Computer-assembled cross-species/cross-modalities two-pore physiologically based pharmacokinetic model for biologics in mice and rats

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.

Biodistribution of Drug/ADA Complexes: The Impact of Immune Complex Formation on Antibody Distribution

The clinical use of therapeutic monoclonal antibodies (mAbs) for the treatment of cancer, inflammation, and other indications has been successfully established. A critical aspect of drug-antibody pharmacokinetics is immunogenicity, which triggers an immune response via an anti-drug antibody (ADA) and forms drug/ADA immune complexes (ICs). As a consequence, there may be a reduced efficacy upon neutralization by ADA or an accelerated drug clearance. It is therefore important to understand immunogenicity in biological therapies. A drug-like immunoglobulin G (IgG) was radiolabeled with tritium, and ICs were formed using polyclonal ADA, directed against the complementary-determining region of the drug-IgG, to investigate in vivo biodistribution in rodents. It was demonstrated that 65% of the radioactive IC dose was excreted within the first 24 h, compared with only 6% in the control group who received non-complexed 3H-drug. Autoradiographic imaging at the early time point indicated a deposition of immune complexes in the liver, lung, and spleen indicated by an increased radioactivity signal. A biodistribution study confirmed the results and revealed further insights regarding excretion and plasma profiles. It is assumed that the immune complexes are readily taken up by the reticuloendothelial system. The ICs are degraded proteolytically, and the released radioactively labeled amino acids are redistributed throughout the body. These are mainly renally excreted as indicated by urine measurements or incorporated into protein synthesis. These biodistribution studies using tritium-labeled immune complexes described in this article underline the importance of understanding the immunogenicity induced by therapeutic proteins and the resulting influence on biological behavior.

Impact of tissue penetration and albumin binding on design of T cell targeted bispecific agents

Bispecific agents are a rapidly growing class of cancer therapeutics, and immune targeted bispecific agents have the potential to expand functionality well beyond monoclonal antibody agents. Humabodies⁎ are fully human single domain antibodies that can be linked in a modular fashion to form multispecific therapeutics. However, the effect of heterogeneous delivery on the efficacy of crosslinking bispecific agents is currently unclear. In this work, we utilize a PSMA-CD137 Humabody with an albumin binding half-life extension (HLE) domain to determine the impact of tissue penetration on T cell activating bispecific agents. Using heterotypic spheroids, we demonstrate that increased tissue penetration results in higher T cell activation at sub-saturating concentrations. Next, we tested the effect of two different albumin binding moieties on tissue distribution using albumin-specific HLE domains with varying affinities for albumin and a non-specific lipophilic dye. The results show that a specific binding mechanism to albumin does not influence tissue penetration, but a non-specific mechanism reduced both spheroid uptake and distribution in the presence of albumin. These results highlight the potential importance of tissue penetration on bispecific agent efficacy and describe how the design parameters including albumin-binding domains can be selected to maximize the efficacy of bispecific agents.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging

The main objective of this manuscript was to validate the ability of the monoclonal antibody physiologically-based pharmacokinetic (PBPK) model to predict tissue concentrations of antibodies in the human. To accomplish this goal, preclinical and clinical tissue distribution and positron emission tomography imaging data generated using zirconium-89 (89Zr) labeled antibodies were obtained from the literature. First, our previously published translational PBPK model for antibodies was expanded to describe the whole-body biodistribution of 89Zr labeled antibody and the free 89Zr, as well as residualization of free 89Zr. Subsequently, the model was optimized using mouse biodistribution data, where it was observed that free 89Zr mainly residualizes in the bone and the extent of antibody distribution in certain tissues (e.g., liver and spleen) may be altered by labeling with 89Zr. The mouse PBPK model was scaled to rat, monkey, and human by simply changing the physiological parameters, and a priori simulations performed by the model were compared with the observed PK data. It was found that model predicted antibody PK in majority of the tissues in all the species superimposed over the observed data, and the model was also able to predict the PK of antibody in human tissues reasonably well. As such, the work presented here provides unprecedented evaluation of the antibody PPBK model for its ability to predict tissue PK of antibodies in the clinic. This model can be used for preclinical-to-clinical translation of antibodies and for prediction of antibody concentrations at the site-of-action in the clinic.

Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products

Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).

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.

Mechanism-Based Pharmacokinetic Modeling of Absorption and Disposition of a Deferoxamine-Based Nanochelator in Rats

Deferoxamine (DFO) is an effective FDA-approved iron chelator. However, its use is considerably limited by off-target toxicities and an extremely cumbersome dose regimen with daily infusions. The recent development of a deferoxamine-based nanochelator (DFO-NP) with selective renal excretion has shown promise in ameliorating animal models of iron overload with a substantially improved safety profile. To further the preclinical development of this promising nanochelator and to inform on the feasibility of clinical development, it is necessary to fully characterize the dose and administration-route-dependent pharmacokinetics and to develop predictive pharmacokinetic (PK) models describing absorption and disposition. Herein, we have evaluated the absorption, distribution, and elimination of DFO-NPs after intravenous and subcutaneous (SC) injection at therapeutically relevant doses in Sprague Dawley rats. We also characterized compartment-based model structures and identified model-based parameters to quantitatively describe the PK of DFO-NPs. Our modeling efforts confirmed that disposition could be described using a three-compartment mamillary model with elimination and saturable reabsorption both occurring from the third compartment. We also determined that absorption was nonlinear and best described by parallel saturable and first-order processes. Finally, we characterized a novel pathway for saturable SC absorption of an ultrasmall organic nanoparticle directly into the systemic circulation, which offers a novel strategy for improving drug exposure for nanotherapeutics.

In vivo biodistribution and pharmacokinetics of sotrovimab, a SARS-CoV-2 monoclonal antibody, in healthy cynomolgus monkeys

PURPOSE

Sotrovimab (VIR-7831), a human IgG1κ monoclonal antibody (mAb), binds to a conserved epitope on the SARS-CoV-2 spike protein receptor binding domain (RBD). The Fc region of VIR-7831 contains an LS modification to promote neonatal Fc receptor (FcRn)-mediated recycling and extend its serum half-life. Here, we aimed to evaluate the impact of the LS modification on tissue biodistribution, by comparing VIR-7831 to its non-LS-modified equivalent, VIR-7831-WT, in cynomolgus monkeys.

METHODS

⁸⁹Zr-based PET/CT imaging of VIR-7831 and VIR-7831-WT was performed up to 14 days post injection. All major organs were analyzed for absolute concentration as well as tissue:blood ratios, with the focus on the respiratory tract, and a physiologically based pharmacokinetics (PBPK) model was used to evaluate the tissue biodistribution kinetics. Radiomics features were also extracted from the PET images and SUV values.

RESULTS

SUV_mean uptake in the pulmonary bronchi for ⁸⁹Zr-VIR-7831 was statistically higher than for ⁸⁹Zr-VIR-7831-WT at days 6 (3.43 ± 0.55 and 2.59 ± 0.38, respectively) and 10 (2.66 ± 0.32 and 2.15 ± 0.18, respectively), while the reverse was observed in the liver at days 6 (5.14 ± 0.80 and 8.63 ± 0.89, respectively), 10 (4.52 ± 0.59 and 7.73 ± 0.66, respectively), and 14 (4.95 ± 0.65 and 7.94 ± 0.54, respectively). Though the calculated terminal half-life was 21.3 ± 3.0 days for VIR-7831 and 16.5 ± 1.1 days for VIR-7831-WT, no consistent differences were observed in the tissue:blood ratios between the antibodies except in the liver. While the lung:blood SUV_mean uptake ratio for both mAbs was 0.25 on day 3, the PBPK model predicted the total lung tissue and the interstitial space to serum ratio to be 0.31 and 0.55, respectively. Radiomics analysis showed VIR-7831 had mean-centralized PET SUV distribution in the lung and liver, indicating more uniform uptake than VIR-7831-WT.

