Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies

Translational two-pore PBPK model to characterize whole-body disposition of different-size endogenous and exogenous proteins

Two-pore physiologically based pharmacokinetic (PBPK) modeling has demonstrated its potential in describing the pharmacokinetics (PK) of different-size proteins. However, all existing two-pore models lack either diverse proteins for validation or interspecies extrapolation. To fill the gap, here we have developed and optimized a translational two-pore PBPK model that can characterize plasma and tissue disposition of different-size proteins in mice, rats, monkeys, and humans. Datasets used for model development include more than 15 types of proteins: IgG (150 kDa), F(ab)2 (100 kDa), minibody (80 kDa), Fc-containing proteins (205, 200, 110, 105, 92, 84, 81, 65, or 60 kDa), albumin conjugate (85.7 kDa), albumin (67 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), dAb2 (23.5 kDa), proteins with an albumin-binding domain (26, 23.5, 22, 16, 14, or 13 kDa), nanobody (13 kDa), and other proteins (110, 65, or 60 kDa). The PBPK model incorporates: (i) molecular weight (MW)-dependent extravasation through large and small pores via diffusion and filtration, (ii) MW-dependent renal filtration, (iii) endosomal FcRn-mediated protection from catabolism for IgG and albumin-related modalities, and (iv) competition for FcRn binding from endogenous IgG and albumin. The finalized model can well characterize PK of most of these proteins, with area under the curve predicted within two-fold error. The model also provides insights into contribution of renal filtration and lysosomal degradation towards total elimination of proteins, and contribution of paracellular convection/diffusion and transcytosis towards extravasation. The PBPK model presented here represents a cross-modality, cross-species platform that can be used for development of novel biologics.

Lymphatic distribution considerations for subunit vaccine design and development

Subunit vaccines are an important platform for controlling current and emerging infectious diseases. The lymph nodes are the primary site generating the humoral response and delivery of antigens to these sites is critical to effective immunization. Indeed, the duration of antigen exposure within the lymph node is correlated with the antibody response. While current licensed vaccines are typically given through the intramuscular route, injecting vaccines subcutaneously allows for direct access to lymphatic vessels and therefore can enhance the transfer of antigen to the lymph nodes. However, protein subunit antigen uptake into the lymph nodes is inefficient, and subunit vaccines require adjuvants to stimulate the initial immune response. Therefore, formulation strategies have been developed to enhance the exposure of subunit proteins and adjuvants to the lymph nodes by increasing lymphatic uptake or prolonging the retention at the injection site. Given that lymph node exposure is a crucial consideration in vaccine design, in depth analyses of the pharmacokinetics of antigens and adjuvants should be the focus of future preclinical and clinical studies. This review will provide an overview of formulation strategies for targeting the lymphatics and prolonging antigen exposure and will discuss pharmacokinetic evaluations which can be applied toward vaccine development.

A Mechanistic Physiologically-Based Pharmacokinetic Platform Model to Guide Adult and Pediatric Intravenous and Subcutaneous Dosing for Bispecific T Cell Engagers

Bispecific T cell engagers (Bi-TCEs) have revolutionized the treatment of oncology indications across both liquid and solid tumors. Bi-TCEs are rapidly evolving from conventional intravenous (i.v.) to more convenient subcutaneous (s.c.) administrations and extending beyond adults to also benefit pediatric patients. Leveraging clinical development experience across three generations of Bi-TCE molecules across both liquid and solid tumor indications from i.v./s.c. dosing in adults and pediatric subjects, we developed a mechanistic-physiologically-based pharmacokinetic (PBPK) platform model for Bi-TCEs. The model utilizes a full PBPK model framework and was successfully validated for PK predictions following i.v. and s.c. dosing across both liquid and solid tumor space in adults for eight Bi-TCEs. After refinement to incorporate physiological ontogeny, the model was successfully validated to predict pediatric PKs in 1 month - < 2 years, 2-11 years, and 12-17 years old subjects following i.v. dosing. Following s.c. dosing in pediatric subjects, the model predicted similar bioavailability, however, a shorter time to maximum concentration (Tmax ) for the three age groups compared with adults. The model was also applied to guide the dosing strategy for first generation of Bi-TCEs for organ impairment, specifically renal impairment, and was able to accurately predict the impact of renal impairment on PK for these relatively small-size Bi-TCEs. This work highlights a novel mechanistic platform model for accurately predicting the PK in adult and pediatric patients across liquid and solid tumor indications from i.v./s.c. dosing and can be used to guide optimal dose and dosing regimen selection and accelerating the clinical development for Bi-TCEs.

A minimal physiologically based pharmacokinetic model to study the combined effect of antibody size, charge, and binding affinity to FcRn/antigen on antibody pharmacokinetics

