A physiologically based pharmacokinetic (PBPK) model to characterize and predict the disposition of monoclonal antibody CC49 and its single chain Fv constructs

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.

A PBPK model for PRRT with [177Lu]Lu-DOTA-TATE: Comparison of model implementations in SAAM II and MATLAB/SimBiology

Physiologically based pharmacokinetic (PBPK) models offer the ability to simulate and predict the biodistribution of radiopharmaceuticals and have the potential to enable individualised treatment planning in molecular radiotherapy. The objective of this study was to develop and implement a whole-body compartmental PBPK model for peptide receptor radionuclide therapy (PRRT) with [177Lu]Lu-DOTA-TATE in SimBiology to allow for more complex analyses. The correctness of the model implementation was ensured by comparing its outputs, such as the time-integrated activity (TIA), with those of a PBPK model implemented in SAAM II software.

METHODS

A combined PBPK model for [68Ga]Ga-DOTA-TATE and [177Lu]Lu-DOTA-TATE was developed and implemented in both SAAM II and SimBiology. A retrospective analysis of 12 patients with metastatic neuroendocrine tumours (NETs) was conducted. First, time-activity curves (TACs) and TIAs from the two software were calculated and compared for identical parameter values. Second, pharmacokinetic parameters were fitted to activity concentrations, analysed and compared.

RESULTS

The PBPK model implemented in SimBiology produced TIA results comparable to those generated by the model implemented in SAAM II, with a relative deviation of less than 0.5% when using the same input parameters. The relative deviation of the fitted TIAs was less than 5% when model parameter values were fitted to the measured activity concentrations.

CONCLUSION

The proposed PBPK model implemented in SimBiology can be used for dosimetry in radioligand therapy and TIA prediction. Its outputs are similar to those generated by the PBPK model implemented in SAAM II, confirming the correctness of the model implementation in SimBiology.

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.

Rectal delivery of 89Zr-labeled infliximab-loaded nanoparticles enables PET imaging-guided localized therapy of inflammatory bowel disease

Inflammatory bowel diseases (IBDs) like Crohn's disease and ulcerative colitis involve chronic gastrointestinal inflammation. The pro-inflammatory cytokine tumor necrosis factor-alpha (TNF-α) drives IBD pathogenesis. Anti-TNF-α therapies using monoclonal antibodies (mAbs) like infliximab (INF) help treat IBD but have limitations. We developed inflammation-targeting polyphenol-poloxamer nanoparticles loaded with the anti-inflammatory mAb INF (INF@PPNP) as a novel IBD therapy. Characterization showed that INF@PPNP had favorable stability and purity. Radiolabeling INF@PPNP with 89Zr enabled tracking localization with positron emission tomography (PET) imaging. Rectal administration of 89Zr-INF@PPNP led to colon delivery with remarkably reduced systemic exposure versus intravenous INF revealed by non-invasive PET imaging. 89Zr-INF@PPNP retention at inflamed foci indicated prolonged INF@PPNP action. INF@PPNP rectally achieved similar anti-inflammatory effects as intravenously injected INF, demonstrating the high therapeutic potential. Our findings support the use of nanoparticle-based rectal administration for localized drug delivery, prolonging drug activity and minimizing systemic exposure, ultimately offering an effective approach for treating IBD.

A physiologically based pharmacokinetic model for V937 oncolytic virus in mice

Introduction: Oncolytic viruses (OVs) represent a novel therapeutic strategy in oncology due to their capability to selectively infect and replicate in cancer cells, triggering a direct and/or immune-induced tumor lysis. However, the mechanisms governing OV pharmacokinetics are still poorly understood. This work aims to develop a physiologically based pharmacokinetic model of the novel OV, V937, in non-tumor-bearing mice to get a quantitative understanding of its elimination and tissue uptake processes. Materials and methods: Model development was performed using data obtained from 60 mice. Viral levels were quantified from eight tissues after a single intravenous V937 dose. An external dataset was used for model validation. This test set included multiple-dose experiments with different routes of administration. V937 distribution in each organ was described using a physiological structure based on mouse-specific organ blood flows and volumes. Analyses were performed using the non-linear mixed-effects approach with NONMEM 7.4. Results: Viral levels showed a drop from 108 to 105 copies/µg RNA at day 1 in blood, reflected in a high estimate of total clearance (18.2 mL/h). A well-stirred model provided an adequate description for all organs except the muscle and heart, where a saturable uptake process improved data description. The highest numbers of viral copies were observed in the brain, lymph node, kidney, liver, lung, and spleen on the first day after injection. On the other hand, the maximum amount of viral copies in the heart, muscle, and pancreas occurred 3 days after administration. Conclusion: To the best of our knowledge, this is the first physiologically based pharmacokinetic model developed to characterize OV biodistribution, representing a relevant source of quantitative knowledge regarding the in vivo behavior of OVs. This model can be further expanded by adding a tumor compartment, where OVs could replicate.

