Monoclonal antibody disposition: a simplified PBPK model and its implications for the derivation and interpretation of classical compartment models

Investigation of simplified physiologically-based pharmacokinetic models in rat and human

Whole-body physiologically-based pharmacokinetic (PBPK) models have many applications in drug research and development. It is often necessary to inform these models with animal or clinical data, updating model parameters, and making the model more predictive for future applications. This provides an opportunity and a challenge given the large number of parameters of such models. The aim of this work was to propose new mechanistic model structures with reduced complexity allowing for parameter optimization. These models were evaluated for their ability to estimate realistic values for unbound tissue to plasma partition coefficients (Kpu) and simulate observed pharmacokinetic (PK) data. Two approaches are presented: using either established kinetic lumping methods based on tissue time constants (drug-dependent) or a novel clustering analysis to identify tissues sharing common Kpu values or Kpu scalars based on similarities of tissue composition (drug-independent). PBPK models derived from these approaches were assessed using PK data of diazepam in rats and humans. Although the clustering analysis produced minor differences in tissue grouping depending on the method used, two larger groups of tissues emerged. One including the kidneys, liver, spleen, gut, heart, and lungs, and another including bone, brain, muscle, and pancreas whereas adipose and skin were generally considered distinct. Overall, a subdivision into four tissue groups appeared most physiologically relevant in terms of tissue composition. Several models were found to have similar abilities to describe diazepam i.v. data as empirical models. Comparability of estimated Kpus to experimental Kpu values for diazepam was one criterion for selecting the appropriate PK model structure.

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.

Preclinical InVivo Data Integrated in a Modeling Network Informs a Refined Clinical Strategy for a CD3 T-Cell Bispecific in Combination with Anti-PD-L1

TYRP1-TCB is a CD3 T-cell bispecific (CD3-TCB) antibody for the treatment of advanced melanoma. A tumor growth inhibition (TGI) model was developed using mouse xenograft data with TYRP1-TCB monotherapy or TYRP1-TCB plus anti-PD-L1 combination. The model was translated to humans to inform a refined clinical strategy. From xenograft mouse data, we estimated an EC₅₀ of 0.345 mg/L for TYRP1-TCB, close to what was observed in vitro using the same tumor cell line. The model showed that, though increasing the dose of TYRP1-TCB in monotherapy delays the time to tumor regrowth and promotes higher tumor cell killing, it also induces a faster rate of tumor regrowth. Combination with anti-PD-L1 extended the time to tumor regrowth by 25% while also decreasing the tumor regrowth rate by 69% compared to the same dose of TYRP1-TCB alone. The model translation to humans predicts that if patients' tumors were scanned every 6 weeks, only 46% of the monotherapy responders would be detected even at a TYRP1-TCB dose resulting in exposures above the EC₉₀. However, combination of TYRP1-TCB and anti-PD-L1 in the clinic is predicted to more than double the overall response rate (ORR), duration of response (DoR) and progression-free survival (PFS) compared to TYRP1-TCB monotherapy. As a result, it is highly recommended to consider development of CD3-TCBs as part of a combination therapy from the outset, without the need to escalate the CD3-TCB up to the Maximum Tolerated Dose (MTD) in monotherapy and without gating the combination only on RECIST-derived efficacy metrics.

Investigating brain uptake of a non-targeting monoclonal antibody after intravenous and intracerebroventricular administration