Protein therapeutics have revolutionized the treatment of a wide range of diseases. While they have distinct physicochemical characteristics that influence their absorption, distribution, metabolism, and excretion (ADME) properties, the relationship between the physicochemical properties and PK is still largely unknown. In this work we present a minimal physiologically-based pharmacokinetic (mPBPK) model that incorporates a multivariate quantitative relation between a therapeutic's physicochemical parameters and its corresponding ADME properties. The model's compound-specific input includes molecular weight, molecular size (Stoke's radius), molecular charge, binding affinity to FcRn, and specific antigen affinity. Through derived and fitted empirical relationships, the model demonstrates the effect of these compound-specific properties on antibody disposition in both plasma and peripheral tissues using observed PK data in mice and humans. The mPBPK model applies the two-pore hypothesis to predict size-based clearance and exposure of full-length antibodies (150 kDa) and antibody fragments (50-100 kDa) within a onefold error. We quantitatively relate antibody charge and PK parameters like uptake rate, non-specific binding affinity, and volume of distribution to capture the relatively faster clearance of positively charged mAb as compared to negatively charged mAb. The model predicts the terminal plasma clearance of slightly positively and negatively charged antibody in humans within a onefold error. The mPBPK model presented in this work can be used to predict the target-mediated disposition of a drug when compound-specific and target-specific properties are known. To our knowledge, a combined effect of antibody weight, size, charge, FcRn, and antigen has not been incorporated and studied in a single mPBPK model previously. By conclusively incorporating and relating a multitude of protein's physicochemical properties to observed PK, our mPBPK model aims to contribute as a platform approach in the early stages of drug development where many of these properties can be optimized to improve a molecule's PK and ultimately its efficacy.

Non-specific irreversible 89Zr-mAb uptake in tumours: evidence from biopsy-proven target-negative tumours using 89Zr-immuno-PET

BACKGROUND

Distribution of mAbs into tumour tissue may occur via different processes contributing differently to the 89Zr-mAb uptake on PET. Target-specific binding in tumours is of main interest; however, non-specific irreversible uptake may also be present, which influences quantification. The aim was to investigate the presence of non-specific irreversible uptake in tumour tissue using Patlak linearization on 89Zr-immuno-PET data of biopsy-proven target-negative tumours. Data of two studies, including target status obtained from biopsies, were retrospectively analysed, and Patlak linearization provided the net rate of irreversible uptake (Ki).

RESULTS

Two tumours were classified as CD20-negative and two as CD20-positive. Four tumours were classified as CEA-negative and nine as CEA-positive. Ki values of CD20-negative (0.43 µL/g/h and 0.92 µL/g/h) and CEA-negative tumours (mdn = 1.97 µL/g/h, interquartile range (IQR) = 1.50-2.39) were higher than zero. Median Ki values of target-negative tumours were lower than CD20-positive (1.87 µL/g/h and 1.90 µL/g/h) and CEA-positive tumours (mdn = 2.77 µL/g/h, IQR = 2.11-3.65).

CONCLUSION

Biopsy-proven target-negative tumours showed irreversible uptake of 89Zr-mAbs measured in vivo using 89Zr-immuno-PET data, which suggests the presence of non-specific irreversible uptake in tumours. Consequently, for 89Zr-immuno-PET, even if the target is absent, a tumour-to-plasma ratio always increases over time.

A compartment model for subcutaneous injection of monoclonal antibodies

Despite the growing popularity of subcutaneous (SC) administration for monoclonal antibodies (mAbs), there remains a limited understanding of the significance of mAb transport rate constants within the interstitial space and the lymphatic system on their pharmacokinetics. To bridge this knowledge gap, we introduce a compartmental model for subcutaneously administered mAbs. Our model differentiates FcRn-expressing cells across various sites, and the model predictions agree with experimental data from both human and rat studies. Our findings indicate that the time to reach the maximum mAb concentration in the plasma, denoted by Tmax, displays a weak positive correlation with mAb half-life and a negligible correlation with bioavailability. In contrast, the half-life of mAbs exhibits a strong positive correlation with bioavailability. Moreover, the rate of mAb transport from lymph to plasma significantly affects the mAb half-life. Increasing the transport rates of mAbs from the injection site to the lymph or from lymph to plasma enhances bioavailability. These insights, combined with our compartmental model, contribute to a deeper understanding of the pharmacokinetics of subcutaneously administered mAbs.

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.

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.

Physiologically Based Pharmacokinetic Modeling to Characterize the Effect of Molecular Charge on Whole-Body Disposition of Monoclonal Antibodies

Motivated by a series of work demonstrating the effect of molecular charge on antibody pharmacokinetics (PK), physiological-based pharmacokinetic (PBPK) models are emerging that relate in silico calculated charge or in vitro measures of polyspecificity to antibody PK parameters. However, only plasma data has been used for model development in these studies, leading to unvalidated assumptions. Here, we present an extended platform PBPK model for antibodies that incorporate charge-dependent endothelial cell pinocytosis rate and nonspecific off-target binding in the interstitial space and on circulating blood cells, to simultaneously characterize whole-body disposition of three antibody charge variants. Predictive potential of various charge metrics was also explored, and the difference between positive charge patches and negative charge patches (i.e., PPC-PNC) was used as the charge parameter to establish quantitative relationships with nonspecific binding affinities and endothelial cell uptake rate. Whole-body disposition of these charge variants was captured well by the model, with less than 2-fold predictive error in area under the curve of most plasma and tissue PK data. The model also predicted that with greater positive charge, nonspecific binding was more substantial, and pinocytosis rate increased especially in brain, heart, kidney, liver, lung, and spleen, but remained unchanged in adipose, bone, muscle, and skin. The presented PBPK model contributes to our understanding of the mechanisms governing the disposition of charged antibodies and can be used as a platform to guide charge engineering based on desired plasma and tissue exposures.