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.

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.

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

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

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

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

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

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

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.

Minimal Physiologically-based Pharmacokinetic Model to Investigate the Effect of Charge on the Pharmacokinetics of Humanized anti-HCV-E2 IgG Antibodies in Sprague-Dawley Rats

PURPOSE

To develop a minimal physiologically-based pharmacokinetic (mPBPK) model in quantifying the relationships between the charge and pharmacokinetics (PK) of therapeutic monoclonal IgG antibody (TMAb).

METHODS

PK data used in this study were native IgG and five humanized anti-HCVE2-IgG antibodies in rats. Different models that related the effect of charge on interstitial distribution, transcapillary transport, and cellular uptake for FcRn-mediated metabolism were tested. External validation was conducted to assess if the charge-parameter relationships derived from rats could be used to predict the PK of TMAbs in mice. The final mPBPK model was used to construct the relationships between the FcRn binding and charge on the PK of TMAbs.

RESULTS

Increasing the isoelectric point (pI) of IgG was associated with higher interstitial space distribution and cellular uptake. The transcapillary transport of IgG from plasma to interstitial space remains constant with pI values below 7.96 and then increased linearly with pI. The model-based simulation results suggested that improving the FcRn binding affinity can overcome the problems of low plasma/interstitial space exposures associated with TMAbs with higher pI values by reducing the FcRn-mediated metabolism and hence increasing drug exposure in the interstitial space that has close contact with many solid tumors.

CONCLUSIONS

The final mPBPK model was developed and used to construct complex quantitative relationships between the pI/FcRn binding affinity and PK of TMAbs and such relationships are useful to select the discovery of a "sweet spot" of designing future generation of TMAbs with optimal PK properties to achieve desirable plasma and tissue drug exposures.

Two-pore physiologically based pharmacokinetic model validation using whole-body biodistribution of trastuzumab and different-size fragments in mice

In the past, our lab proposed a two-pore PBPK model for different-size protein therapeutics using de novo derived parameters and the model was validated using plasma PK data of different-size antibody fragments digitized from the literature (Li Z, Shah DK, J Pharmacokinet Pharmacodynam 46(3):305-318, 2009). To further validate the model using tissue distribution data, whole-body biodistribution study of 6 different-size proteins in mice were conducted. Studied molecules covered a wide MW range (13-150 kDa). Plasma PK and tissue distribution profiles is 9 tissues were measured, including heart, lung, liver, spleen, kidney, skin, muscle, small intestine, large intestine. Tumor exposure of different-size proteins were also evaluated. The PBPK model was validated by comparing percentage predictive errors (%PE) between observed and model predicted results for each type of molecule in each tissue. Model validation showed that the two-pore PBPK model was able to predict plasma, tissues and tumor PK of all studied molecules relatively well. This model could serve as a platform for developing a generic PBPK model for protein therapeutics in the future.

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.

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.

