Physiologically based pharmacokinetic model for T84.66: a monoclonal anti-CEA antibody

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.

Physiologically based pharmacokinetic (PBPK) model that describes enhanced FcRn-dependent distribution of monoclonal antibodies (mAbs) by pI-engineering in mice

We previously reported that monoclonal antibodies (mAbs) with a high isoelectric point (pI) value tended to exhibit fast plasma clearance (CL) and large steady-state volume of distribution (Vdss) in mice. However, the positive correlation between pI, CL, and Vdss cannot be described by the reported physiologically based pharmacokinetic (PBPK) models, in which FcRn-mediated transcytosis of mAbs is set to be minimal compared to convection-mediated transport. To address this issue, physiological parameters (lymph flow rate, reflection coefficient, endothelial uptake clearance, and FcRn concentration) were optimized based on the pharmacokinetic profiles of mAbs with various pI values in wild type and FcRn-deficient (beta-2-microglobulin knockout [KO]) mice. Simulations using the PBPK model developed in this study showed a positive correlation between pI, CL and Vdss observed in wild-type mice. Therefore, this model successfully characterized our hypothetical mechanism that an electrostatic positive interaction between mAbs and the endothelial membrane enhances FcRn-mediated transcytosis of mAbs, resulting in large Vdss. We sought to determine the right contribution of the two pathways of antibody distribution to the interstitial space and established a new model that could effectively capture the effect of pI on FcRn-mediated distribution of mAbs in the body.

Expansion of platform physiologically-based pharmacokinetic model for monoclonal antibodies towards different preclinical species: cats, sheep, and dogs

Monoclonal antibodies (mAbs) are becoming an important therapeutic option in veterinary medicine, and understanding the pharmacokinetic (PK) of mAbs in higher-order animal species is also important for human drug development. To better understand the PK of mAbs in these animals, here we have expanded a platform physiological-based pharmacokinetic (PBPK) model to characterize the disposition of mAbs in three different preclinical species: cats, sheep, and dogs. We obtained PK data for mAbs and physiological parameters for the three different species from the literature. We were able to describe the PK of mAbs following intravenous (IV) or subcutaneous administration in cats, IV administration in sheep, and IV administration dogs reasonably well by fixing the physiological parameters and just estimating the parameters related to the binding of mAbs to the neonatal Fc receptor. The platform PBPK model presented here provides a quantitative tool to predict the plasma PK of mAbs in dogs, cats, and sheep. The model can also predict mAb PK in different tissues where the site of action might be located. As such, the mAb PBPK model presented here can facilitate the discovery, development, and preclinical-to-clinical translation of mAbs for veterinary and human medicine. The model can also be modified in the future to account for more detailed compartments for certain organs, different pathophysiology in the animals, and target-mediated drug disposition.

Assessment of Clinical Response to V937 Oncolytic Virus After Intravenous or Intratumoral Administration Using Physiologically-Based Modeling

Oncolytic viruses (OVs) represent a potential therapeutic strategy in cancer treatment. However, there is currently a lack of comprehensive quantitative models characterizing clinical OV kinetics and distribution to the tumor. In this work, we present a mechanistic modeling framework for V937 OV, after intratumoral (i.t.) or intravascular (i.v.) administration in patients with cancer. A minimal physiologically-based pharmacokinetic model was built to characterize biodistribution of OVs in humans. Viral dynamics was incorporated at the i.t. cellular level and linked to tumor response, enabling the characterization of a direct OV killing triggered by the death of infected tumor cells and an indirect killing induced by the immune response. The model provided an adequate description of changes in V937 mRNA levels and tumor size obtained from phase I/II clinical trials after V937 administration. The model showed prominent role of viral clearance from systemic circulation and infectivity in addition to known tumor aggressiveness on clinical response. After i.v. administration, i.t. exposure of V937 was predicted to be several orders of magnitude lower compared with i.t. administration. These differences could be overcome if there is high virus infectivity and/or replication. Unfortunately, the latter process could not be identified at the current clinical setting. This work provides insights on selecting optimal OV considering replication rate and infectivity.

Mechanisms of Obesity-Induced Changes in Pharmacokinetics of IgG in Rats

PURPOSE

To evaluate how obesity affects the pharmacokinetics of human IgG following subcutaneous (SC) and intravenous (IV) administration to rats and the homeostasis of endogenous rat IgG.

METHODS

Differences in body weight and size, body composition, and serum concentration of endogenous rat IgG in male Zucker obese (ZUC-FA/FA) and control (ZUC-LEAN) rats were measured from the age of 5 weeks up to 30 weeks. At the age of 23-24 weeks animals received a single IV or SC dose of human IgG (1 g/kg of total body weight), and serum pharmacokinetics was followed for 7 weeks. A mechanistic model linking obesity-related changes in pharmacokinetics with animal growth and changes in body composition was developed.