Monoclonal antibodies play an important role in the treatment of various diseases. However, the development of these drugs against neurological disorders where the drug target is located in the brain is challenging and requires a good understanding of the local drug concentration in the brain. In this original research, we investigated the systemic and local pharmacokinetics in the brain of healthy rats after either intravenous (IV) or intracerebroventricular (ICV) administration of EGFRvIII-T-Cell bispecific (TCB), a bispecific monoclonal antibody. We established an experimental protocol that allows serial sampling in serum, cerebrospinal fluid (CSF) and interstitial fluid (ISF) of the prefrontal cortex in freely moving rats. For detection of drug concentration in ISF, a push-pull microdialysis technique with large pore membranes was applied. Brain uptake into CSF and ISF was characterized and quantified with a reduced brain physiologically-based pharmacokinetic model. The model allowed us to interpret the pharmacokinetic processes of brain uptake after different routes of administration. The proposed model capturing the pharmacokinetics in serum, CSF and ISF of the prefrontal cortex suggests a barrier function between the CSF and ISF that impedes free antibody transfer. This finding suggests that ICV administration may not be better suited to reach higher local drug exposure as compared to IV administration. The model enabled us to quantify the relative contribution of the blood-brain barrier (BBB) and Blood-CSF-Barrier to the uptake into the interstitial fluid of the brain. In addition, we compared the brain uptake of three monoclonal antibodies after IV dosing. In summary, the presented approach can be applied to profile compounds based on their relative uptake in the brain and provides quantitative insights into which pathways are contributing to the net exposure in the brain.

Localization of drug biodistribution in a 3D-bioengineered subcutaneous neovascularized microenvironment

Local immunomodulation has shown the potential to control the immune response in a site-specific manner for wound healing, cancer, allergy, and cell transplantation, thus abrogating adverse effects associated with systemic administration of immunotherapeutics. Localized immunomodulation requires confining the biodistribution of immunotherapeutics on-site for maximal immune control and minimal systemic drug exposure. To this end, we developed a 3D-printed subcutaneous implant termed 'NICHE', consisting of a bioengineered vascularized microenvironment enabled by sustained drug delivery on-site. The NICHE was designed as a platform technology for investigating local immunomodulation in the context of cell therapeutics and cancer vaccines. Here we studied the ability of the NICHE to localize the PK and biodistribution of different model immunomodulatory agents in vivo. For this, we first performed a mechanistic evaluation of the microenvironment generated within and surrounding the NICHE, with emphasis on the parameters related to molecular transport. Second, we longitudinally studied the biodistribution of ovalbumin, cytotoxic T lymphocyte-associated antigen-4-Ig (CTLA4Ig), and IgG delivered locally via NICHE over 30 days. Third, we used our findings to develop a physiologically-based pharmacokinetic (PBPK) model. Despite dense and mature vascularization within and surrounding the NICHE, we showed sustained orders of magnitude higher molecular drug concentrations within its microenvironment as compared to systemic circulation and major organs. Further, the PBPK model was able to recapitulate the biodistribution of the 3 molecules with high accuracy (r ​> ​0.98). Overall, the NICHE and the PBPK model represent an adaptable platform for the investigation of local immunomodulation strategies for a wide range of biomedical applications.

Pharmacokinetics and Pharmacodynamics of T-Cell Bispecifics in the Tumour Interstitial Fluid

The goal of this study is to investigate the pharmacokinetics in plasma and tumour interstitial fluid of two T-cell bispecifics (TCBs) with different binding affinities to the tumour target and to assess the subsequent cytokine release in a tumour-bearing humanised mouse model. Pharmacokinetics (PK) as well as cytokine data were collected in humanised mice after iv injection of cibisatamab and CEACAM5-TCB which are binding with different binding affinities to the tumour antigen carcinoembryonic antigen (CEA). The PK data were modelled and coupled to a previously published physiologically based PK model. Corresponding cytokine release profiles were compared to in vitro data. The PK model provided a good fit to the data and precise estimation of key PK parameters. High tumour interstitial concentrations were observed for both TCBs, influenced by their respective target binding affinities. In conclusion, we developed a tailored experimental method to measure PK and cytokine release in plasma and at the site of drug action, namely in the tumour. Integrating those data into a mathematical model enabled to investigate the impact of target affinity on tumour accumulation and can have implications for the PKPD assessment of the therapeutic antibodies.

Cytokine Release Syndrome By T-cell-Redirecting Therapies: Can We Predict and Modulate Patient Risk?