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

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

Physiologically Based Pharmacokinetic Modeling and Tissue Distribution Characteristics of SHetA2 in Tumor-Bearing Mice

The orally available novel small molecule SHetA2 is the lead sulfur-containing heteroarotinoid that selectively inhibits cancer cells over normal cells, and is currently under clinical development for anticancer treatment and cancer prevention. The objective of this study was to assess and characterize the tissue distribution of SHetA2 in tumor-bearing mice by developing a physiologically based pharmacokinetic (PBPK) model. An orthotopic SKOV3 ovarian cancer xenograft mouse model was used to most accurately mimic the ovarian cancer tumor microenvironment in the peritoneal cavity. SHetA2 concentrations in plasma and 14 different tissues were measured at various time points after a single intravenous dose of 10 mg/kg and oral dose of 60 mg/kg, and these data were used to develop a whole-body PBPK model. SHetA2 exhibited a multi-exponential plasma concentration decline with an elimination half-life of 4.5 h. Rapid and extensive tissue distribution, which was best described by a perfusion rate-limited model, was observed with the tissue-to-plasma partition coefficients (k_p = 1.4-21.2). The PBPK modeling estimated the systemic clearance (76.4 mL/h) from circulation as a main elimination pathway of SHetA2. It also indicated that the amount absorbed into intestine was the major determining factor for the oral bioavailability (22.3%), while the first-pass loss from liver and intestine contributed minimally (< 1%). Our results provide an insight into SHetA2 tissue distribution characteristics. The developed PBPK model can be used to predict the drug exposure at tumors or local sites of action for different dosing regimens and scaled up to humans to correlate with efficacy.

Understanding the Monoclonal Antibody Disposition after Subcutaneous Administration using a Minimal Physiologically based Pharmacokinetic Model

PURPOSE

Monoclonal antibodies (mAbs) are commonly administered by subcutaneous (SC) route. However, bioavailability is often reduced after SC administration. In addition, the sequential transfer of mAbs through the SC tissue and lymphatic system is not completely understood. Therefore, major objectives of this study were a) To understand absorption of mAbs via the lymphatic system after SC administration using physiologically based pharmacokinetic (PBPK) modeling, and b) to demonstrate application of the model for prediction of SC pharmacokinetics (PK) of mAbs.

METHODS

A minimal PBPK model was constructed using various physiological parameters related to the SC injection site and lymphatic system. The remainder of the body organs were represented using a 2-compartment model (central and peripheral compartments), with parameters derived from available intravenous (IV) PK data. The IV and SC clinical PK data of a total of 10 mAbs were obtained from literature. The SC PK data were used to estimate the lymphatic trunk-lymph node (LN) clearance.

RESULTS

The mean estimated lymphatic trunk-LN clearance obtained from 37 SC PK profiles of mAbs was 0.00213 L/h (0.001332 to 0.002928, 95% confidence intervals). The estimated lymphatic trunk-LN clearance was greater for the mAbs with higher isoelectric point (pI). In addition, the estimated clearance increased with decrease in the bioavailability.

CONCLUSION

The minimal PBPK model identified SC injection site lymph flow, afferent and efferent lymph flows, and volumes associated with the SC injection site, lymphatic capillaries and lymphatic trunk-LN as important physiological parameters governing the absorption of mAbs after SC administration. The model may be used to predict PK of mAbs using the relationship of lymphatic trunk-LN clearance and the pI. In addition, the model can be used as a bottom platform to incorporate SC and lymphatic in vitro clearance data for mAb PK prediction in the future.

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

A critical step in the translational science of nanomaterials from preclinical animal studies to humans is the comprehensive investigation of their disposition (or ADME) and pharmacokinetic behaviours. Disposition and pharmacokinetic data are ideally collected in different animal species (rodent and nonrodent), at different dose levels, and following multiple administrations. These data are used to assess the systemic exposure and effect to nanomaterials, primary determinants of their potential toxicity and therapeutic efficacy. At toxic doses in animal models, pharmacokinetic (termed toxicokinetic) data are related to toxicologic findings that inform the design of nonclinical toxicity studies and contribute to the determination of the maximum recommended starting dose in clinical phase 1 trials. Nanomaterials present a unique challenge for disposition and pharmacokinetic investigations owing to their prolonged circulation times, nonlinear pharmacokinetic profiles, and their extensive distribution into tissues. Predictive relationships between nanomaterial physicochemical properties and behaviours in vivo are lacking and are confounded by anatomical, physiological, and immunological differences amongst preclinical animal models and humans. These challenges are poorly understood and frequently overlooked by investigators, leading to inaccurate assumptions of disposition, pharmacokinetic, and toxicokinetics profiles across species that can have profoundly detrimental impacts for nonclinical toxicity studies and clinical phase 1 trials. Herein are highlighted two research tools for analysing and interpreting disposition and pharmacokinetic data from multiple species and for extrapolating this data accurately in humans. Empirical methodologies and mechanistic mathematical modelling approaches are discussed with emphasis placed on important considerations and caveats for representing nanomaterials, such as the importance of integrating physiological variables associated with the mononuclear phagocyte system (MPS) into extrapolation methods for nanomaterials. The application of these tools will be examined in recent examples of investigational and clinically approved nanomaterials. Finally, strategies for applying these extrapolation tools in a complementary manner to perform dose predictions and in silico toxicity assessments in humans will be explained. A greater familiarity with the available tools and prior experiences of extrapolating nanomaterial disposition and pharmacokinetics from preclinical animal models to humans will hopefully result in a more straightforward roadmap for the clinical translation of promising nanomaterials.