Gallium-68-labeled Peptide PET Quantifies Tumor Exposure of PD-L1 Therapeutics

PURPOSE

Immune checkpoint therapy (ICT) is currently ineffective in a majority of patients. Tumor drug exposure measurements can provide vital insights into mechanisms involved in the resistance of solid tumors to those therapeutics; however, tools to quantify in situ drug exposure are few. We have investigated the potential of programmed death-ligand 1 (PD-L1) pharmacodynamics, quantified using PET, to inform on the tumor exposure of anti-PD-L1 (aPD-L1) therapeutics.

EXPERIMENTAL DESIGN

To noninvasively quantify PD-L1 levels, we first developed a novel peptide-based gallium-68-labeled binder, [68Ga]Ga-DK223, and evaluated its in vivo distribution, pharmacokinetics, and PD-L1 specificity in preclinical models of triple-negative breast cancer and urothelial carcinoma with variable PD-L1 expression. We then quantified baseline and accessible PD-L1 levels in tumors as a noninvasive pharmacodynamic measure to assess tumor exposure to two aPD-L1 antibodies (avelumab and durvalumab).

RESULTS

DK223 exhibited a KD of 1.01±0.83 nmol/L for PD-L1 and inhibited the PD-1:PD-L1 interaction in a dose-dependent manner. [68Ga]Ga-DK223 provides high-contrast PET images within 60 minutes of administration and detects PD-L1 in an expression-dependent manner in xenograft models. PD-L1 pharmacodynamics measured using [68Ga]Ga-DK223-PET revealed that avelumab and durvalumab had similar exposure early during therapy, but only durvalumab exhibited sustained exposure at the tumor.

CONCLUSIONS

[68Ga]Ga-DK223 detected variable PD-L1 levels and exhibited salient features required for clinical translation. [68Ga]Ga-DK223-PET could be useful for quantifying total PD-L1 levels at baseline and accessible PD-L1 levels during therapy to understand drug exposure at the tumor, thus supporting its use for guiding and optimizing ICT.

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.

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.

Opportunities and Challenges for PBPK Model of mAbs in Paediatrics and Pregnancy

New drugs may in some cases need to be tested in paediatric and pregnant patients. However, it is difficult to recruit such patients and there are many ethical issues around their inclusion in clinical trials. Modelling and simulation can help to plan well-designed clinical trials with a reduced number of participants and to bridge gaps where recruitment is difficult. Physiologically based pharmacokinetic (PBPK) models for small molecule drugs have been used to aid study design and dose adjustments in paediatrics and pregnancy, with several publications in the literature. However, published PBPK models for monoclonal antibodies (mAb) in these populations are scarce. Here, the current status of mAb PBPK models in paediatrics and pregnancy is discussed. Seven mAb PBPK models published for paediatrics were found, which report good prediction accuracy across a wide age range. No mAb PBPK models for pregnant women have been published to date. Current challenges to the development of such PBPK models are discussed, including gaps in our knowledge of relevant physiological processes and availability of clinical data to verify models. As the availability of such data increases, it will help to improve our confidence in the PBPK model predictive ability. Advantages for using PBPK models to predict mAb PK in paediatrics and pregnancy are discussed. For example, the ability to incorporate ontogeny and gestational changes in physiology, prediction of maternal, placental and foetal exposure and the ability to make predictions from in vitro and preclinical data prior to clinical data being 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.

Streamlining physiologically‐based pharmacokinetic model design for intravenous delivery of nanoparticle drugs

Physiologically‐based pharmacokinetic (PBPK) modeling for nanoparticles elucidates the nanoparticle drug’s disposition in the body and serves a vital role in drug development and clinical studies. This paper offers a systematic and tutorial‐like approach to developing a model structure and writing distribution ordinary differential equations based on asking binary questions involving the physicochemical nature of the drug in question. Further, by synthesizing existing knowledge, we summarize pertinent aspects in PBPK modeling and create a guide for building model structure and distribution equations, optimizing nanoparticle and non‐nanoparticle specific parameters, and performing sensitivity analysis and model validation. The purpose of this paper is to facilitate a streamlined model development process for students and practitioners in the field.

Pharmacokinetics, Pharmacodynamics, Safety and Immunogenicity of CMAB807, a New Denosumab Biosimilar, in Healthy Chinese Subjects

Objective: Pharmacokinetics (PK), pharmacodynamics (PD), safety and immunogenicity studies were conducted to evaluate the bioequivalence of CMAB807, a biosimilar to denosumab (Prolia^®), which is the only approved RANKL inhibitor for the treatment of osteoporosis.

Methods: In this randomized, double-blind, single-dose phase I study, 132 healthy Chinese male subjects received a subcutaneous injection of 60 mg of CMAB807 or denosumab at a 1:1 ratio. The PK, PD, safety and immunogenicity results were assessed prior to and up to 126 days after administration.

Results: The PK profiles of CMAB807 and denosumab were similar. The geometric mean ratios of the maximum concentration (C_max), AUC_0-t and AUC_o-∞ were 102.41, 104.15 and 103.89%, respectively, and the 90% confidence interval was observed to be within 80.00–125.00%, which indicated the bioequivalence of CMAB807 and denosumab. The PD profiles of the two groups were also comparable. The production of the C-terminal cross-linking telopeptide of type I collagen (CTX1) was inhibited by up to 85% for 10 days, and this inhibition was sustained for up to 126 days in both the CMAB807 and denosumab groups. No subjects in the CMAB807 group, three subjects in the denosumab group before administration, and two subjects in the denosumab group after administration were positive for anti-drug antibody (ADA). Adverse events (AEs) were observed in 98.5% of subjects in both groups. The most common AE recorded was increased parathyroid hormone (PTH) levels, with incidences of 92.4 and 95.5% in the CMAB807 and denosumab groups, respectively. No clinically meaningful differences were observed in safety and immunogenicity between CMAB807 and denosumab.