RESULTS

Significant differences were observed in both endogenous and exogenous IgG pharmacokinetics between obese and control groups. The AUC for human IgG was lower in obese groups (57.6% of control after IV and 48.1% after SC dosing), and clearance was 1.75-fold higher in obese animals. The mechanistic population model successfully captured the data and included several major components: endogenous rat IgG homeostasis with age-dependent synthesis rate; competition of human IgG and endogenous rat IgG for FcRn binding and its effect on endogenous rat IgG concentrations following injection of a high dose of human IgG; and the effect of body size and composition (changing over time and dependent on the obesity status) on pharmacokinetic parameters.

CONCLUSIONS

We identified important obesity-induced changes in the pharmacokinetics of IgG. Results can potentially facilitate optimization of the dosing of IgG-based therapeutics in the obese population.

Toward systems-informed models for biologics disposition: covariates of the abundance of the neonatal Fc Receptor (FcRn) in human tissues and implications for pharmacokinetic modelling

Biologics are a fast-growing therapeutic class, with intertwined pharmacokinetics and pharmacodynamics, affected by the abundance and function of the FcRn receptor. While many investigators assume adequacy of classical models, such as allometry, for pharmacokinetic characterization of biologics, advocates of physiologically-based pharmacokinetics (PBPK) propose consideration of known systems parameters that affect the fate of biologics to enable a priori predictions, which go beyond allometry. The aim of this study was to deploy a systems-informed modelling approach to predict the disposition of Fc-containing biologics. We used global proteomics to quantify the FcRn receptor [p51 and β₂-microglobulin (B2M) subunits] in 167 samples of human tissue (liver, intestine, kidney and skin) and assessed covariates of its expression. FcRn p51 subunit was highest in liver relative to other tissues, and B2M was 1-2 orders of magnitude more abundant than FcRn p51 across all sets. There were no sex-related differences, while higher expression was confirmed in neonate liver compared with adult liver. Trends of expression in liver and kidney indicated a moderate effect of body mass index, which should be confirmed in a larger sample size. Expression of FcRn p51 subunit was approximately 2-fold lower in histologically normal liver tissue adjacent to cancer compared with healthy liver. FcRn mRNA in plasma-derived exosomes correlated moderately with protein abundance in matching liver tissue, opening the possibility of use as a potential clinical tool. Predicted effects of trends in FcRn abundance in healthy and disease (cancer and psoriasis) populations using trastuzumab and efalizumab PBPK models were in line with clinical observations, and global sensitivity analysis revealed endogenous IgG plasma concentration and tissue FcRn abundance as key systems parameters influencing exposure to Fc-conjugated biologics.

Physiologically-based pharmacokinetic model for pulmonary disposition of protein therapeutics in humans

Lung related disorders like COPD and Asthma, as well as various infectious diseases, form a major therapeutic area which would benefit from a predictive and adaptable mathematical model for describing pulmonary disposition of biological modalities. In this study we fill that gap by extending the cross-species two-pore physiologically-based pharmacokinetic (PBPK) platform with more detailed respiratory tract that includes the airways and alveolar space with epithelial lining fluid. We parameterize the paracellular and FcRn-facilitated exchange pathways between the epithelial lining fluid and lung interstitial space by building a mechanistic model for the exchange between the two. The optimized two-pore PBPK model described pulmonary exposure of several systemically dosed mAbs for which data is available and is also in agreement with the observed levels of endogenous IgG and albumin. The proposed framework can be used to assess pharmacokinetics of new lung-targeting biologic therapies and guide their dosing to achieve desired exposure at the pulmonary site-of-action.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

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.

Targeted Delivery of Endosomal Escape Peptides to Enhance Immunotoxin Potency and Anti-cancer Efficacy

This work describes use of anti-carcinoembryonic antigen antibodies (10H6, T84.66) for targeted delivery of an endosomal escape peptide (H6CM18) and gelonin, a type I ribosome inactivating protein. The viability of colorectal cancer cells (LS174T, LoVo) was assessed following treatment with gelonin or gelonin immunotoxins, with or without co-treatment with T84.66-H6CM18. Fluorescent microscopy was used to visualize the escape of immunoconjugates from endosomes of treated cells, and efficacy and toxicity were assessed in vivo in xenograft tumor-bearing mice following single- and multiple-dose regimens. Application of 25 pM T84.66-H6CM18 combined with T84.66-gelonin increased gelonin potency by ~ 1,000-fold and by ~ 6,000-fold in LS174T and LoVo cells. Intravenous 10H6-gelonin at 1.0 mg/kg was well tolerated by LS174T tumor-bearing mice, while 10 and 25 mg/kg doses led to signs of toxicity. Single-dose administration of PBS, gelonin conjugated to T84.66 or 10H6, T84.66-H6CM18, or gelonin immunotoxins co-administered with T84.66-H6CM18 were evaluated. The combinations of T84.66-gelonin + 1.0 mg/kg T84.66-H6CM18 and 10H6-gelonin + 0.1 mg/kg T84.66-H6CM18 led to significant delays in LS174T growth. Use of a multiple-dose regimen allowed further anti-tumor effects, significantly extending median survival time by 33% and by 69%, for mice receiving 1 mg/kg 10H6-gelonin + 0.1 mg/kg T84.66-H6CM18 (p = 0.0072) and 1 mg/kg 10H6-gelonin + 1 mg/kg T84.66-H6CM18 (p = 0.0017). Combined administration of gelonin immunoconjugates with antibody-targeted endosomal escape peptides increased the delivery of gelonin to the cytoplasm of targeted cells, increased gelonin cell killing in vitro by 1,000-6,000 fold, and significantly increased in vivo efficacy.