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.

Evaluation of the predictive performance of physiologically based pharmacokinetic models for intramuscular injections of therapeutic proteins

Several physiologically-based pharmacokinetic (PBPK) models have been reported for intravenous (IV) and subcutaneous (SC) injections, but there has been a paucity of work for intramuscular (IM) injections. The primary objective of this work was a wide-scale evaluation of the predictive performance of IM PBPK models of therapeutic proteins. PBPK models for all administration routes available in the literature have regarded muscle as the total muscle (TM) in the body; however, anatomically, the body is composed of discrete muscle groups. Clinically, IM is administered to a specific muscle (SM). We explored the predictive performance of IM PBPK models with an SM or TM dosing site. The plasma concentration-time profiles of seven therapeutic proteins after an IM dose in humans served as the clinically observed data for model evaluation - this was a diverse group ranging from 30 to 149 kDa from six protein classes. Pharmacokinetic parameters C_max, t_max, AUC_0-∞, and ka were estimated. SM and TM IM PBPK approaches were compared using Average Fold Error (AFE) and Pearson Chi-Square LineShape analyses. This work represents the first wide-scale validation of IM PBPK models and suggests that these models predict IM PBPK reasonably well. The SM and TM approach provided comparable performance.

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.

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

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

Targeting therapeutics to endothelium: are we there yet?

Vascular endothelial cells represent an important therapeutic target in many pathologies, including inflammation, oxidative stress, and thrombosis; however, delivery of drugs to this site is often limited by the lack of specific affinity of therapeutics for these cells. Selective delivery of both small molecule drugs and therapeutic proteins to the endothelium has been achieved through the use of targeting ligands, such as monoclonal antibodies, directed against endothelial cell surface markers, particularly cell adhesion molecules (CAMs). Careful selection of target molecules and targeting agents allows for precise delivery to sites of inflammation, thereby maximizing therapeutic drug concentrations at the site of injury. A good understanding of the physiological and pathological determinants of drug and drug carrier pharmacokinetics and biodistribution may allow for a priori identification of optimal properties of drug carrier and targeting agent. Targeted delivery of therapeutics such as antioxidants and antithrombotic agents to the injured endothelium has shown efficacy in preclinical models, suggesting the potential for translation into clinical practice. As with all therapeutics, demonstration of both efficacy and safety are required for successful clinical implementation, which must be considered not only for the individual components (drug, targeting agent, etc.) but also for the sum of the parts (e.g., the drug delivery system), as unexpected toxicities may arise with complex delivery systems. While the use of endothelial targeting has not been translated into the clinic to date, the preclinical results summarized here suggest that there is hope for successful implementation of these agents in the years to come.

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

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

Two-Pore Minimum Physiologically-based Pharmacokinetic Model to Describe the Disposition of Therapeutic Monoclonal IgG Antibody in Humans

PURPOSE

The aim of this study was to develop a two-pore minimum physiologically-based pharmacokinetic (mPBPK) model in describing the pharmacokinetic (PK) of therapeutic monoclonal antibody (TMAb) in human subjects.

