Scale-up of a physiologically-based pharmacokinetic model to predict the disposition of monoclonal antibodies in monkeys

Translation of Monoclonal Antibodies Pharmacokinetics from Animal to Human Using Physiologically Based Modeling in Open Systems Pharmacology (OSP) Suite: A Retrospective Analysis of Bevacizumab

Interspecies translation of monoclonal antibodies (mAbs) pharmacokinetics (PK) in presence of target-mediated drug disposition (TMDD) is particularly challenging. Incorporation of TMDD in physiologically based PK (PBPK) modeling is recent and needs to be consolidated and generalized to provide better prediction of TMDD regarding inter-species translation during preclinical and clinical development steps of mAbs. The objective of this study was to develop a generic PBPK translational approach for mAbs using the open-source software (PK-Sim® and Mobi®). The translation of bevacizumab based on data in non-human primates (NHP), healthy volunteers (HV), and cancer patients was used as a case example for model demonstration purpose. A PBPK model for bevacizumab concentration-time data was developed using data from literature and the Open Systems Pharmacology (OSP) Suite version 10. PK-sim® was used to build the linear part of bevacizumab PK (mainly FcRn-mediated), whereas MoBi® was used to develop the target-mediated part. The model was first developed for NHP and used for a priori PK prediction in HV. Then, the refined model obtained in HV was used for a priori prediction in cancer patients. A priori predictions were within 2-fold prediction error (predicted/observed) for both area under the concentration-time curve (AUC) and maximum concentration (Cmax) and all the predicted concentrations were within 2-fold average fold error (AFE) and average absolute fold error (AAFE). Sensitivity analysis showed that FcRn-mediated distribution and elimination processes must be accounted for at all mAb concentration levels, whereas the lower the mAb concentration, the more significant the target-mediated elimination. This project is the first step to generalize the full PBPK translational approach in Model-Informed Drug Development (MIDD) of mAbs using OSP Suite.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Complex PK-PD of an engineered IL-15/IL-15Rα-Fc fusion protein in cynomolgus monkeys: QSP modeling of lymphocyte dynamics

XmAb24306 is a lymphoproliferative interleukin (IL)-15/IL-15 receptor α (IL-15Rα) Fc-fusion protein currently under clinical investigation as an immunotherapeutic agent for cancer treatment. XmAb24306 contains mutations in IL-15 that attenuate its affinity to the heterodimeric IL-15 receptor βγ (IL-15R). We observe substantially prolonged pharmacokinetics (PK) (half-life ∼ 2.5 to 4.5 days) in single- and repeat-dose cynomolgus monkey (cyno) studies compared to wild-type IL-15 (half-life ∼ 1 hour), leading to increased exposure and enhanced and durable expansion of NK cells, CD8+ T cells and CD4-CD8- (double negative [DN]) T cells. Drug clearance varied with dose level and time post-dose, and PK exposure decreased upon repeated dosing, which we attribute to increased target-mediated drug disposition (TMDD) resulting from drug-induced lymphocyte expansion (i.e., pharmacodynamic (PD)-enhanced TMDD). We developed a quantitative systems pharmacology (QSP) model to quantify the complex PKPD behaviors due to the interactions of XmAb24306 with multiple cell types (CD8+, CD4+, DN T cells, and NK cells) in the peripheral blood (PB) and lymphoid tissues. The model, which includes nonspecific drug clearance, binding to and TMDD by IL15R differentially expressed on lymphocyte subsets, and resultant lymphocyte margination/migration out of PB, expansion in lymphoid tissues, and redistribution to the blood, successfully describes the systemic PK and lymphocyte kinetics observed in the cyno studies. Results suggest that after 3 doses of every-two-week (Q2W) doses up to 70 days, the relative contributions of each elimination pathway to XmAb24306 clearance are: DN T cells > NK cells > CD8+ T cells > nonspecific clearance > CD4+ T cells. Modeling suggests that observed cellular expansion in blood results from the influx of cells expanded by the drug in lymphoid tissues. The model is used to predict lymphoid tissue expansion and to simulate PK-PD for different dose regimens. Thus, the model provides insight into the mechanisms underlying the observed PK-PD behavior of an engineered cytokine and can serve as a framework for the rapid integration and analysis of data that emerges from ongoing clinical studies in cancer patients as single-agent or given in combination.