Conclusion: CMAB807 represents a new potential treatment option for patients with osteoporosis.

Clinical Trial Registration:https://clinicaltrials.gov (Registration No. NCT03925051), http://www.chinadrugtrial/org.cn/index.html (Registration No. CTR20190800).

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.

Physiologically Based Modeling to Predict Monoclonal Antibody Pharmacokinetics in Humans from in vitro Physiochemical Properties

A model-based framework is presented to predict monoclonal antibody (mAb) pharmacokinetics (PK) in humans based on in vitro measures of antibody physiochemical properties. A physiologically based pharmacokinetic (PBPK) model is used to explore the predictive potential of 14 in vitro assays designed to measure various antibody physiochemical properties, including nonspecific cell-surface interactions, FcRn binding, thermal stability, hydrophobicity, and self-association. Based on the mean plasma PK time course data of 22 mAbs from humans reported in the literature, we found a significant positive correlation (R = 0.64, p = .0013) between the model parameter representing antibody-specific vascular to endothelial clearance and heparin relative retention time, an in vitro measure of nonspecific binding. We also found that antibody-specific differences in paracellular transport due to convection and diffusion could be partially explained by antibody heparin relative retention time (R = 0.52, p = .012). Other physiochemical properties, including antibody thermal stability, hydrophobicity, cross-interaction and self-association, in and of themselves were not predictive of model-based transport parameters. In contrast to other studies that have reported empirically derived expressions relating in vitro measures of antibody physiochemical properties directly to antibody clearance, the proposed PBPK model-based approach for predicting mAb PK incorporates fundamental mechanisms governing antibody transport and processing, informed by in vitro measures of antibody physiochemical properties, and can be expanded to include more descriptive representations of each of the antibody processing subsystems, as well as other antibody-specific information.

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.

[Optimization of rabies (Rhabdoviridae: Lyssavirus) dog vaccination schedule using a mathematical model]

INTRODUCTION

Most cases of human rabies are caused by dog (Canis lupus familiaris) bites. Therefore, the implementation of vaccination programs of these animals is one of the urgent tasks.The work aims to identify the factors influencing the production of antirabies virus-neutralizing antibodies (VNAs) in vaccinated dogs, and to formulate recommendations for adjusting the vaccination schedule using mathematical modeling (MM).

MATERIAL AND METHODS

We used a fixed-effects modeling procedure to estimate the two-compartment model parameters using log-transformed data (obtained by RFFIT, rapid fluorescent focus inhibition test; and FAVN, fluorescent antibody virus-neutralization test) on the VNAs levels in the serum of vaccinated dogs.

RESULTS

More vigorous immune response after a two-dose primary vaccination is formed in juvenile dogs at the age of 3 months to 1 year compared to the adult dogs. Following the primary vaccination and revaccination 1 year after, VNAs were produced more intensively in adult stray dogs than in domestic dogs.

DISCUSSION

The short-term immune response observed in dogs aged up to 3 months is due to the presence of colostral antibodies and the active growth of the organism at this age. The results of our study confirm that most of the dogs have a level of antirabies VNAs of ≥0.5 IU/ml up to two or more years following immunization. However, only regular annual revaccination ensures the protective VNAs level in animals that responded poorly to vaccination due to various factors.

CONCLUSION

The following antirabies vaccination schedule is recommended: primary vaccination of the dog at the age of 3 months up to 1 year with 1-2 month intervals, then revaccination annually. This work also demonstrates the possibility of a wider application of MM methods for solving problems of vaccine prevention.

Pharmacodynamic measures within tumors expose differential activity of PD(L)-1 antibody therapeutics

Macromolecules such as monoclonal antibodies (mAbs) are likely to experience poor tumor penetration because of their large size, and thus low drug exposure of target cells within a tumor could contribute to suboptimal responses. Given the challenge of inadequate quantitative tools to assess mAb activity within tumors, we hypothesized that measurement of accessible target levels in tumors could elucidate the pharmacologic activity of a mAb and could be used to compare the activity of different mAbs. Using positron emission tomography (PET), we measured the pharmacodynamics of immune checkpoint protein programmed-death ligand 1 (PD-L1) to evaluate pharmacologic effects of mAbs targeting PD-L1 and its receptor programmed cell death protein 1 (PD-1). For PD-L1 quantification, we first developed a small peptide-based fluorine-18-labeled PET imaging agent, [¹⁸F]DK222, which provided high-contrast images in preclinical models. We then quantified accessible PD-L1 levels in the tumor bed during treatment with anti-PD-1 and anti-PD-L1 mAbs. Applying mixed-effects models to these data, we found subtle differences in the pharmacodynamic effects of two anti-PD-1 mAbs (nivolumab and pembrolizumab). In contrast, we observed starkly divergent target engagement with anti-PD-L1 mAbs (atezolizumab, avelumab, and durvalumab) that were administered at equivalent doses, correlating with differential effects on tumor growth. Thus, we show that measuring PD-L1 pharmacodynamics informs mechanistic understanding of therapeutic mAbs targeting PD-L1 and PD-1. These findings demonstrate the value of quantifying target pharmacodynamics to elucidate the pharmacologic activity of mAbs, independent of mAb biophysical properties and inclusive of all physiological variables, which are highly heterogeneous within and across tumors and patients.