METHODS

PK data used in this study were endogenous/exogenous native IgG and two TMAbs (palivizumab and Motavizumab-YTE) in normal volunteer or familial hypercatabolic hypoproteinemia (FIHH) patient. Several important components were implemented to overcome the limitations of the early mPBPK model, e.g. two-pore model to describe the transcapillary transport of IgG from vascular to interstitial space. Six mPBPK models with different osmotic reflection coefficient (OFC) of transcapillary transport, endocytosis rates (ETR) and plasma clearance for the TMAbs/IgG were tested and the best model was selected using AICc values.

RESULTS

The final model consisted of different OFC and ETR values for native IgG and TMAbs, supporting the hypothesis that the dynamics in the endosomal space had an important role in the compliant FcRn salvage mechanism to determine the clearance of TMAbs. The estimated FcRn concentration of FIHH subjects was 2.72 μmol/l. The final two-pore mPBPK model has a better performance for native IgG than previously developed mPBPK model.

CONCLUSIONS

The final two-pore mPBPK model not only overcome the limitations of the early mPBPK model but also has a better performance to describe the disposition of the IgG antibody in human subjects.

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.

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.

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

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

The Use of Microdosing in the Development of Small Organic and Protein Therapeutics

Microdosing as a regulatory concept was introduced to facilitate exploratory studies in humans. The concept involves the use of very low doses of a radionuclide-labeled compound for imaging studies or for assessing plasma pharmacokinetics using equipment that has a highly sensitive readout. The supporting principle is that use of these low doses for a limited time in well-controlled, small populations will limit exposure and have a low risk of adverse effects. Microdosing regulations specify a reduced preclinical toxicology-assessment package in order to shorten the route to human studies and reduce its cost. However, for extrapolation to therapeutically relevant doses and plasma concentrations, there are specific aspects of the use of these low doses and low plasma concentrations that require special attention. These specific aspects are reviewed in this article, with separate attention being paid to small organic molecules and protein therapeutics. The indications for microdosing in drug development are discussed in terms of the 3 pillars of survival in drug development, the first of which is characterization of tissue distribution and access to the site of action; the second, engagement of the target; and the third, induction of tissue responses relevant to a therapeutic response.

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 Pharmacokinetic (PBPK) Modeling of Pharmaceutical Nanoparticles

With the great interests in the discovery and development of drug products containing nanoparticles, there is a great demand of quantitative tools for assessing quality, safety, and efficacy of these products. Physiologically based pharmacokinetic (PBPK) modeling and simulation approaches provide excellent tools for describing and predicting in vivo absorption, distribution, metabolism, and excretion (ADME) of nanoparticles administered through various routes. PBPK modeling of nanoparticles is an emerging field, and more than 20 PBPK models of nanoparticles used in pharmaceutical products have been published in the past decade. This review provides an overview of the ADME characteristics of nanoparticles and how these ADME processes are described in PBPK models. Recent advances in PBPK modeling of pharmaceutical nanoparticles are summarized. The major challenges in model development and validation and possible solutions are also discussed.

Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model

The aim of this tutorial is to introduce the fundamental concepts of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling with a special focus on their practical implementation in a typical PBPK model building workflow. To illustrate basic steps in PBPK model building, a PBPK model for ciprofloxacin will be constructed and coupled to a pharmacodynamic model to simulate the antibacterial activity of ciprofloxacin treatment.

Pulmonary pharmacodynamics of an anti-GM-CSFRα antibody enables therapeutic dosing that limits exposure in the lung