Model-Based Assessment of the Contribution of Monocytes and Macrophages to the Pharmacokinetics of Monoclonal Antibodies

PURPOSE

We have hypothesized that a high concentration of circulating monocytes and macrophages may contribute to the fast weight-based clearance of monoclonal antibodies (mAbs) in young children. Exploring this hypothesis, this work uses modeling to clarify the role of monocytes and macrophages in the elimination of mAbs.

METHODS

Leveraging pre-clinical data from mice, a minimal physiologically-based pharmacokinetic model was developed to characterize mAb uptake and FcRn-mediated recycling in circulating monocytes, macrophages, and endothelial cells. The model characterized IgG disposition in complex scenarios of site-specific FcRn deletion and variable endogenous IgG levels. Evaluation was performed for predicting IgG disposition with co-administration of high dose IVIG. A one-at-a-time sensitivity analysis quantified the role of relevant cellular parameters on IgG elimination in various scenarios.

RESULTS

The plasma AUC of mAbs was highly sensitive to endothelial cell parameters, but had near-nil sensitivity to monocyte and macrophage parameters, even in scenarios with 90% loss of FcRn expression/activity. In mice with normal FcRn expression, simulations suggest that less than 2% of an IV dose is eliminated in macrophages, while endothelial cells are predicted to dominate mAb elimination.

CONCLUSIONS

The model suggests that the role of monocytes and macrophages in IgG homeostasis includes extensive uptake and highly efficient FcRn-mediated protection, but not appreciable degradation when FcRn is present. Therefore, it is very unlikely that a high concentration of circulating monocytes can contribute to explaining the fast weight-based clearance of mAbs in very young children, even if FcRn expression/activity was 90% lower in children than in adults.

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.

Potential and pitfalls of 89Zr-immuno-PET to assess target status: 89Zr-trastuzumab as an example

Background

⁸⁹Zirconium-immuno-positron emission tomography (⁸⁹Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation.

Methods

The relation between tumor uptake and target concentration was predicted by mathematical modeling of ⁸⁹Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example.

Results

⁸⁹Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg ⁸⁹Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3.

Conclusion

The example for ⁸⁹Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose.

Pivotal Dose of Pembrolizumab: A Dose-Finding Strategy for Immuno-Oncology

Despite numerous publications emphasizing the value of dose finding, drug development in oncology is dominated by the mindset that higher dose provides higher efficacy. Examples of dose finding implemented by biopharmaceutical firms can change this mindset. The purpose of this article is to outline a pragmatic dose selection strategy for immuno-oncology (IO) and other targeted monoclonal antibodies (mAbs). The approach was implemented for pembrolizumab. Selecting a recommended phase II dose (RP2D) with a novel mechanism of action is often challenging due to uncertain relationships between pharmacodynamics measurements and clinical end points. Additionally, phase I efficacy and safety data are generally inadequate for RP2D selection for IO mAbs. Here, the RP2D was estimated based on phase I (clinical study KN001 A and A2) pharmacokinetics data as the dose required for target saturation, which represents a surrogate for maximal pharmacological effect for antagonist mAbs. Due to limitations associated with collecting and analyzing tumor biopsies, characterizing intratumoral target engagement (TE) is challenging. To overcome this gap, a physiologically-based pharmacokinetic model was implemented to predict intratumoral TE. As tumors are spatially heterogeneous, TE was predicted in well-vascularized and poorly vascularized tumor regions. Additionally, impact of differences in target expression, for example, due to interindividual variability and cancer type, was simulated. Simulations showed that 200 mg every 3 weeks can achieve ≥ 90% TE in clinically relevant scenarios, resulting in the recommendation of 200 mg every 3 weeks as the RP2D. Randomized dose comparison studies (KN001 B2 and D) showing similar efficacy over a fivefold dose/exposure range confirmed the RP2D as the pivotal dose.

Pharmacokinetics and pharmacodynamics of therapeutic antibodies in tumors and tumor-draining lymph nodes

The signaling axis from the primary tumor to the tumor-draining lymph node (TDLN) has emerged as a crucial mediator for the efficacy of immunotherapies in neoadjuvant settings, challenging the primary use of immunotherapy in adjuvant settings. TDLNs are regarded as highly opportunistic sites for cancer cell dissemination and promote further spread via several primary tumor-dependent mechanisms. Lesion-level mixed responses to antibody immunotherapy have been traced to local immune signatures present in the TDLN and the organ-specific primary tumors that they drain. However, the pharmacokinetics (PK) and biodistribution gradients of antibodies in primary tumors and TDLNs have not been systemically evaluated. These concentration gradients are critical in ensuring adequate antibody pharmacodynamic (PD) T-cell activation and/or anti-tumor response. The current work reviews the knowledge for developing physiologically-based PK and pharmacodynamic (PBPK/PD) models to quantify antibody biodistribution gradients in anatomically distinct primary tumors and TDLNs as a means to characterize the clinically observed heterogeneous responses to antibody therapies. Several clinical and pathophysiological considerations in modeling the primary tumor-TDLN axis, as well as a summary of both preclinical and clinical PK/PD lymphatic antibody disposition studies, will be provided.