Monoclonal Antibody Pharmacokinetics in Cynomolgus Monkeys Following Subcutaneous Administration: Physiologically Based Model Predictions from Physiochemical Properties

An integrated physiologically based modeling framework is presented for predicting pharmacokinetics and bioavailability of subcutaneously administered monoclonal antibodies in cynomolgus monkeys, based on in silico structure-derived metrics characterizing antibody size, overall charge, local charge, and hydrophobicity. The model accounts for antibody-specific differences in pinocytosis, transcapillary transport, local lymphatic uptake, and pre-systemic degradation at the subcutaneous injection site and reliably predicts the pharmacokinetics of five different wild-type mAbs and their Fc variants following intravenous and subcutaneous administration. Significant associations were found between subcutaneous injection site degradation rate and the antibody's local positive charge of its complementarity-determining region (R = 0.56, p = 0.0012), antibody pinocytosis rate and its overall positive charge (R = 0.59, p = 0.00063), and antibody paracellular transport and its overall charge together with hydrophobicity (R = 0.63, p = 0.00096). Based on these results, population simulations were performed to predict the relationship between bioavailability and antibody local positive charge. In addition, model simulations were conducted to calculate the relative contribution of absorption pathways (lymphatic and blood), pre-systemic degradation pathways (interstitial and lysosomal), and the influence of injection site lymph flow on antibody bioavailability and pharmacokinetics. The proposed physiologically based modeling framework integrates fundamental mechanisms governing antibody subcutaneous absorption and disposition, with structured-based physiochemical properties, to predict antibody bioavailability and pharmacokinetics in vivo.

Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection

The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.

Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics

Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.

Recent Advances in Translational Pharmacokinetics and Pharmacodynamics Prediction of Therapeutic Antibodies Using Modeling and Simulation

Therapeutic monoclonal antibodies (mAbs) have been a promising therapeutic approach for several diseases and a wide variety of mAbs are being evaluated in clinical trials. To accelerate clinical development and improve the probability of success, pharmacokinetics and pharmacodynamics (PKPD) in humans must be predicted before clinical trials can begin. Traditionally, empirical-approach-based PKPD prediction has been applied for a long time. Recently, modeling and simulation (M&S) methods have also become valuable for quantitatively predicting PKPD in humans. Although several models (e.g., the compartment model, Michaelis–Menten model, target-mediated drug disposition model, and physiologically based pharmacokinetic model) have been established and used to predict the PKPD of mAbs in humans, more complex mechanistic models, such as the quantitative systemics pharmacology model, have been recently developed. This review summarizes the recent advances and future direction of M&S-based approaches to the quantitative prediction of human PKPD for mAbs.

Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper

Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.

Comparison of Various Approaches to Translate Non-Linear Pharmacokinetics of Monoclonal Antibodies from Cynomolgus Monkey to Human

BACKGROUND AND OBJECTIVES

The prediction of pharmacokinetics of monoclonal antibodies (mAbs) exhibiting non-linear pharmacokinetics in preclinical species to human is challenging, and very limited scientific work has been published in this field of research. Therefore, we have conducted an elaborate comparative assessment to determine the most reliable preclinical to clinical scaling strategy for mAbs with non-linear pharmacokinetics.

METHODS

We have compared three different scaling approaches to predict human pharmacokinetics from cynomolgus monkey. In the first approach, cynomolgus monkey pharmacokinetic parameters estimated using a two-compartment model with parallel linear and non-linear elimination were allometrically scaled to simulate human pharmacokinetics. In the second approach, allometric exponents were integrated with a minimal physiologically based pharmacokinetic (mPBPK) model to translate human pharmacokinetics. In the third approach, we have employed a species time-invariant method, wherein a two-compartment model with parallel linear and non-linear elimination was used as a framework model for simulation of the human profile.