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.

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

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

Safety and pharmacokinetics of a new biosimilar trastuzumab (HL02): a Phase I bioequivalence study in healthy Chinese men

Objectives: The study aimed to explore the bioequivalence of a proposed biosimilar HL02 vs. its reference products (US-trastuzumab) among healthy Chinese men.Methods: In this study, nine healthy male subjects received single ascending doses of trastuzumab biosimilar (HL02, 2-8 mg/kg), and then a randomized, double-blind, two-arm, parallel study was conducted to investigate the PK similarity of HL02 (6 mg/kg) with that of US-trastuzumab as a reference drug.Results: PK properties exhibited by HL02 (N = 55) were similar to those of US-trastuzumab (N = 52). The comparison of biosimilarity with US-trastuzumab showed that the 90% confidence intervals (CIs) of the ratios for C_max, AUC_0-t, and AUC_0-∞ were within 80-125%. Nineteen subjects were positive for ADA and negative for NAb in both HL02 and US-trastuzumab groups. In total, 81.67% of subjects in HL02 and 78.95% in US-trastuzumab groups showed treatment-related mild or moderate adverse events, mild elevation of transaminase level being the most common adverse events (AE) recorded.Conclusions: The PK characteristics and immunogenicity exhibited by HL02 were similar to that of the reference product, US-trastuzumab. The safety profiles were similar in both the treatment groups with mild-moderate adverse effects.

Predicting Method for the Human Plasma Concentration-Time Profile of a Monoclonal Antibody from the Half-life of Non-human Primates

Efficiency (speed and cost) and animal welfare are important factors in the development of new drugs. A novel method (the half-life method) was developed to predict the human plasma concentration-time profile of a monoclonal antibody (mAb) after intravenous (i.v.) administration using less data compared to the conventional approach; moreover, predicted results were comparable to conventional method. This new method use human geometric means of pharmacokinetics (PK) parameters and the non-human primates (NHP) half-life of each mAb. PK data on mAbs in humans and NHPs were collected from literature focusing on linear elimination, and the two-compartment model was used for analysis. The following features were revealed in humans: 1) the coefficient of variation in the distribution volume of the central compartment and at steady state of mAbs was small (22.6 and 23.8%, respectively) and 2) half-life at the elimination phase (t1/2_β) was the main contributor to plasma clearance. Moreover, distribution volume showed no significant correlation between humans and NHPs, and human t1/2_β showed a good correlation with allometrically scaled t1/2_β of NHP. Based on the features revealed in this study, we propose a new method for predicting the human plasma concentration-time profile of mAbs after i.v. dosing. When tested, this half-life method showed reasonable human prediction compared with a conventional empirical approach. The half-life method only requires t1/2_β to predict human PK, and is therefore able to improve animal welfare and potentially accelerate the drug development process.

Heparin chromatography as an in vitro predictor for antibody clearance rate through pinocytosis

The pharmacokinetic (PK) properties of therapeutic antibodies directly affect efficacy, dose and dose intervals, application route and tissue penetration. In indications where health-care providers and patients can choose between several efficacious and safe therapeutic options, convenience (determined by dosing interval or route of application), which is mainly driven by PK properties, can affect drug selection. Therapeutic antibodies can have greatly different PK even if they have identical Fc domains and show no target-mediated drug disposition. Biophysical properties like surface charge or hydrophobicity, and binding to surrogates for high abundant off-targets (e.g., baculovirus particles, Chinese hamster ovary cell membrane proteins) were proposed to be responsible for these differences. Here, we used heparin chromatography to separate a polyclonal mix of endogenous human IgGs (IVIG) into fractions that differ in their PK properties. Heparin was chosen as a surrogate for highly negatively charged glycocalyx components on endothelial cells, which are among the main contributors to nonspecific clearance. By directly correlating heparin retention time with clearance, we identified heparin chromatography as a tool to assess differences in unspecific cell-surface interaction and the likelihood for increased pinocytotic uptake and degradation. Building on these results, we combined predictors for FcRn-mediated recycling and cell-surface interaction. The combination of heparin and FcRn chromatography allow identification of antibodies with abnormal PK by mimicking the major root causes for fast, non-target-mediated, clearance of therapeutic, Fc-containing proteins.

Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings

Constant technological advancement enabled the production of therapeutic monoclonal antibodies (mAbs) and will continue to contribute to their rapid expansion. Compared to small-molecule drugs, mAbs have favorable characteristics, but also more complex pharmacokinetics (PK), e.g., target-mediated nonlinear elimination and recycling by neonatal Fc-receptor. This review briefly discusses mAb biology, similarities and differences in PK processes across species and within human, and provides a detailed overview of allometric scaling approaches for translating mAb PK from preclinical species to human and extrapolating from adults to children. The approaches described here will remain vital in mAb drug development, although more data are needed, for example, from very young patients and mAbs with nonlinear PK, to allow for more confident conclusions and contribute to further growth of this field. Improving mAb PK predictions will facilitate better planning of (pediatric) clinical studies and enable progression toward the ultimate goal of expediting drug development.