Pulmonary alveolar proteinosis is associated with impaired alveolar macrophage differentiation due to genetic defects in the granulocyte macrophage colony-stimulating factor (GM-CSF) axis or autoantibody blockade of GM-CSF. The anti-GM-CSFRα antibody mavrilimumab has shown clinical benefit in patients with rheumatoid arthritis, but with no accompanying pulmonary pathology observed to date. We aimed to model systemic versus pulmonary pharmacodynamics of an anti-GM-CSFRα antibody to understand the pharmacology that contributes to this therapeutic margin. Mice were dosed intraperitoneal with anti-GM-CSFRα antibody, and pharmacodynamics bioassays for GM-CSFRα inhibition performed on blood and bronchoalveolar lavage (BAL) cells to quantify coverage in the circulation and lung, respectively. A single dose of 3 mg/kg of the anti-GM-CSFRα antibody saturated the systemic cellular pool, but dosing up to 10 times higher had no effect on the responsiveness of BAL cells to GM-CSF. Continued administration of this dose of anti-GM-CSFRα antibody for 7 consecutive days also had no inhibitory effect on these cells. Partial inhibition of GM-CSFRα function on cells from the BAL was only observed after dosing for 5 or 7 consecutive days at 30 mg/kg, 10-fold higher than the proposed therapeutic dose. In conclusion, dosing with anti-GM-CSFRα antibody using regimes that saturate circulating cells, and have been shown to be efficacious in inflammatory arthritis models, did not lead to complete blockade of the alveolar macrophages response to GM-CSF. This suggests a significant therapeutic window is possible with GM-CSF axis inhibition.

Multiscale Modeling of Antibody-Drug Conjugates: Connecting Tissue and Cellular Distribution to Whole Animal Pharmacokinetics and Potential Implications for Efficacy

Antibody-drug conjugates exhibit complex pharmacokinetics due to their combination of macromolecular and small molecule properties. These issues range from systemic concerns, such as deconjugation of the small molecule drug during the long antibody circulation time or rapid clearance from nonspecific interactions, to local tumor tissue heterogeneity, cell bystander effects, and endosomal escape. Mathematical models can be used to study the impact of these processes on overall distribution in an efficient manner, and several types of models have been used to analyze varying aspects of antibody distribution including physiologically based pharmacokinetic (PBPK) models and tissue-level simulations. However, these processes are quantitative in nature and cannot be handled qualitatively in isolation. For example, free antibody from deconjugation of the small molecule will impact the distribution of conjugated antibodies within the tumor. To incorporate these effects into a unified framework, we have coupled the systemic and organ-level distribution of a PBPK model with the tissue-level detail of a distributed parameter tumor model. We used this mathematical model to analyze new experimental results on the distribution of the clinical antibody-drug conjugate Kadcyla in HER2-positive mouse xenografts. This model is able to capture the impact of the drug-antibody ratio (DAR) on tumor penetration, the net result of drug deconjugation, and the effect of using unconjugated antibody to drive ADC penetration deeper into the tumor tissue. This modeling approach will provide quantitative and mechanistic support to experimental studies trying to parse the impact of multiple mechanisms of action for these complex drugs.

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.

Physiologically Based Pharmacokinetic Model for Long-Circulating Inorganic Nanoparticles

A physiologically based pharmacokinetic model was developed for accurately characterizing and predicting the in vivo fate of long-circulating inorganic nanoparticles (NPs). This model is built based on direct visualization of NP disposition details at the organ and cellular level. It was validated with multiple data sets, indicating robust inter-route and interspecies predictive capability. We suggest that the biodistribution of long-circulating inorganic NPs is determined by the uptake and release of NPs by phagocytic cells in target organs.

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.

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

Preclinical assessment of monoclonal antibody (mAb) disposition during drug development often includes investigations in non-human primate models. In many cases, mAb exhibit non-linear disposition that relates to mAb-target binding [i.e., target-mediated disposition (TMD)]. The goal of this work was to develop a physiologically-based pharmacokinetic (PBPK) model to predict non-linear mAb disposition in plasma and in tissues in monkeys. Physiological parameters for monkeys were collected from several sources, and plasma data for several mAbs associated with linear pharmacokinetics were digitized from prior literature reports. The digitized data displayed great variability; therefore, parameters describing inter-antibody variability in the rates of pinocytosis and convection were estimated. For prediction of the disposition of individual antibodies, we incorporated tissue concentrations of target proteins, where concentrations were estimated based on categorical immunohistochemistry scores, and with assumed localization of target within the interstitial space of each organ. Kinetics of target-mAb binding and target turnover, in the presence or absence of mAb, were implemented. The model was then employed to predict concentration versus time data, via Monte Carlo simulation, for two mAb that have been shown to exhibit TMD (2F8 and tocilizumab). Model predictions, performed a priori with no parameter fitting, were found to provide good prediction of dose-dependencies in plasma clearance, the areas under plasma concentration versu time curves, and the time-course of plasma concentration data. This PBPK model may find utility in predicting plasma and tissue concentration versus time data and, potentially, the time-course of receptor occupancy (i.e., mAb-target binding) to support the design and interpretation of preclinical pharmacokinetic-pharmacodynamic investigations in non-human primates.