RESULTS

Human exposure parameters projected by an integrated allometric method were only within two fold for approximately 45-70% of predictions at different doses of five mAbs evaluated, while approximately 70-80% of Cmax and AUC predictions by integrated mPBPK modelling as well as the species time-invariant method were within two-fold error. The average fold error for clearance predictions by the integrated mPBPK method was 1.10-1.45 fold, whilst for the species time-variant and integrated allometric methods, the average fold error was between 1.04 and 1.37 fold and 1.24 and 2.13 fold, respectively.

CONCLUSIONS

Our findings suggest that the species time-variant method and mPBPK proposed by us can be employed to reliably translate non-linear pharmacokinetics of mAbs from cynomolgus monkey to human.

Targeting drug delivery in the vascular system: Focus on endothelium

The bloodstream is the main transporting pathway for drug delivery systems (DDS) from the site of administration to the intended site of action. In many cases, components of the vascular system represent therapeutic targets. Endothelial cells, which line the luminal surface of the vasculature, play a tripartite role of the key target, barrier, or victim of nanomedicines in the bloodstream. Circulating DDS may accumulate in the vascular areas of interest and in off-target areas via mechanisms bypassing specific molecular recognition, but using ligands of specific vascular determinant molecules enables a degree of precision, efficacy, and specificity of delivery unattainable by non-affinity DDS. Three decades of research efforts have focused on specific vascular targeting, which have yielded a multitude of DDS, many of which are currently undergoing a translational phase of development for biomedical applications, including interventions in the cardiovascular, pulmonary, and central nervous systems, regulation of endothelial functions, host defense, and permeation of vascular barriers. We discuss the design of endothelial-targeted nanocarriers, factors underlying their interactions with cells and tissues, and describe examples of their investigational use in models of acute vascular inflammation with an eye on translational challenges.

Whole-Body Pharmacokinetics of Antibody in Mice Determined using Enzyme-Linked Immunosorbent Assay and Derivation of Tissue Interstitial Concentrations

Here we have reported whole-body disposition of wild-type IgG and FcRn non-binding IgG in mice, determined using Enzyme-Linked Immunosorbent Assay (ELISA). The disposition data generated using ELISA are compared with previously published biodistribution data generated using radiolabelled IgG. In addition, we introduce a novel concept of ABC_IS values, which are defined as percentage ratios of tissue interstitial and plasma AUC values. These values can help in predicting tissue interstitial concentrations of monoclonal antibodies (mAbs) based on the plasma concentrations. Tissue interstitial concentrations derived from our study are also compared with previously reported values measured using microdialysis or centrifugation method. Lastly, the new set of biodistribution data generated using ELISA are used to refine the PBPK model for mAbs.

The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation

Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.

Physiologically-based modeling of monoclonal antibody pharmacokinetics in drug discovery and development

Over the past few decades, monoclonal antibodies (mAbs) have become one of the most important and fastest growing classes of therapeutic molecules, with applications in a wide variety of disease areas. As such, understanding of the determinants of mAb pharmacokinetic (PK) processes (absorption, distribution, metabolism, and elimination) is crucial in developing safe and efficacious therapeutics. In the present review, we discuss the use of physiologically-based pharmacokinetic (PBPK) models as an approach to characterize the in vivo behavior of mAbs, in the context of the key PK processes that should be considered in these models. Additionally, we discuss current and potential future applications of PBPK in the drug discovery and development timeline for mAbs, spanning from identification of potential target molecules to prediction of potential drug-drug interactions. Finally, we conclude with a discussion of currently available PBPK models for mAbs that could be implemented in the drug development process.