T-cell-redirecting therapies are promising new therapeutic options in the field of cancer immunotherapy, but the development of these modalities is challenging. A commonly observed adverse event in patients treated with T-cell-redirecting therapies is cytokine release syndrome (CRS). Its clinical manifestation is a burden on patients, and continues to be a big hurdle in the clinical development of this class of therapeutics. We review different T-cell-redirecting therapies, discuss key factors related to cytokine release and potentially leading to CRS, and present clinical mitigation strategies applied for those modalities. We propose to dissect those risk factors into drug-target-disease-related factors and individual patient risk factors. Aiming to optimize the therapeutic intervention of these modalities, we illustrate how the knowledge on drug-target-disease-related factors, such as target expression, binding affinity, and target accessibility, can be leveraged in a model-based framework and highlight with case examples how modeling and simulation is applied to guide drug discovery and development. We draw attention to the current gaps in predicting the individual patient's risk towards a high-grade CRS, which requires further considerations of risk factors related, but not limited to, the patient's demographics, genetics, underlying pathologies, treatment history, and environmental exposures. The drug-target-disease-related factors together with the individual patient's risk factors can be regarded as the patient's propensity for developing CRS in response to therapy. As an outlook, we suggest implementing a risk scoring system combined with mechanistic modeling to enable the prediction of an individual patient's risk of CRS for a given therapeutic intervention.

Improving priors for human monoclonal antibody linear pharmacokinetic parameters by using half-lives from non-human primates

Obtaining a good prior for the linear pharmacokinetics of new monoclonal antibodies (mAbs) would be an advantage not only for designing first-in-human (FIH) studies but also for stabilizing fitting of data with non-linear target-mediated disposition models. We estimated the pharmacokinetics from FIH studies for five mAbs using a two-compartment model, both separately and together, using a simple pool, a third hierarchical level of random effects for between mAb differences and non-human-primate half-lives as a predictor covariate for said differences. There was good agreement between compounds for the rapidly accessible central volume of 2.9 L (70 kg human), but clearances and peripheral volumes differed with terminal half-lives ranging from 15 to 28 days. The simple pool of human studies gave inter-individual variability estimates of 32% coefficient of variation (CV) for clearance and 33% CV for peripheral volume, larger than for separate fits (13-26% CV and 15-35% CV for clearance and volume respectively). Using third level hierarchical random effects gave inter-individual variability estimates close to those of separate fits (24% and 16% CV respectively). The between-mAb differences became predictable if non-human primate body weight scaled terminal half-life estimates were included as covariates on clearance and peripheral volume. In conclusion, ignoring inter-mAb variation leads to inflated estimates of inter-individual variability and unrealistic simulations for FIH studies. However, by using 70 kg body weight scaled terminal half-life estimates from non-human primates one can account for between-mAb differences and provide non-inflated priors for the linear pharmacokinetic parameters of new mAbs.

Influence of Antigen Mass on the Pharmacokinetics of Therapeutic Antibodies in Humans

Therapeutic antibodies are increasingly used to treat various diseases, including neoplasms and chronic inflammatory diseases. Antibodies exhibit complex pharmacokinetic properties, notably owing to the influence of antigen mass, i.e. the amount of antigenic targets to which the monoclonal antibody binds specifically. This review focuses on the influence of antigen mass on the pharmacokinetics of therapeutic antibodies quantified by pharmacokinetic modelling in humans. Out of 159 pharmacokinetic studies, 85 reported an influence of antigen mass. This influence led to non-linear elimination decay in 50 publications, which was described using target-mediated drug disposition or derived models, as quasi-steady-state, irreversible binding and Michaelis-Menten models. In 35 publications, the pharmacokinetics was apparently linear and the influence of antigen mass was described as a covariate of pharmacokinetic parameters. If some reported covariates, such as the circulating antigen level or tumour size, are likely to be correlated to antigen mass, others, such as disease activity or disease type, may contain little information on the amount of antigenic targets. In some cases, antigen targets exist in different forms, notably in the circulation and expressed at the cell surface. The influence of antigen mass should be soundly described during the early clinical phases of drug development. To maximise therapeutic efficacy, sufficient antibody doses should be administered to ensure the saturation of antigen targets by therapeutic antibodies in all patients. If necessary, antigen mass should be taken into account in routine clinical practice.