Development of a physiologically-based pharmacokinetic model for ocular disposition of monoclonal antibodies in rabbits

Development of protein therapeutics for ocular disorders, particularly age-related macular degeneration (AMD), is a highly competitive and expanding therapeutic area. However, the application of a predictive and translatable ocular PK model to better understand ocular disposition of protein therapeutics, such as a physiologically-based pharmacokinetic (PBPK) model, is missing from the literature. Here, we present an expansion of an antibody platform PBPK model towards rabbit and incorporate a novel anatomical and physiologically relevant ocular component. Parameters describing all tissues, flows, and binding events were obtained from existing literature and fixed a priori. First, translation of the platform PBPK model to rabbit was confirmed by evaluating the model's ability to predict plasma PK of a systemically administered exogenous antibody. Then, the PBPK model with the new ocular component was validated by estimation of serum and ocular (i.e. aqueous humor, retina, and vitreous humor) PK of two intravitreally administered monoclonal antibodies. We show that the proposed PBPK model is capable of accurately (i.e. within twofold) predicting ocular exposure of antibody-based drugs. The proposed PBPK model can be used for preclinical-to-clinical translation of antibodies developed for ocular disorders, and assessment of ocular toxicity for systemically administered antibody-based therapeutics.

A Physiologically-Based Pharmacokinetic Model for the Prediction of "Half-Life Extension" and "Catch and Release" Monoclonal Antibody Pharmacokinetics

Monoclonal antibodies (mAbs) can be engineered to have “extended half‐life” and “catch and release” properties to improve target coverage. We have developed a mAb physiologically‐based pharmacokinetic model that describes intracellular trafficking, neonatal Fc receptor (FcRn) recycling, and nonspecific clearance of mAbs. We extended this model to capture target binding as a function of target affinity, expression, and turnover. For mAbs engineered to have an extended half‐life, the model was able to accurately predict the terminal half‐life (82% within 2‐fold error of the observed value) in the human FcRn transgenic (Tg32) homozygous mouse and human. The model also accurately captures the trend in pharmacokinetic and target coverage data for a set of mAbs with differing catch and release properties in the Tg32 mouse. The mechanistic nature of this model allows us to explore different engineering techniques early in drug discovery, potentially expanding the number of “druggable” targets.

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.

A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

A translational platform PBPK model for antibody disposition in the brain

In this manuscript, we have presented the development of a novel platform physiologically-based pharmacokinetic (PBPK) model to characterize brain disposition of mAbs in the mouse, rat, monkey and human. The model accounts for known anatomy and physiology of the brain, including the presence of distinct blood-brain barrier and blood-cerebrospinal fluid (CSF) barrier. CSF and interstitial fluid turnover, and FcRn mediated transport of mAbs are accounted for. The model was first used to characterize published and in-house pharmacokinetic (PK) data on the disposition of mAbs in rat brain, including the data on PK of mAb in different regions of brain determined using microdialysis. Majority of model parameters were fixed based on literature reported values, and only 3 parameters were estimated using rat data. The rat PBPK model was translated to mouse, monkey, and human, simply by changing the values of physiological parameters corresponding to each species. The translated PBPK models were validated by a priori predicting brain PK of mAbs in all three species, and comparing predicted exposures with observed data. The platform PBPK model was able to a priori predict all the validation PK profiles reasonably well (within threefold), without estimating any parameters. As such, the platform PBPK model presented here provides an unprecedented quantitative tool for prediction of mAb PK at the site-of-action in the brain, and preclinical-to-clinical translation of mAbs being developed against central nervous system (CNS) disorders. The proposed model can be further expanded to account for target engagement, disease pathophysiology, and novel mechanisms, to support discovery and development of novel CNS targeting mAbs.

Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans

Salvage of endogenous immunoglobulin G (IgG) by the neonatal Fc receptor (FcRn) is implicated in many clinical areas, including therapeutic monoclonal antibody kinetics, patient monitoring in IgG multiple myeloma, and antibody-mediated transplant rejection. There is a clear clinical need for a fully parameterized model of FcRn-mediated recycling of endogenous IgG to allow for predictive modeling, with the potential for optimizing therapeutic regimens for better patient outcomes. In this paper we study a mechanism-based model incorporating nonlinear FcRn-IgG binding kinetics. The aim of this study is to determine whether parameter values can be estimated using the limited in vivo human data, available in the literature, from studies of the kinetics of radiolabeled IgG in humans. We derive mathematical descriptions of the experimental observations-timecourse data and fractional catabolic rate (FCR) data-based on the underlying physiological model. Structural identifiability analyses are performed to determine which, if any, of the parameters are unique with respect to the observations. Structurally identifiable parameters are then estimated from the data. It is found that parameter values estimated from timecourse data are not robust, suggesting that the model complexity is not supported by the available data. Based upon the structural identifiability analyses, a new expression for the FCR is derived. This expression is fitted to the FCR data to estimate unknown parameter values. Using these parameter estimates, the plasma IgG response is simulated under clinical conditions. Finally a suggestion is made for a reduced-order model based upon the newly derived expression for the FCR. The reduced-order model is used to predict the plasma IgG response, which is compared with the original four-compartment model, showing good agreement. This paper shows how techniques for compartmental model analysis-structural identifiability analysis, linearization, and reparameterization-can be used to ensure robust parameter identification.