Minimal physiologically-based pharmacokinetic model to investigate the effect of pH dependent FcRn affinity and the endothelial endocytosis on the pharmacokinetics of anti-VEGF humanized IgG1 antibody in cynomolgus monkey

In this study, we developed a first minimal physiologically-based pharmacokinetic (mPBPK) model to investigate the complex interaction effects of endocytosis rate/FcRn binding affinity at both acidic/physiological pH on the pharmacokinetics (PK) of the anti-VEGF IgG₁ antibodies. The data used in this study were the PK of the native IgG and humanized anti-VEGF IgG₁ antibodies with a wide range FcRn-binding at both acidic and physiological pH in the cynomolgus monkey. The basic structure of the developed mPBPK models consisted of plasma, tissue and lymph compartments. The tissue compartment was subdivided into vascular, endothelial and interstitial spaces. Non-equilibrium binding mechanism was used to describe the FcRn-IgG interaction in the endosome. The fittings in the final model with three pH systems in the endosome compartment showed a good fit based on the visualization of the fitted graphs and the coefficient of variations of the estimated parameters (CV < 50%). The quantitative endocytosis/FcRn binding affinity PK relationships was constructed using the final model to provide better understanding of complex interaction effects of endocytosis rate and FcRn binding on PK of anti-VEGF IgG₁ antibodies. This result may serve as an important model-based drug discovery platform to guide the design and development of the future generation of anti-VEGF IgG₁ or other therapeutic IgG₁ antibodies. In addition, the mPBPK model developed in cynomolgus monkey was successfully used to predict the PK of the anti-VEGF IgG₁ antibody (bevacizumab) in human subjects.

Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting the Effects of Anti-FcRn Therapy on the Disposition of Endogenous IgG in Humans

This work scaled up a previously developed physiologically based pharmacokinetic model to predict the effects of anti-FcRn agents on the disposition of endogenous IgG in human subjects. Simulations were performed with the scaled model to predict the effects of single- and multiple-dose administration of anti-FcRn monoclonal antibodies (1-256 mg/kg) and high-dose intravenous immune globulin (0.4-2 g/kg). The model was evaluated for prediction accuracy through comparison to the effects of rozanolixizumab, an anti-FcRn monoclonal antibodies under current clinical evaluation, on the disposition of endogenous IgG in healthy human subjects. The model provided reasonably accurate predictions of the effects of rozanolixizumab. Prediction errors for the maximum reduction in endogenous IgG concentrations were -8.50% (90% model prediction interval: -14.0% to 1.44%), 3.33% (90% model prediction interval: -13.9% to 21.2%), and 6.85% (90% model prediction interval: -35.2% to 10.5%) for rozanolixizumab doses of 1, 4, and 7 mg/kg, respectively. Model simulations predict that anti-FcRn therapies will exhibit greater dose potency in healthy volunteers than in patients with elevated IgG production rates (e.g., as typically found in autoimmune disease). The model appears to have potential for use in assessing and predicting novel dosing strategies for anti-FcRn therapies.

Application of Physiologically Based Pharmacokinetic Modeling to Predict the Effects of FcRn Inhibitors in Mice, Rats, and Monkeys

There is a growing interest in developing inhibitors of the neonatal Fc-receptor, FcRn, for use in the treatment for humoral autoimmune conditions. We have developed a new physiologically based pharmacokinetic model that is capable of characterizing the pharmacokinetics and pharmacodynamics of anti-FcRn monoclonal antibodies (mAb) in mice, rats, and monkeys. The model includes incorporation of FcRn recycling of immune gamma globulin (IgG) in hematopoietic cells in addition to FcRn recycling of IgG in vascular endothelial cells and considers FcRn turnover and intracellular cycling. The model captured antibody disposition in wild-type and FcRn-knockout mice and rats, and also predicted the effects of intravenous immune globulin and anti-FcRn mAb on IgG disposition. Simulations predicted the change in IgG clearance in response to intravenous immune globulin with good accuracy in rats (mean prediction error of 7.15% ± 7.67%). In monkeys, prediction windows for simulated IgG concentration versus time data, as generated through Monte Carlo simulation, were able to capture the effects of anti-FcRn mAb on endogenous IgG. The model may have utility in guiding preclinical evaluations of anti-FcRn therapies in development, potentially assisting in the identification of optimal dosing strategies for this emerging class of immunosuppressive drugs.