Informing Development of Bispecific Antibodies Using Physiologically Based Pharmacokinetic-Pharmacodynamic Models: Current Capabilities and Future Opportunities

Antibody therapeutics continue to represent a significant portion of the biotherapeutic pipeline, with growing promise for bispecific antibodies (BsAbs). BsAbs can target 2 different antigens at the same time, such as simultaneously binding tumor-cell receptors and recruiting cytotoxic immune cells. This simultaneous engagement of 2 targets can be potentially advantageous, as it may overcome disadvantages posed by a monotherapy approach, like the development of resistance to treatment. Combination therapy approaches that modulate 2 targets simultaneously offer similar advantages, but BsAbs are more efficient to develop. Unlike combination approaches, BsAbs can facilitate spatial proximity of targets that may be necessary to induce the desired effect. Successful development of BsAbs requires understanding antibody formatting and optimizing activity for both targets prior to clinical trials. To realize maximal efficacy, special attention is required to fully define pharmacokinetic (PK)/pharmacodynamic (PD) relationships enabling selection of dose and regimen. The application of physiologically based pharmacokinetics (PBPK) has been evolving to inform the development of novel treatment modalities such as bispecifics owing to the increase in our understanding of pharmacology, utility of multiscale models, and emerging clinical data. In this review, we discuss components of PBPK models to describe the PK characteristics of BsAbs and expand the discussion to integration of PBPK and PD models to inform development of BsAbs. A framework that can be adopted to build PBPK-PD models to inform the development of BsAbs is also proposed. We conclude with examples that highlight the application of PBPK-PD and share perspectives on future opportunities for this emerging quantitative tool.

Quantifying PD-L1 Expression to Monitor Immune Checkpoint Therapy: Opportunities and Challenges

Simple Summary

Malignant cells hijack the regulatory roles of immune checkpoint proteins for immune evasion and survival. Therapeutics blocking those proteins can restore the balance of the immune system and lead to durable responses in cancer patients. Although a subset of patients derive benefit, there are few non-invasive technologies to guide and monitor those therapies to improve success rates. This is a review of the advancements in non-invasive methods for quantification of immune checkpoint protein programmed death ligand 1 expression, a biomarker detected by immunohistochemistry and widely used for guiding immune checkpoint therapy.

Abstract

Therapeutics targeting programmed death ligand 1 (PD-L1) protein and its receptor PD-1 are now dominant players in restoring anti-tumor immune responses. PD-L1 detection by immunohistochemistry (IHC) is emerging as a reproducible biomarker for guiding patient stratification for those therapies in some cancers. However, PD-L1 expression in the tumor microenvironment is highly complex. It is upregulated by aberrant genetic alterations, and is highly regulated at the transcriptional, posttranscriptional, and protein levels. Thus, PD-L1 IHC is inadequate to fully understand the relevance of PD-L1 levels in the whole body and their dynamics to improve therapeutic outcomes. Imaging technologies could potentially assist in meeting that need. Early clinical investigations show promising results in quantifying PD-L1 expression in the whole body by positron emission tomography (PET). Within this context, this review summarizes advancements in regulation of PD-L1 expression and imaging agents, and in PD-L1 PET for drug development, and discusses opportunities and challenges presented by these innovations for guiding immune checkpoint therapy (ICT).

Pharmacokinetic prediction of an antibody in mice based on an in vitro cell-based approach using target receptor-expressing cells

In vivo pharmacokinetics (PK) studies using mice and monkeys are the main approaches for evaluating and predicting the PK of antibodies, and there is a strong demand for methods that do not require animal experiments. In this work, we focused on quantitatively predicting the nonlinear PK of an antibody based on cell-based assays. An anti-mouse Fc gamma receptor IIB antibody was used as a model antibody. To determine the PK parameters related to nonspecific elimination in vivo, the plasma concentration profile at 100 mg/kg, at which target-specific clearance is saturated, was analyzed by a 2-compartment model. To estimate the parameters related to target-specific elimination, the Michaelis–Menten constant (K_m) and the maximum elimination rate (V_max) were determined by an uptake assay using Chinese hamster ovary (CHO) cells expressing the target receptor. Finally, the integration of all of these parameters permitted the PK to be predicted at doses ranging from 1 to 100 mg/kg regardless of whether target-specific clearance was saturated or nonsaturated. The findings presented herein show that in vitro assays using target-expressing cells are useful tools for obtaining PK parameters and predicting PK profiles and, in some cases, eliminate the need for in vivo PK studies using experimental animals.

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.

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.

Predicting monoclonal antibody pharmacokinetics following subcutaneous administration via whole-body physiologically-based modeling

Use of the subcutaneous (SC) route for administering monoclonal antibodies (mAbs) to treat chronic conditions has been hindered because of an incomplete understanding of fundamental mechanisms controlling mAb absorption from the SC site, and due to the limited translatability of preclinical studies. In this paper, we report on the development and evaluation of a whole-body physiologically-based model to predict mAb pharmacokinetics following SC administration. The circulatory model is based on the physiological processes governing mAb transport and includes two mAb-specific parameters representing differences in pinocytosis rate and the diffusive/convective transport rates among mAbs. At the SC administration site, two additional parameters are used to represent mAb differences in lymphatic capillary uptake and in pre-systemic clearance. Model development employed clinical intravenous (IV) plasma PK data from 20 mAbs and SC plasma PK data from 12 of these mAbs, as obtained from the literature. The resulting model reliably described both the IV and SC measured plasma concentration data. In addition, a metric based on the positive charge across the mAb's complementarity determining region vicinity was found to positively correlate with the model-based estimates of the mAb-specific parameter governing organ/tissue pinocytosis transport and with estimates of the mAb's SC lymphatic capillary clearance. These two relationships were incorporated into the model and accurately predicted the SC PK profiles of three out of four separate mAbs not included in model development. The whole-body physiologically-based model reported herein, provides a platform to characterize and predict the plasma disposition of monoclonal antibodies following SC administration in humans.