Two-pore physiologically based pharmacokinetic model with de novo derived parameters for predicting plasma PK of different size protein therapeutics

Two-pore PBPK models have been used for characterizing the PK of protein therapeutics since 1990s. However, widespread utilization of these models is hampered by the lack of a priori parameter values, which are typically estimated using the observed data. To overcome this hurdle, here we have presented the development of a two-pore PBPK model using de novo derived parameters. The PBPK model was validated using plasma PK data for different size proteins in mice. Using the "two pore theory" we were able to establish the relationship between protein size and key model parameters, such as: permeability-surface area product (PS), vascular reflection coefficient (σ), peclet number (Pe), and glomerular sieving coefficient (θ). The model accounted for size dependent changes in tissue extravasation and glomerular filtration. The model was able to a priori predict the PK of 8 different proteins: IgG (150 kDa), scFv-Fc (105 kDa), F(ab)₂ (100 kDa, minibody (80 kDa), scFv₂ (55 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), and nanobody (13 kDa). In addition, the model was able to provide unprecedented quantitative insight into the relative contribution of convective and diffusive pathway towards trans-capillary mass transportation of different size proteins. The two-pore PBPK model was also able to predict systemic clearance (CL) versus Molecular Weight relationship for different size proteins reasonably well. As such, the PBPK model proposed here represents a bottom-up systems PK model for protein therapeutics, which can serve as a generalized platform for the development of truly translational PBPK model for protein therapeutics.

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.

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.

MPBPK-TMDD models for mAbs: alternative models, comparison, and identifiability issues

The aim of the present study was to evaluate model identifiability when minimal physiologically-based pharmacokinetic (mPBPK) models are integrated with target mediated drug disposition (TMDD) models in the tissue compartment. Three quasi-steady-state (QSS) approximations of TMDD dynamics were explored: on (a) antibody-target complex, (b) free target, and (c) free antibody concentrations in tissue. The effects of the QSS approximations were assessed via simulations, taking as reference the mPBPK-TMDD model with no simplifications. Approximation (a) did not affect model-derived concentrations, while with the inclusion of approximation (b) or (c), target concentration profiles alone, or both drug and target concentration profiles respectively deviated from the reference model profiles. A local sensitivity analysis was performed, highlighting the potential importance of sampling in the terminal pharmacokinetic phase and of collecting target concentration data. The a priori and a posteriori identifiability of the mPBPK-TMDD models were investigated under different experimental scenarios and designs. The reference model and QSS approximation (a) on antibody-target complex were both found to be a priori identifiable in all scenarios, while under the further inclusion of QSS approximation (b) target concentration data were needed for a priori identifiability to be preserved. The property could not be assessed for the model including all three QSS approximations. A posteriori identifiability issues were detected for all models, although improvement was observed when appropriate sampling and dose range were selected. In conclusion, this work provides a theoretical framework for the assessment of key properties of mathematical models before their experimental application. Attention should be paid when applying integrated mPBPK-TMDD models, as identifiability issues do exist, especially when rich study designs are not feasible.

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.

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

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

A minimal physiologically based pharmacokinetic model to investigate FcRn-mediated monoclonal antibody salvage: Effects of Kon, Koff, endosome trafficking, and animal species

Manipulation of binding affinity between monoclonal antibodies (mAbs) and the neonatal Fc receptor (FcRn) has been leveraged to extend mAb half-life; however, the steps required for success remain ambiguous and experimental observations are inconsistent. Recent models have considered the time course of endosomal transit a major contributor to the relationship between FcRn affinity and antibody half-life. Our objective was to develop a minimal physiologically based pharmacokinetic model to explain how changes in IgG-FcRn association rate constant (K_on), dissociation rate constant (K_off), and endosomal transit time [T_(w)] translate to improved IgG clearance across mice, monkeys and humans. By simulating mAb clearance across physiological values of K_on, K_off, and T_(w), we found that lowering K_off improves clearance only until the dissociation half-life reaches endosomal transit time. In contrast, K_on influenced clearance independently of T_(w).The model was then applied to fit 66 mAb plasma profiles across species digitized from the literature, and clearance of mAb (CL_IgG) and vascular fluid-phase endocytosis rate (CL_up) were estimated. We found that CL_IgG scaled well with body weight (allometric exponent of 0.90). After accounting for mAbs with significant FcRn binding at physiological pH, CL_up was allometrically scalable (exponent 0.72). For the antibodies surveyed, K_on was more highly correlated with CL_IgG across all species. The relationship between K_off and K_D with CL_IgG was largely inconsistent. Taken together, this model provides a parsimonious approach to evaluate endosomal transit kinetics using only mAb plasma concentrations. These findings reinforce the idea that endosomal transit kinetics should be considered when modeling FcRn salvage.