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.

Effects of the FcRn developmental pharmacology on the pharmacokinetics of therapeutic monoclonal IgG antibody in pediatric subjects using minimal physiologically-based pharmacokinetic modelling

The aim of this study was to investigate neonatal Fc receptor (FcRn) concentration developmental pharmacology in adult and pediatric subjects using minimal physiologically-based pharmacokinetic (mPBPK) modelling. Three types of pharmacokinetic (PK) data for three agents (endogenous/exogenous native IgG, bevacizumab and palivizumab) were used. The adult group contained six subjects with weights from 50 to 100 kg. For pediatric subjects, seven age groups were assumed, with five subjects each having the weight of 95%, 75%, 50%, 25% and 5% percentile of the population. A first evidence-based rating system to evaluate the quality of the source data used to derive pediatric-specific mPBPK model parameter was proposed. A stepwise approach was used to examine the best combination of age/weight effect on the parameters of the mPBPK model in adult and pediatric subjects. IgG synthesis rate (K_syn), extravasation rate (ER) and FcRn were fitted simultaneously to the PK of bevacizumab and native-IgG in both adult and pediatric. All fitting showed good fits based on the graphs and the coefficient of variation of the fitted parameters (< 50%). Estimated weight-normalized K_syn increased while weight-normalized FcRn and ER decreased with increasing age. The age and weight effect on FcRn were successfully estimated from the data. The final mPBPK model developed with native IgG and bevacizumab was able to predict the PK of palivizumab in pediatric subjects. Implementation of the mPBPK model enables us to analyze the relationships of age, weight, FcRn, ER and K_syn in both adult and pediatric subject. This information may benefit the understanding of complex interaction between the FcRn developmental pharmacology and PK parameters, and improve the prediction of the antibody disposition in pediatric subjects.

Application of Pharmacokinetics Modelling to Predict Human Exposure of a Cationic Liposomal Subunit Antigen Vaccine System

The pharmacokinetics of a liposomal subunit antigen vaccine system composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and the immunostimulatory agent trehalose 6,6-dibehenate (TDB) (8:1 molar ratio) combined with the Ag85B-ESAT-6 (H1) antigen were modelled using mouse in-vivo data. Compartment modelling and physiologically based pharmacokinetics (PBPK) were used to predict the administration site (muscle) and target site (lymph) temporal concentration profiles and factors governing these. Initial estimates using compartmental modelling established that quadriceps pharmacokinetics for the liposome demonstrated a long half-life (22.6 days) compared to the associated antigen (2.62 days). A mouse minimal-PBPK model was developed and successfully predicted quadriceps liposome and antigen pharmacokinetics. Predictions for the popliteal lymph node (PLN) aligned well at earlier time-points. A local sensitivity analysis highlighted that the predicted AUC_muscle was sensitive to the antigen degradation constant k_deg (resulting in a 3-log change) more so than the fraction escaping the quadriceps (f_e) (resulting in a 10-fold change), and the predicted AUC_PLN was highly sensitive to f_e. A global sensitivity analysis of the antigen in the muscle demonstrated that model predictions were within the 50th percentile for predictions and showed acceptable fits. To further translate in-vitro data previously generated by our group, the mouse minimal-PBPK model was extrapolated to humans and predictions made for antigen pharmacokinetics in muscle and PLN. Global analysis demonstrated that both k_deg and f_e had a minimal impact on the resulting simulations in the muscle but a greater impact in the PLN. In summary, this study has predicted the in-vivo fate of DDA:TDB:H1 in humans and demonstrated the roles that formulation degradation and fraction escaping the depot site can play upon the overall depot effect within the site of administration.