[Pharmacokinetic variability of therapeutic antibodies]

Therapeutic antibodies have been increasingly used for the treatment of various diseases, including cancers and chronic inflammatory diseases. The pharmacokinetic interindividual variability of mAbs is large and influences, at least in part, the clinical response to antibody treatment. This variability is explained by a number of individual sources of variability, which are reviewed here. Some of them are major because they are frequently reported to greatly influence the interindividual variability; notably, increased body size, the presence of anti-drug antibodies, and high antigen mass are associated with decreased antibody concentrations. Other individual sources of variability are of less critical importance. They include sex, age, co-treatments, or genetic polymorphisms of IgG Fc receptors (FcgRs). The interindividual variability of antibody pharmacokinetics should be soundly described in order to design optimal dosing strategy.

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

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

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.

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

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

Nanotracing and cavity-ring down spectroscopy: A new ultrasensitive approach in large molecule drug disposition studies

New therapeutic biological entities such as bispecific antibodies targeting tissue or specific cell populations form an increasingly important part of the drug development portfolio. However, these biopharmaceutical agents bear the risk of extensive target-mediated drug disposition or atypical pharmacokinetic properties as compared to canonical antibodies. Pharmacokinetics and bio-distribution studies become therefore more and more important during lead optimization. Biologics present, however, greater analytical challenges than small molecule drugs due to the mass and selectivity limitation of mass spectrometry and ligand-binding assay, respectively. Radiocarbon (¹⁴C) and its detection methods, such as the emerging ¹⁴C cavity ring down spectroscopy (CRDS), thus can play an important role in the large molecule quantitation where a ¹⁴C-tag is covalently bound through a stable linker. CRDS has the advantage of a simplified sample preparation and introduction system as compared to accelerator mass spectrometry (AMS) and can be accommodated within an ordinary research laboratory. In this study, we report on the labeling of an anti-IL17 IgG1 model antibody with ¹⁴C propionate tag and its detection by CRDS using it as nanotracer (2.1 nCi or 77.7 Bq blended with the therapeutic dose) in a pharmacokinetics study in a preclinical species. We compare these data to data generated by AMS in parallel processed samples. The derived concentration time profiles for anti-IL17 by CRDS were in concordance with the ones derived by AMS and γ-counting of an ¹²⁵I-labeled anti-IL17 radiotracer and were well described by a 2-compartment population pharmacokinetic model. In addition, antibody tissue distribution coefficients for anti-IL17 were determined by CRDS, which proved to be a direct and sensitive measurement of the extravascular tissue concentration of the antibody when tissue perfusion was applied. Thus, this proof-of-concept study demonstrates that trace ¹⁴C-radiolabels and CRDS are an ultrasensitive approach in (pre)clinical pharmacokinetics and bio-distribution studies of new therapeutic entities.

A new pharmacokinetic model for 90Y-ibritumomab tiuxetan based on 3-dimensional dosimetry

Monoclonal antibodies (mAbs) are key components in several therapies for cancer and inflammatory diseases but current knowledge of their clinical pharmacokinetics and distribution in human tissues remains incomplete. Consequently, optimal dosing and scheduling in clinics are affected. With sequential radiolabeled mAb-based imaging, radiation dosing in tissues/organs can be calculated to provide a better assessment of mAb concentrations in tissues. This is the first pharmacokinetic model of ⁹⁰Y-Ibritumomab tiuxetan (⁹⁰Y-IT) in humans to be described, based on three-dimensional (3D) dosimetry using single-photon emission computed-tomography coupled with computed-tomography. 19 patients with follicular lymphoma were treated initially with ⁹⁰Y-IT in the FIZZ trial. Based on a compartmental approach individualising the vascular compartment within studied organs, this study proposes a reliable pharmacokinetic (PK) five-compartment model replacing the currently used two-compartment model and constitutes a new direction for further research. This model provides exchange constants between the different tissues, Area Under the Curve of ¹¹¹In-IT in blood (AUC) and Mean Residence Time (MRT) that have not been reported so far for IT. Finally, the elimination process appears to occur in a compartment other than the liver or the spleen and suggests the metabolism of mAbs may take place mainly on the vascular compartment level.

Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance

Quantitative Systems Pharmacology (QSP) models provide a means of integrating knowledge into a quantitative framework and, ideally, this integration leads to a better understanding of biology and better predictions of new experiments and clinical trials. In practice, these goals may be compromised by model complexity and uncertainty. To address these problems, we recommend that the predictive performance of QSP models be assessed through comparison with simpler models developed specifically for this purpose.

Hematopoietic cells as site of first-pass catabolism after subcutaneous dosing and contributors to systemic clearance of a monoclonal antibody in mice

The neonatal Fc receptor (FcRn) has been demonstrated to contribute to a high bioavailability of monoclonal antibodies (mAbs). In this study, we explored the cellular sites of FcRn-mediated protection after subcutaneous (SC) and intravenous (IV) administration. SC absorption and IV disposition kinetics of a mAb were studied in hFcRn transgenic (Tg) bone marrow chimeric mice in which hFcRn was restricted to radioresistant cells or hematopoietic cells. SC bioavailabilities close to 90% were observed in hFcRn Tg mice and chimeric mice with hFcRn expression in hematopoietic cells, whereas SC bioavailabilities were markedly lower when FcRn was missing in hematopoietic cells. Our study demonstrates: 1) FcRn in radiosensitive hematopoietic cells is required for high SC bioavailability, indicating first-pass catabolism after SC administration by hematopoietic cells; 2) FcRn-mediated transcytosis or recycling by radioresistent cells is not required for high SC bioavailability; and 3) after IV administration hematopoietic and radioresistent cells contribute about equally to clearance of the mAb. A pharmacokinetic model was devised to describe a mixed elimination via radioresistent and hematopoietic cells from vascular and extravascular compartments, respectively. Overall, the study indicates a relevant role of hematopoietic cells for first-pass clearance of mAbs after SC administration and confirms their role in the overall clearance of mAbs.

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

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.

Impact of altered endogenous IgG on unspecific mAb clearance

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

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

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

Clinical Pharmacokinetics and Pharmacodynamics of Biologic Therapeutics for Treatment of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease with potentially severe clinical manifestation that mainly affects women of child-bearing age. Patients who do not respond to standard-of-care therapies, such as corticosteroids and immunosuppressants, require biologic therapeutics that specifically target a single or multiple SLE pathogenesis pathways. This review summarizes the clinical pharmacokinetic and pharmacodynamic characteristics of biologic agents that are approved, used off-label, or in the active pipeline of drug development for SLE patients. Depending on the type of target, the interacting biologics may exhibit linear (non-specific) or non-linear (target-mediated) disposition profiles, with terminal half-lives varying from approximately 1 week to 1 month. Biologics given by subcutaneous administration, which offers dosing flexibility over intravenous administration, demonstrated a relatively slow absorption with a time to maximum concentration of approximately 1 day to 2 weeks and a variable bioavailability of 30-82 %. The population pharmacokinetics of monoclonal antibodies were best described by a two-compartment model with central clearance and steady-state volume of distribution ranging from 0.176 to 0.215 L/day and 3.60-5.29 L, respectively. The between-subject variability in pharmacokinetic parameters were moderate (20-79 %) and could be partially explained by body size. The development of linked pharmacokinetic-pharmacodynamic models incorporating SLE disease biomarkers are an attractive strategy for use in dosing regimen simulation and optimization. The relationship between efficacy/adverse events and biologic concentration should be evaluated to improve clinical trial outcomes, especially for biologics in the advanced phase of drug development. New strategies, such as model-based precision dosing dashboards, could be utilized to incorporate information collected from therapeutic drug monitoring into pharmacokinetic/pharmacodynamic models to enable individualized dosing in real time.

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.

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.