CONCLUSION

The half-life extended VIR-7831 remained in circulation longer than VIR-7831-WT, consistent with enhanced FcRn binding, while the tissue:blood concentration ratios in most tissues for both drugs remained statistically indistinguishable throughout the course of the experiment. In the bronchiolar region, a higher concentration of ⁸⁹Zr-VIR-7831 was detected. The data also allow unparalleled insight into tissue distribution and elimination kinetics of mAbs that can guide future biologic drug discovery efforts, while the residualizing nature of the ⁸⁹Zr label sheds light on the sites of antibody catabolism.

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

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

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

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

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

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

Diagnostic biomarker kinetics: how brain-derived biomarkers distribute through the human body, and how this affects their diagnostic significance: the case of S100B

Blood biomarkers of neurological diseases are often employed to rule out or confirm the presence of significant intracranial or cerebrovascular pathology or for the differential diagnosis of conditions with similar presentations (e.g., hemorrhagic vs. embolic stroke). More widespread utilization of biomarkers related to brain health is hampered by our incomplete understanding of the kinetic properties, release patterns, and excretion of molecules derived from the brain. This is, in particular, true for S100B, an astrocyte-derived protein released across the blood–brain barrier (BBB). We developed an open-source pharmacokinetic computer model that allows investigations of biomarker’s movement across the body, the sources of biomarker’s release, and its elimination. This model was derived from a general in silico model of drug pharmacokinetics adapted for protein biomarkers. We improved the model’s predictive value by adding realistic blood flow values, organ levels of S100B, lymphatic and glymphatic circulation, and glomerular filtration for excretion in urine. Three key variables control biomarker levels in blood or saliva: blood–brain barrier permeability, the S100B partition into peripheral organs, and the cellular levels of S100B in astrocytes. A small contribution to steady-state levels of glymphatic drainage was also observed; this mechanism also contributed to the uptake of organs of circulating S100B. This open-source model can also mimic the kinetic behavior of other markers, such as GFAP or NF-L. Our results show that S100B, after uptake by various organs from the systemic circulation, can be released back into systemic fluids at levels that do not significantly affect the clinical significance of venous blood or salivary levels after an episode of BBB disruption.

Application of quantitative protein mass spectrometric data in the early predictive analysis of target engagement by monoclonal antibodies

Model‐informed drug discovery is endorsed by the US Food and Drug Administration (FDA) to improve the flow of medicines from bench to bedside. In the case of monoclonal antibodies, this necessitates taking into account not only the pharmacokinetic (PK) properties of the drug, but also the tissue distribution, concentration, and turnover of the target to guide dose and affinity selection, as well as serve as a link to downstream pharmacology. Relevant information (e.g., tissue proteomic data from quantitative mass spectrometry), is increasingly available from public domain data repositories, although not necessarily in the form that is directly usable for the purpose of quantitative, predictive, and mechanistic PK/pharmacodynamic (PD) modeling based on molarity or similar frameworks instead. Using secreted plasma protein concentrations measured both by immunochemical methods and mass spectrometry, we addressed this gap and derived an optimized nonlinear empirical function that establishes the correlation between the two data sets and validated the approach taken using a wider data set of all proteins found in plasma. In addition, we present a semimechanistic framework for the plasma half‐life of soluble proteins where clearance is expressed as a nonlinear function of the molecular weight of the protein. Finally, we apply the approach to two established therapeutic antibody targets: complement factor C5 and PCSK9 to demonstrate how the described framework can be applied to predictive PK/PD modeling.

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.