Utility of physiologically based pharmacokinetic (PBPK) modeling in oncology drug development and its accuracy: a systematic review

PURPOSE

Physiologically based pharmacokinetic (PBPK) modeling, a mathematical modeling approach which uses a pharmacokinetic model to mimick human physiology to predict drug concentration-time profiles, has been used for the discover and development of drugs in various fields, including oncology, since 2000. There have been a few general review articles on the utilization of PBPK in the development of oncology drugs, but these do not include an evaluation of model prediction accuracy. We therefore conducted a systematic review to define the accuracy of PBPK model prediction and its utility throughout all the developmental phases of oncology drugs.

METHODS

A systematic search was performed in the PubMed, PubMed Central and Cochrane Library databases from 1980 to February 2017 for articles (1) written in English, (2) focused on oncology or antineoplastic or anticancer drugs, tumor or cancer or anticancer drugs listed in the U.S. National Institutes of Health and (3) involving a PBPK model. The absolute-average-folding-errors (AAFEs) of the area under the curve (AUC) between predicted and observed values in each article were calculated to assess model prediction accuracy.

RESULTS

Of the 2341 articles initially identified by our search of the databases, 40 were included in the review analysis. These articles reported on six types of studies, i.e. in vivo (n = 4), first-in-human (n = 5), phase II/III clinical trials (n = 9), organ impairment (n = 3), pediatrics (n = 4) and drug-drug interactions (n = 15). AAFEs of the predicted AUC for all groups of studies were within 1.3-fold of each other despite variations in experimental methodologies.

CONCLUSION

PBPK modeling is a potential tool which can be effectively applied throughout all phases of oncology drug development. The number of experimental animals and human participants enrolled in the studies can be reduced using PBPK modeling and PBPK-population-PK modeling. The limited number of publications of unsuccessful model application to date may contribute to bias toward the usefulness of modeling.

"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.

A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim

Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

Highlighting Vitamin D Receptor-Targeted Activities of 1α,25-Dihydroxyvitamin D3 in Mice via Physiologically Based Pharmacokinetic-Pharmacodynamic Modeling

We expanded our published physiologically based pharmacokinetic model (PBPK) on 1α,25-dihydroxyvitamin D₃ [1,25(OH)₂D₃], ligand of the vitamin D receptor (VDR), to appraise VDR-mediated pharmacodynamics in mice. Since 1,25(OH)₂D₃ kinetics was best described by a segregated-flow intestinal model (SFM) that described a low/partial intestinal (blood/plasma) flow to enterocytes, with feedback regulation of its synthesis (Cyp27b1) and degradation (Cyp24a1) enzymes, this PBPK(SFM) model was expanded to describe the VDR-mediated changes (altered/basal mRNA expression) of target genes/responses with the indirect response model. We examined data on 1) renal Trpv5 (transient receptor potential cation channel, subfamily V member 5) and Trpv6 and intestinal Trpv6 (calcium channels) for calcium absorption; 2) liver 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (Hmgcr) and cytochrome 7α-hydroxylase (Cyp7a1) for cholesterol synthesis and degradation, respectively; and 3) renal and brain Mdr1 (multidrug-resistance protein that encodes the P-glycoprotein) for digoxin disposition after repetitive intraperitoneal doses of 120 pmol 1,25(OH)₂D₃ Fitting, performed with modeling software, yielded reasonable prediction of a dominant role of intestinal Trpv6 in calcium absorption, circadian rhythm that is characterized by simple cosine models for Hmgcr and Cyp7a1 on liver cholesterol, and brain and renal Mdr1 on tissue efflux of digoxin. Fitted parameters on the E_max, EC₅₀, and turnover rate constants of VDR-target genes [zero-order production (k_in) and first-order degradation (k_out) rate constants] showed low coefficients of variation and acceptable median prediction errors (4.5%-40.6%). Sensitivity analyses showed that the E_max and EC₅₀ values are key parameters that could influence the pharmacodynamic responses. In conclusion, the PBPK(SFM)-pharmacodynamic model successfully characterized VDR gene activation and serves as a useful tool to predict the therapeutic effects of 1,25(OH)₂D₃.

Interstitial IgG antibody pharmacokinetics assessed by combined in vivo- and physiologically-based pharmacokinetic modelling approaches

KEY POINTS

For therapeutic antibodies, total tissue concentrations are frequently reported as a lump sum measure of the antibody in residual plasma, interstitial fluid and cells. In terms of correlating antibody exposure to a therapeutic effect, however, interstitial pharmacokinetics might be more relevant. In the present study, we collected total tissue and interstitial antibody biodistribution data in mice and assessed the composition of tissue samples aiming to correct total tissue measurements for plasma and cellular content. All data and parameters were integrated into a refined physiologically-based pharmacokinetic model for monoclonal antibodies to enable the tissue-specific description of antibody pharmacokinetics in the interstitial space. We found that antibody interstitial concentrations are highly tissue-specific and dependent on the underlying capillary structure but, in several tissues, they reach relatively high interstitial concentrations, contradicting the still-prevailing view that both the distribution to tissues and the interstitial concentrations for antibodies are generally low.