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.

Dose Correction for a Michaelis-Menten Approximation of a Target-Mediated Drug Disposition Model with a Multiple Intravenous Dosing Regimens

This study aimed to develop a method for implementing dose correction in a Michaelis-Menten (M-M) approximation of a target-mediated drug disposition (TMDD) model with multiple intravenous (IV) bolus administrations. We derived the formula of a correction factor (Fcorr) for each dose in a multiple IV bolus dosing regimens for M-M model. Fcorr depends on the residual free drug amount prior IV bolus dosing event and dose amount. We conducted a stochastic simulation and estimation (SSE) exercise based on therapeutic antibody PK parameters to evaluate the effect of Fcorr on parameter estimation. Previously published clinical PK data of recombinant human erythropoietin (rHuEPO) from four clinical trials in healthy subjects receiving multiple IV bolus doses were analyzed by both M-M model with and without dose correction (MMC and MMNC) as well as the rapid-binding/quasi-steady-state (RB/QSS) TMDD models. Our results showed that MMNC introduced bias to fixed-effect parameter estimates and overestimated random-effect variables. Compared with MMC, MMNC was not able to adequately characterize the nonlinearity in the PK data of antibody and rHuEPO. The MMC-based simulation demonstrated that thricely weekly 10 IU/kg rHuEPO dosing regimen yielded Fcorr = 0.5. This result suggested that the lower-than-expected exposure for rHuEPO at low dose is due to target binding. An M-M approximation of the TMDD model should include a dose correction to avoid model misfitting and potential bias in the estimated PK parameters.

Population pharmacokinetics, exposure-safety, and immunogenicity of atezolizumab in pediatric and young adult patients with cancer

BACKGROUND

The iMATRIX-atezolizumab study was a phase I/II, multicenter, open-label study designed to assess the safety and pharmacokinetics of atezolizumab in pediatric and young adult patients. We describe the pharmacokinetics (PK), exposure-safety, and immunogenicity of atezolizumab in pediatric and young adults with metastatic solid tumors or hematologic malignancies enrolled in this study.

METHODS

Patients aged < 18 years (n = 69) received a weight-adjusted dose of atezolizumab (15 mg/kg every 3 weeks [q3w]; maximum 1200 mg); those aged ≥ 18 years (n = 18) received a flat dose (1200 mg q3w). A prior two-compartment intravenous infusion input adult population-PK (popPK) model of atezolizumab was used as a basis to model pediatric data.

RESULTS

A total of 431 atezolizumab serum concentrations from 87 relapse-refractory pediatric and young adult patients enrolled in the iMATRIX-atezolizumab study were used for the popPK analysis. The dataset comprised predominantly patients aged < 18 years, including two infants aged < 2 years, with a wide body weight and age range. The clearance and volume of distribution estimates of atezolizumab were 0.217 L/day and 3.01 L, respectively. Atezolizumab geometric mean trough exposures were ~ 20% lower in pediatric patients versus young adults; this was not clinically meaningful as both groups achieved the target concentration (6 μg/mL). Safety was similar between pediatric and young adult patients with no exposure-safety relationship observed. Limited responses (4/87) precluded an exposure-response assessment on outcomes. A comparable rate (13% vs 11%) of atezolizumab anti-drug antibodies was seen in pediatric and young adult patients.

CONCLUSIONS

These findings demonstrate a similar exposure-safety profile of atezolizumab in pediatric and young adult patients, supportive of weight-based dosing in pediatric patients.

TRIAL REGISTRATION

NCT02541604.

Population pharmacokinetics and covariate analysis of Sym004, an antibody mixture against the epidermal growth factor receptor, in subjects with metastatic colorectal cancer and other solid tumors

Sym004 is an equimolar mixture of two monoclonal antibodies, futuximab and modotuximab, which non-competitively block the epidermal growth factor receptor (EGFR). Sym004 has been clinically tested for treatment of solid tumors. The present work characterizes the non-linear pharmacokinetics (PK) of Sym004 and its constituent antibodies and investigates two types of covariate models for interpreting the interindividual variability of Sym004 exposure. Sym004 serum concentration data from 330 cancer patients participating in four Phase 1 and 2 trials (n = 247 metastatic colorectal cancer, n = 87 various types advanced solid tumors) were pooled for non-linear mixed effects modeling. Dose regimens of 0.4-18 mg/kg Sym004 dosed by i.v. infusion weekly or every 2nd week were explored. The PK profiles for futuximab and modotuximab were parallel, and the parameter values for their population PK models were similar. The PK of Sym004 using the sum of the serum concentrations of futuximab and modotuximab was well captured by a 2-compartment model with parallel linear and saturable, Michaelis-Menten-type elimination. The full covariate model including all plausible covariates included in a single step showed no impact on Sym004 exposure of age, Asian race, renal and hepatic function, tumor type and previous anti-EGFR treatments. The reduced covariate model contained statistically and potentially clinically significant influences of body weight, albumin, sex and baseline tumor size. Population PK modeling and covariate analysis of Sym004 were feasible using the sum of the serum concentrations of the two constituent antibodies. Full and reduced covariate models provided insights into which covariates may be clinically relevant for dose modifications and thus may need further exploration.