A Two-Pore Physiologically Based Pharmacokinetic Model to Predict Subcutaneously Administered Different-Size Antibody/Antibody Fragments

Quantitative modeling of the subcutaneous absorption processes of protein therapeutics is challenging. Here we have proposed a "two-pore" PBPK model that is able to simultaneously characterize plasma PK of different-size protein therapeutics in mice. The skin compartment is evolved to mechanistically account for the absorption pathways through lymph and blood capillaries, as well as local degradation at the SC injection site. The model is developed using in-house plasma PK data generated following subcutaneous administration of 6 different-size protein therapeutics (13-150 kDa) in mice. The model was able to capture plasma PK of all molecules following intravenous and subcutaneous administration relatively well. From the observed plasma PK profiles, as well as from the model simulation result, several important PK descriptors were found to be dependent on protein size for FcRn nonbinding molecules. A positive correlation was found between T_max and protein size. A "U" shape relationship was found between C_max and protein size. Negative correlations were observed between bioavailability (F) and local degradation rate (k_deg,SC), and F and protein size. Pathway analysis of the model was conducted for the subcutaneous absorption process, and continuous relationships were established between the percentage of absorption through lymphatic and vascular pathways and protein size. This PBPK model could serve as a platform for the development of different-size protein therapeutics and will be scaled up to humans for translational studies in the future.

A pilot study evaluating GSK1070806 inhibition of interleukin-18 in renal transplant delayed graft function

INTRODUCTION

Delayed graft function (DGF) following renal transplantation is a manifestation of acute kidney injury (AKI) leading to poor long-term outcome. Current treatments have limited effectiveness in preventing DGF. Interleukin-18 (IL18), a biomarker of AKI, induces interferon-γ expression and immune activation. GSK1070806, an anti-IL18 monoclonal antibody, neutralizes activated (mature) IL18 released from damaged cells following inflammasome activation. This phase IIa, single-arm trial assessed the effect of a single dose of GSK1070806 on DGF occurrence post donation after circulatory death (DCD) kidney transplantation.

METHODS

The 3 mg/kg intravenous dose was selected based on prior studies and physiologically based pharmacokinetic (PBPK) modeling, indicating the high likelihood of a rapid and high level of IL18 target engagement when administered prior to kidney allograft reperfusion. Utilization of a Bayesian sequential design with a background standard-of-care DGF rate of 50% based on literature, and confirmed via extensive registry data analyses, enabled a statistical efficacy assessment with a minimal sample size. The primary endpoint was DGF frequency, defined as dialysis requirement ≤7 days post transplantation (except for hyperkalemia). Secondary endpoints included safety, pharmacokinetics and pharmacodynamic biomarkers.

RESULTS

GSK1070806 administration was associated with IL18-GSK1070806 complex detection and increased total serum IL18 levels due to IL18 half-life prolongation induced by GSK1070806 binding. Interferon-γ-induced chemokine levels declined or remained unchanged in most patients. Although the study was concluded prior to the Bayesian-defined stopping point, 4/7 enrolled patients (57%) had DGF, exceeding the 50% standard-of-care rate, and an additional two patients, although not reaching the protocol-defined DGF definition, demonstrated poor graft function. Six of seven patients experienced serious adverse events (SAEs), including two treatment-related SAEs.

CONCLUSION

Overall, using a Bayesian design and extensive PBPK dose modeling with only a small sample size, it was deemed unlikely that GSK1070806 would be efficacious in preventing DGF in the enrolled DCD transplant population.

TRIAL REGISTRATION

NCT02723786.

Cross-species/cross-modality physiologically based pharmacokinetics for biologics: 89Zr-labelled albumin-binding domain antibody GSK3128349 in humans

Two-pore physiologically-based pharmacokinetics (PBPK) for biologics describes the tissue distribution and elimination kinetics of soluble proteins as a function of their hydrodynamic radius and the physiological properties of the organs. Whilst many studies have been performed in rodents to parameterize the PBPK framework in terms of organ-specific lymph flow rates, similar validation in humans has been limited. This is mainly due to the paucity of the tissue distribution time course data for biologics that is not distorted by target-related binding. Here, we demonstrate that a PBPK model based on rodent data provided good to satisfactory extrapolation to the tissue distribution time course of ⁸⁹Zr-labeled albumin-binding domain antibody (AlbudAb™) GSK3128349 in healthy human volunteers, including correct prediction of albumin-like plasma half-life, volume of distribution, and extravasation half-life. The AlbudAb™ used only binds albumin, and hence it also provides information about the tissue distribution kinetics and turnover of that ubiquitous and multifunctional plasma protein.