ABSTRACT

For most therapeutic antibodies, the interstitium is the target space. Although experimental methods for measuring antibody pharmacokinetics (PK) in this space are not well established, thus making quantitative assessment difficult, the interstitial antibody concentration is assumed to be low. In the present study, we combined direct quantification of antibodies in the interstitial fluid with a physiologically-based PK (PBPK) modelling approach, with the aim of better describing the PK of monoclonal antibodies in the interstitial space of different tissues. We isolated interstitial fluid by tissue centrifugation and conducted an antibody biodistribution study in mice, measuring total tissue and interstitial concentrations in selected tissues. Residual plasma, interstitial volumes and lymph flows, which are important PBPK model parameters, were assessed in vivo. We could thereby refine the PBPK modelling of monoclonal antibodies, better interpret antibody biodistribution data and more accurately predict their PK in the different tissue spaces. Our results indicate that, in tissues with discontinuous capillaries (liver and spleen), interstitial concentrations are reflected by the plasma concentration. In tissues with continuous capillaries (e.g. skin and muscle), ∼50-60% of the plasma concentration is found in the interstitial space. In the brain and kidney, on the other hand, antibodies are restricted to the vascular space. Our data may significantly impact the interpretation of biodistribution data of monoclonal antibodies and might be important when relating measured concentrations to a therapeutic effect. By contrast to the view that the antibody distribution to the interstitial space is limited, using direct measurements and model-based data interpretation, we show that high antibody interstitial concentrations are reached in most tissues.

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.

Quantification of IgG monoclonal antibody clearance in tissues

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.

Impact of altered endogenous IgG on unspecific mAb clearance

Immunodeficient mice are crucial models to evaluate the efficacy of monoclonal antibodies (mAbs). When studying mAb pharmacokinetics (PK), protection from elimination by binding to the neonatal Fc receptor (FcRn) is known to be a major process influencing the unspecific clearance of endogenous and therapeutic IgG. The concentration of endogenous IgG in immunodeficient mice, however is reduced, and this effect on the FcRn protection mechanism and subsequently on unspecific mAb clearance is unknown, yet of great importance for the interpretation of mAb PK data. We used a PBPK modelling approach to elucidate the influence of altered endogenous IgG concentrations on unspecific mAb clearance. To this end, we used PK data in immunodeficient mice, i.e. nude and severe combined immunodeficiency mice. To avoid impact of target-mediated clearance processes, we focussed on mAbs without affinity to a target antigen in these mice. In addition, intravenous immunoglobulin (IVIG) data of immunocompetent mice was used to study the impact of increased total IgG concentrations on unspecific therapeutic antibody clearance. The unspecific clearance is linear, whenever therapeutic IgG concentrations, i.e. mAb and IVIG concentrations are lower than FcRn; it can be non-linear if therapeutic IgG concentrations are larger than FcRn and endogenous IgG concentrations (e.g., under IVIG therapy). Unspecific mAb clearance of immunodeficient mice is effectively linear (under mAb doses as typically used in human). Studying the impact of reduced endogenous IgG concentrations on unspecific mAb clearance is of great relevance for the extrapolation to clinical species, e.g., when predicting mAb PK in immunosuppressed cancer patients.

Analysis of a Compartmental Model of Endogenous Immunoglobulin G Metabolism with Application to Multiple Myeloma

Immunoglobulin G (IgG) metabolism has received much attention in the literature for two reasons: (i) IgG homeostasis is regulated by the neonatal Fc receptor (FcRn), by a pH-dependent and saturable recycling process, which presents an interesting biological system; (ii) the IgG-FcRn interaction may be exploitable as a means for extending the plasma half-life of therapeutic monoclonal antibodies, which are primarily IgG-based. A less-studied problem is the importance of endogenous IgG metabolism in IgG multiple myeloma. In multiple myeloma, quantification of serum monoclonal immunoglobulin plays an important role in diagnosis, monitoring and response assessment. In order to investigate the dynamics of IgG in this setting, a mathematical model characterizing the metabolism of endogenous IgG in humans is required. A number of authors have proposed a two-compartment nonlinear model of IgG metabolism in which saturable recycling is described using Michaelis–Menten kinetics; however it may be difficult to estimate the model parameters from the limited experimental data that are available. The purpose of this study is to analyse the model alongside the available data from experiments in humans and estimate the model parameters. In order to achieve this aim we linearize the model and use several methods of model and parameter validation: stability analysis, structural identifiability analysis, and sensitivity analysis based on traditional sensitivity functions and generalized sensitivity functions. We find that all model parameters are identifiable, structurally and taking into account parameter correlations, when several types of model output are used for parameter estimation. Based on these analyses we estimate parameter values from the limited available data and compare them with previously published parameter values. Finally we show how the model can be applied in future studies of treatment effectiveness in IgG multiple myeloma with simulations of serum monoclonal IgG responses during treatment.

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

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

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.