Across-Species Scaling of Monoclonal Antibody Pharmacokinetics Using a Minimal PBPK Model

PURPOSE

To examine the across-species scalability of monoclonal antibody (mAb) pharmacokinetics (PK) and assess similarities in tissue distribution across species using a recently developed minimal PBPK (mPBPK) model.

METHODS

Twelve sets of antibody PK data from various species were obtained from the literature, which were jointly and individually analyzed. In joint analysis, vascular reflection coefficients for tissues with either tight (σ 1 ) or leaky endothelium (σ 2 ) were assumed consistent across species with systemic clearance allometrically scaled (CL = a∙BW (b) ). Four parameters (σ 1 , σ 2 , a, and b) were estimated in the joint analysis. In addition, the PK from each species was individually analyzed to assess species similarities in tissue distribution.

RESULTS

Twelve mAb PK profiles were well-captured by the mPBPK model in the joint analysis. The estimated σ 1 ranged 0.690 to 0.999 with an average of 0.908; and σ 2 ranged 0.258 to 0.841 with an average of 0.579. Clearance was reasonably scaled and b ranged 0.695 to 1.27 averaging 0.91. Predictions of plasma concentrations for erlizumab and canakinumab in humans using parameters obtained from fitting animal data were consistent with actual measurements.

CONCLUSIONS

Therapeutic mAbs given IV usually exhibit biexponential kinetics with their distribution properties best captured using physiological concepts. The mPBPK modeling approach may facilitate efforts in translating antibody distribution and overall PK across species.

Tools for predicting the PK/PD of therapeutic proteins

INTRODUCTION

Assessments of the pharmacokinetic/pharmacodynamic (PK/PD) characteristics are an integral part in the development of novel therapeutic agents. Compared with traditional small molecule drugs, therapeutic proteins possess many distinct PK/PD features that necessitate the application of modified or separate approaches for assessing their PK/PD relationships.

AREAS COVERED

In this review, the authors discuss tools that are utilized to describe and predict the PK/PD features of therapeutic proteins and that are valuable additions in the armamentarium of drug development approaches to facilitate and accelerate their successful preclinical and clinical development.

EXPERT OPINION

A variety of state-of-the-art PK/PD tools is currently being applied and has been adjusted to support the development of proteins as therapeutics, including allometric scaling approaches, target-mediated disposition models, first-in-man dose calculations, physiologically based PK models and empirical and semi-mechanistic PK/PD modeling. With the advent of the next generation of biologics including bioengineered antibody constructs being developed, these tools will need to be further refined and adapted to ensure their applicability and successful facilitation of the drug development process for these novel scaffolds.

A PBPK workflow for first-in-human dose selection of a subcutaneously administered pegylated peptide

Predicting the pharmacokinetic (PK) time course of a subcutaneously (SC) administered novel therapeutic protein using in silico approaches offers an opportunity to streamline the drug development process by facilitating selection of starting and target doses in initial human trials. Herein, we propose a workflow for predicting the human exposure time course following SC administration. Leveraging knowledge obtained following both intravenous and SC administration in monkeys, this workflow employs the development of a whole body physiologically-based pharmacokinetic (PBPK) model incorporating vascular circulation, lymphatic uptake and both renal and non-specific clearance mechanisms to predict the PK of a novel pegylated peptide. Optimization of the model was initially performed in monkeys, after which the model was scaled up to human proportion. Inclusion of a SC depot compartment allowed for precise simulation of the SC time course in monkeys. Simulated human exposure after SC administration was within approximately 20 % of the observed values and successfully predicted the time course of two subsequent dosing levels. This workflow represents one of the first publications of a PBPK workflow to predict the time course of a SC administered therapeutic protein based off of a single, non-human primate species and shows promise in facilitating the dose selection in first-in-human dose escalation studies for novel protein therapeutics.