Clinical Pharmacokinetics and Pharmacodynamics of Monoclonal Antibodies Approved to Treat Rheumatoid Arthritis

Monoclonal antibodies (mAbs) are increasingly used to treat rheumatoid arthritis (RA). At present, anti-tumor necrosis factor-α drugs (infliximab, adalimumab, certolizumab pegol, and golimumab), rituximab, and tocilizumab are approved for RA treatment. This review focuses on the pharmacokinetics and pharmacodynamics of mAbs approved in RA. Being large proteins, mAbs exhibit complex pharmacokinetic and pharmacodynamic properties. In particular, owing to the interactions of mAbs with their antigenic targets, the pharmacokinetics of mAbs depends on target turnover and exhibits non-specific (linear) and target-mediated (often nonlinear) clearances. Their volume of distribution is low (3-4 L) and their elimination half-life usually ranges from 2 to 3 weeks. The inter-individual pharmacokinetic variability of mAbs is usually large and is partly explained by differences in antigenic burden or by anti-drug antibodies, which accelerate mAb elimination. The inter-individual variability of clinical response is large and influenced by the pharmacokinetics. The analysis of mAbs concentration-effect relationship relies more and more often on pharmacokinetic-pharmacodynamic modeling; these models being suitable for dosing optimization. Even if adverse effects of mAbs used in RA are well known, the relationship between mAb concentration and adverse effects is poorly documented, especially for anti-tumor necrosis factor-α mAbs. Overall, RA patients treated with mAbs should benefit from individualized dosing strategies. Because of the complexity of their pharmacokinetics and mechanisms of action, the current dosing strategy of mAbs is not based on sound knowledge. New studies are needed to assess individual dosing regimen, adjusted notably to disease activity.

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.

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.

Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model

Although advantages of physiologically based pharmacokinetic models (PBPK) are now well established, PBPK models that are linked to pharmacodynamic (PD) models to predict pharmacokinetics (PK), PD, and efficacy of monoclonal antibodies (mAbs) in humans are uncommon. The aim of this study was to develop a PD model that could be linked to a physiologically based mechanistic FcRn model to predict PK, PD, and efficacy of efalizumab. The mechanistic FcRn model for mAbs with target-mediated drug disposition within the Simcyp population-based simulator was used to simulate the pharmacokinetic profiles for three different single doses and two multiple doses of efalizumab administered to virtual Caucasian healthy volunteers. The elimination of efalizumab was modeled with both a target-mediated component (specific) and catabolism in the endosome (non-specific). This model accounted for the binding between neonatal Fc receptor (FcRn) and efalizumab (protective against elimination) and for changes in CD11a target concentration. An integrated response model was then developed to predict the changes in mean Psoriasis Area and Severity Index (PASI) scores that were measured in a clinical study as an efficacy marker for efalizumab treatment. PASI scores were approximated as continuous and following a first-order asymptotic progression model. The reported steady state asymptote (Y ss) and baseline score [Y (0)] was applied and parameter estimation was used to determine the half-life of progression (T p) of psoriasis. Results suggested that simulations using this model were able to recover the changes in PASI scores (indicating efficacy) observed during clinical studies. Simulations of both single dose and multiple doses of efalizumab concentration-time profiles as well as suppression of CD11a concentrations recovered clinical data reasonably well. It can be concluded that the developed PBPK FcRn model linked to a PD model adequately predicted PK, PD, and efficacy of efalizumab.

Simulation of monoclonal antibody pharmacokinetics in humans using a minimal physiologically based model

Compared to small chemical molecules, monoclonal antibodies and Fc-containing derivatives (mAbs) have unique pharmacokinetic behaviour characterised by relatively poor cellular permeability, minimal renal filtration, binding to FcRn, target-mediated drug disposition, and disposition via lymph. A minimal physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics of mAbs in humans was developed. Within the model, the body is divided into three physiological compartments; plasma, a single tissue compartment and lymph. The tissue compartment is further sub-divided into vascular, endothelial and interstitial spaces. The model simultaneously describes the levels of endogenous IgG and exogenous mAbs in each compartment and sub-compartment and, in particular, considers the competition of these two species for FcRn binding in the endothelial space. A Monte-Carlo sampling approach is used to simulate the concentrations of endogenous IgG and mAb in a human population. Existing targeted-mediated drug disposition (TMDD) models are coupled with the minimal PBPK model to provide a general platform for simulating the pharmacokinetics of therapeutic antibodies using primarily pre-clinical data inputs. The feasibility of utilising pre-clinical data to parameterise the model and to simulate the pharmacokinetics of adalimumab and an anti-ALK1 antibody (PF-03446962) in a population of individuals was investigated and results were compared to published clinical data.