Tissue expression profile of human neonatal Fc receptor (FcRn) in Tg32 transgenic mice

The neonatal Fc receptor (FcRn) is a homeostatic receptor responsible for prolonging immunoglobulin G (IgG) half-life by protecting it from lysosomal degradation and recycling it to systemic circulation. Tissue-specific FcRn expression is a critical parameter in physiologically-based pharmacokinetic (PBPK) modeling for translational pharmacokinetics of Fc-containing biotherapeutics. Using online peptide immuno-affinity chromatography coupled with high resolution mass spectrometry, we established a quantitative FcRn tissue protein expression profile in human FcRn (hFcRn) transgenic mice, Tg32 homozygous and hemizygous strains. The concentration of hFcRn across 14 tissues ranged from 3.5 to 111.2 pmole per gram of tissue. Our hFcRn quantification data from Tg32 mice will enable a more refined PBPK model to improve the accuracy of human PK predictions for Fc-containing biotherapeutics.

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.

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.

Population physiologically-based pharmacokinetic model incorporating lymphatic uptake for a subcutaneously administered pegylated peptide

PURPOSE

Physiologically-based pharmacokinetic (PBPK) models provide a rational mechanistic approach for predicting the time course of macromolecules in plasma. Population PBPK models for large molecules necessitate incorporation of lymphatic circulation to mechanistically account for biodistribution. Moreover, characterization of subcutaneous absorption requires consideration of the microvascular transit from the injection site to the systemic circulation. A PBPK model for a pegylated peptide conjugate, previously developed for primates, was modified to describe the lymphatic uptake in a population of humans by incorporation of interindividual variability in the lymphatic circulation and a unique lymphatic drainage compartment (LDC). The model was then used to simulate the time course of the drug in a population of humans and compared to the same drug administered to a group of human subjects participating in a first-in-human study.

METHODS

Organ, blood and lymph masses for the population were sampled from either normal or log-normal distributions. Blood flows were calculated for each organ based on mean organ perfusion per gram of organ tissue and lymphatic flow was set as a fixed fraction of blood flow. Interindividual variability in lymphatic volume was assumed to be similar to that of blood volume. The volume of the LDC was parameterzed as a fraction of the injection volume. Sensitivity analysis was performed to study uncertain parameters and distribution assumptions.

RESULTS

The population generator was capable of simulating a virtual population incorporating the lymphatic circulation. Incorporation of a LDC resulted in similar line shape relative to the observed data and incorporation of anthropometric variability accounted for individual differences in the absorption and elimination phases across all dose cohorts. Line shape was sensitive to the inclusion of LDC while peak and elimination portions of the time course were influenced by the magnitude of variance assumed for blood volume and renal clearance, respectively.

CONCLUSION

Lymphatic circulation can be incorporated into a population PBPK model assuming similar interindividual variability as observed for blood volume. Incorporation of an LDC, where the volume of this transit compartment is proportional to the SC injection volume may be an important mechanistic means of predicting the transit from the SC depot to the systemic circulation.

Key factors influencing ADME properties of therapeutic proteins: A need for ADME characterization in drug discovery and development

Protein therapeutics represent a diverse array of biologics including antibodies, fusion proteins, and therapeutic replacement enzymes. Since their inception, they have revolutionized the treatment of a wide range of diseases including respiratory, vascular, autoimmune, inflammatory, infectious, and neurodegenerative diseases, as well as cancer. While in vivo pharmacokinetic, pharmacodynamic, and efficacy studies are routinely carried out for protein therapeutics, studies that identify key factors governing their absorption, distribution, metabolism, and excretion (ADME) properties have not been fully investigated. Thorough characterization and in-depth study of their ADME properties are critical in order to support drug discovery and development processes for the production of safer and more effective biotherapeutics. In this review, we discuss the main factors affecting the ADME characteristics of these large macromolecular therapies. We also give an overview of the current tools, technologies, and approaches available to investigate key factors that influence the ADME of recombinant biotherapeutic drugs, and demonstrate how ADME studies will facilitate their future development.

Challenges and considerations for development of therapeutic proteins in pediatric patients

Target specificity and generally good tolerability of therapeutic proteins (TPs) present desirable treatment opportunities for pediatric patients. However, little is known on the ontogeny of processes related to the pharmacokinetics (PK) and disposition of TPs. The science, regulatory requirements and strategy of developing TPs for children are evolving. Our current review of TPs, (with focus on monoclonal antibodies and fusion proteins) that were approved for pediatric use indicates that dose-selection for pediatric pivotal studies is often based on adult PK information alone. This approach might not be sufficient if more complex PK properties than simple linear PK are present. Body weight-based dosing for pediatric patients directly scaled down from adult dosing can lead to under-exposure in young pediatric patients who are usually in the lowest body-weight range. Tiered-fixed dosing can be reasonably effective for TPs in achieving comparable exposure in children over a wide age range. The uniqueness of the pediatric population, the practical challenges in conducting clinical studies in this population, as well as regulations from health authorities warrant including pharmacometrics as an integral component of pediatric drug development. We propose a framework distinct from previous proposals, to guide clinical pharmacology strategy for pediatric drug development specifically for TPs.