic effects, i.e. the dose at which no mutagenic effects were observed (Gocke et al., 2009-a). We calculate AUC and C(max) in mice at the threshold dose to be 350 microM h and 315 microM, respectively. Thus we conclude that a large safety factor can be deduced, whatever the basis of comparison, as is discussed in detail by Muller et al. (2009).

The benefits of modelling and simulation at the pre-clinical stage of drug development can be realized through formal and realistic integration of data on physicochemical properties, pharmacokinetics, pharmacodynamics, formulation and safety. Such data integration and the powerful combination of physiologically based pharmacokinetic (PBPK) with pharmacokinetic-pharmacodynamic relationship (PK/PD) models provides the basis for quantitative outputs allowing comparisons across compounds and resulting in improved decision-making during the selection process. Such PBPK/PD evaluations provide crucial information on the potency and safety of drug candidates in vivo and the bridging of the PK/PD concept established during the pre-clinical phase to clinical studies. Modelling and simulation is required to address a number of key questions at the various stages of the drug-discovery and -development process. Such questions include the following. (1) What is the expected human PK profile for potential clinical candidate(s)? (2) Is this profile and its associated PD adequate for the given indication? (3) What is the optimal dosing schedule with respect to safety and efficacy? (4) Is a food effect expected? (5) How can formulation be improved and what is the potential benefit? (6) What is the expected variability and uncertainty in the predictions?

We report on a new, high-throughput assay designed to measure octanol/water partition coefficients in early drug discovery. The assay is carried out in 96-well microtiterplates and measures the diffusion of compounds between two aqueous compartments separated by a thin octanol liquid layer. Octanol/water partition coefficients are derived from the apparent permeability (P(a)) values using a calibration curve. The assay can measure partition coefficients within the range -2 to + 8; thus, a dynamic range of 10 log units can be covered in one single run. Unlike chromatographic methods, the technology is not restricted to neutral and weakly basic compounds, and, as no stationary phase is involved, the data can be strictly compared with values obtained from traditional methods such as shake-flask/HPLC or dual-phase potentiometric titration.

Nanomedicine offers promising and innovative tools to treat cancer. Recently, liposomes conjugated with an antibody were developed to target breast cancer cells while sparing healthy tissues from the toxicity of the chemotherapy. These nanoparticles are called antibody-nanoconjugates (ANCs) and are currently tested in a preclinical trial. However, the pharmacokinetics, biodistribution, and efficacy of these nanoparticles are not well known and could be improved. Mathematical modeling can help in understanding the intratumor penetration of the nanoparticles and in quantifying the treatment efficacy.Pharmacokinetic-pharmacodynamic modeling evaluates the dose-response relationship in vivo and can be used to optimize the therapy schedule. Here, we described several biological processes using ordinary differential equations: (i) the untreated tumor growth with a novel reduced Gompertz model, (ii) the nanoparticle biodistribution using a two-compartment pharmacokinetic model, and (iii) the therapeutic response with a resistance model. All the models were validated against experimental data in the statistical framework of nonlinear mixed-effects modeling, which models simultaneously the dynamic of the population and the inter-individual variability.Furthermore, we derived a spatial mathematical model with the two-scale asymptotic expansion method to describe the fluid and nanoparticle transport within the tumor tissue. This approach allowed us to evaluate the barriers that impair a homogeneous distribution of nanoparticles at the tumor site. Moreover, we propose a computational framework to predict tumor accumulation of nanoparticles using individual imaging data.; La nanomédecine offre des perspectives ambitieuses pour le traitement du cancer. Récemment, des liposomes conjugués à des anticorps spécifiques ont été développés pour cibler les cellules tumorales du cancer au sein, en réduisant la toxicité de la chimiothérapie dans les tissus sains. Ces nanoparticules, appelées ANC (pour antibody nano-conjugate), sont actuellement testées dans une phase préclinique. Cependant, la pharmacocinétique, la biodistribution et l'efficacité de ces nanoparticules ne sont pas bien caracterisées quantitativement et pourrait être ameliorées. La modélisation mathématique peut aider à mieux comprendre la dynamique de la pénétration des ANC dans la tumeur et à améliorer l'efficacité du traitement.La modélisation pharmacocinétique-pharmacodynamique permet d'évaluer la réponse du traitement extit{in vivo} en fonction de la dose injectée. Dans ce travail, nous avons décrit plusieurs phénomènes biologiques avec des équations differentielles ordinaires : (i) la croissance tumorale avec un nouveau modèle réduit de Gompertz, (ii) la biodistribution des nanoparticules avec un modèle pharmacocinétique à deux compartiments, et (iii) la réponse au traitement avec un modèle de résistance. Tous les modèles ont été calibrés dans le cadre des modèles non linéaires à effets mixtes, qui décrivent la dynamique globale de la population ainsi que la variabilité individuelle.De plus, nous avons dérivé un modèle mathématique spatial avec la technique de développement asymptotique double-échelle pour décrire le transport des fluides et des nanoparticules dans le tissu tumoral. Cette méthodologie nous permet d'évaluer les barrières microscopiques qui empêchent une distribution homogène des ANC dans la tumeur. Finalement, nous proposons un schéma computationnel pour prédire l'accumulation des nanoparticules à partir des données individuels d'imagerie.