A Minimal Physiologically-Based Pharmacokinetic Model Demonstrates Role of the Neonatal Fc Receptor (FcRn) Competition in Drug-Disease Interactions With Antibody Therapy

Disease trajectories following antibody therapy can have a significant impact on the pharmacokinetics of the antibody. Although this phenomenon can often be explained by reduced target-expressing cells, other mechanisms may play a role. We use a novel minimal physiologically-based pharmacokinetic model to evaluate an alternative drug-disease interaction mechanism involving competitive inhibition of neonatal Fc receptor (FcRn)-mediated Immunoglobulin G recycling by paraproteins. The model is validated with clinical data from the anti-FcRn antibody M281 and is used to conduct a scenario test to quantify the interaction among M-protein, the characteristic paraprotein of multiple myeloma (MM), and the anti-CD38 antibody daratumumab indicated for MM treatment. Simulations predict up to a 3.6-fold increase in daratumumab half-life following M-protein reduction, which lends credence to the hypothesis that FcRn competition in MM can manifest as time-dependent reduction of clearance for daratumumab. This model can inform optimal dosing strategies for antibodies in MM and other pathologies of paraprotein excess.

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.

Pharmacokinetic and Drug Metabolism Properties of Novel Therapeutic Modalities

The discovery and development of novel pharmaceutical therapies is rapidly transitioning from a small molecule-dominated focus to a more balanced portfolio consisting of small molecules, monoclonal antibodies, engineered proteins (modified endogenous proteins, bispecific antibodies, and fusion proteins), oligonucleotides, and gene-based therapies. This commentary, and the special issue as a whole, aims to highlight these emerging modalities and the efforts underway to better understand their unique pharmacokinetic and absorption, disposition, metabolism, and excretion (ADME) properties. The articles highlighted herein can be broadly grouped into those focusing on the ADME properties of novel therapeutics, those exploring targeted-delivery strategies, and finally, those discussing oligonucleotide therapies. It is also evident that whereas the field in general continues to progress toward new and more complex molecules, a significant amount of effort is still being placed on antibody-drug conjugates. As therapeutic molecules become increasingly complex, a parallel demand for advancements in experimental and analytical tools will become increasingly evident, both to increase the speed and efficiency of identifying safe and efficacious molecules and simultaneously decreasing our dependence on in vivo studies in preclinical species. The research and commentary included in this special issue will provide researchers, clinicians, and the patients we serve more options in the ongoing fight against grievous illnesses and unmet medical needs. SIGNIFICANCE STATEMENT: Recent trends in drug discovery and development suggest a shift away from a small molecule-dominated approach to a more balanced portfolio that includes small molecules, monoclonal antibodies, engineered proteins, and gene therapies. The research presented in this special issue of Drug Metabolism and Disposition will serve to highlight advancements in the understanding of the mechanisms that govern the pharmacokinetic and drug metabolism properties of the novel therapeutic modalities.

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.

Whole-Body Physiologically Based Pharmacokinetic Modeling of Trastuzumab and Prediction of Human Pharmacokinetics

In the present study, we evaluated the pharmacokinetics (PK) of trastuzumab and sought to predict human PK based on animal studies, through the use of optical imaging and a whole-body physiologically based pharmacokinetic (WB-PBPK) modeling approach. The PK study was conducted in 24 mice, where serial blood samples were withdrawn and major organs were isolated after the last blood withdrawal. The drug concentrations in blood and major organs were measured via optical imaging. The WB-PBPK model was constructed using known physiological values including the volumes of major organs and blood/lymphatic flow. The NONMEM software (version 7.3) was used to determine tissue partition coefficients. Using the WB-PBPK model, a clinical trial simulation was performed with reference to human physiological values acquired from the literature. The simulated human PK was then compared with the actual PK observed in the previous study in which healthy male subjects received 6 mg/kg trastuzumab (Herceptin^®) via intravenous route. The ratio of the simulated versus observed area under the concentration-time curve was 1.02 and that of maximal concentration was 0.72. The current study describes the potential synergistic applications of WB-PBPK and optical imaging in human PK prediction based on preclinical data obtained in early-stage drug development.

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.

Pharmacologic Considerations in the Disposition of Antibodies and Antibody-Drug Conjugates in Preclinical Models and in Patients

The rapid advancement in the development of therapeutic proteins, including monoclonal antibodies (mAbs) and antibody-drug conjugates (ADCs), has created a novel mechanism to selectively deliver highly potent cytotoxic agents in the treatment of cancer. These agents provide numerous benefits compared to traditional small molecule drugs, though their clinical use still requires optimization. The pharmacology of mAbs/ADCs is complex and because ADCs are comprised of multiple components, individual agent characteristics and patient variables can affect their disposition. To further improve the clinical use and rational development of these agents, it is imperative to comprehend the complex mechanisms employed by antibody-based agents in traversing numerous biological barriers and how agent/patient factors affect tumor delivery, toxicities, efficacy, and ultimately, biodistribution. This review provides an updated summary of factors known to affect the disposition of mAbs/ADCs in development and in clinical use, as well as how these factors should be considered in the selection and design of preclinical studies of ADC agents in development.

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.

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.