A novel model for the pharmacokinetic studies of bevacizumab and etanercept in healthy volunteers and patients

Therapeutic monoclonal antibodies (mAbs) have been successfully applied to treat various diseases and shown a promising prospect in medical treatment. MAbs have some unique characteristics when compared with small chemical drugs, and their pharmacokinetic (PK) properties are much more complex than those of small chemical drugs, whose eliminations are usually linear. In this study, a new model was established through taking into account the mechanisms of the elimination of mAbs. The proposed model was applied to the modeling and simulation of two kinds of mAbs, including bevacizumab and etanercept, in PK studies of healthy volunteers and eligible patients, and the classical linear compartment model was set as control. The goodness-of-fit of the fitting concentration-time curve of mAbs was calculated to verify the accuracy of both models during the modeling and simulation. The accuracy of the proposed model was better than that of classical linear compartment model in healthy volunteers and even much better in patients. The proposed model demonstrates a stronger ability in the modeling and simulation of mAbs, and may provide a new option for the PK studies of those reagents.

Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity

Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients.

Physiologically-based modeling to predict the clinical behavior of monoclonal antibodies directed against lymphocyte antigens

Many clinically approved and investigational monoclonal antibody (mAb)-based therapeutics are directed against proteins located in the systemic circulation, including cytokines, growth factors, lymphocyte proteins, and shed antigens. Interaction between mAb and target may lead to non-linear pharmacokinetics (PK), characterized by rapid, target-mediated elimination. Several groups have reported that determinants of target-mediated elimination could include mAb-target binding, target expression, and target turnover. Recently, we scaled a physiologically-based pharmacokinetic model for mAb disposition to man and used it to predict the non-linear PK of mAbs directed against tumor epithelial proteins. In this work, we extended the previously described model to account for the influence of lymphocyte proteins on mAb PK in man. To account for the dynamic behavior of lymphocytes in the circulation, lymphocyte cycling between blood and lymphoid organs was described using first-order transfer rate constants. Use of lymphocyte cycling and reported target turnover rates in the model allowed the accurate prediction of the pharmacokinetics and pharmacodynamics (PD) of 4 mAbs (TRX1, MTRX1011a, rituximab, daclizumab) directed against 3 lymphocyte targets (CD4, CD20, CD25). The results described here suggest that the proposed model structure may be useful in the a priori prediction of the PK/PD properties of mAbs directed against antigens in the circulation.

Application of a catenary PBPK model to predict the disposition of "catch and release" anti-PCSK9 antibodies

The development of 'catch and release', or pH-sensitive, monoclonal antibodies (mAb) has become of interest to groups seeking to reduce the influence of target-mediated elimination on pharmacokinetics and pharmacodynamics. In this work, a catenary physiologically-based pharmacokinetic (PBPK) model is described to predict the pharmacokinetic benefit conferred by engineering mAbs for 'catch and release' binding. Our previously published PBPK model was adapted for consideration of the production and elimination of proprotein convertase subtilisin/kexin type 9 (PCSK9) in mice, and the model was then applied to predict the pharmacokinetics of anti-PCSK9 mAb with pH-stable (J10) and pH-sensitive binding (J17). The model was able to generate reasonable predictions of both J10 and J17 plasma pharmacokinetics. For J10, mean (±standard deviation) predicted vs. observed areas under the plasma concentration curve (AUCinf) were: 217 (77.1) vs. 103nMday (1mg/kg), 1.14×10(3) (858) vs. 769nMday (3mg/kg), and 6.60×10(3) (5.58×10(3)) vs. 2.86×10(3)nMday (10mg/kg), and for J17 the values were: 838 (161) vs. 818nMday (1mg/kg), 2.30×10(3) (441) vs. 2.57×10(3)nMday (3mg/kg), and 8.42×10(3) (1.50×10(3)) vs. 9.17×10(3)nMday (10mg/kg). Further simulations with the model predicted that target turnover and the magnitude of change in the complex dissociation rate constant between pH 7.4 and pH 6.0 are key determinants of the improvements in pharmacokinetics associated with 'catch and release' mAbs. The model described here may be useful for prediction of the pharmacokinetics of 'catch and release' mAbs directed against other targets.