A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn)

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.

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

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

Physiologically-based modeling to predict the clinical behavior of monoclonal antibodies directed against lymphocyte antigens

Many clinically approved and investigational monoclonal antibody (mAb)-based therapeutics are directed against proteins located in the systemic circulation, including cytokines, growth factors, lymphocyte proteins, and shed antigens. Interaction between mAb and target may lead to non-linear pharmacokinetics (PK), characterized by rapid, target-mediated elimination. Several groups have reported that determinants of target-mediated elimination could include mAb-target binding, target expression, and target turnover. Recently, we scaled a physiologically-based pharmacokinetic model for mAb disposition to man and used it to predict the non-linear PK of mAbs directed against tumor epithelial proteins. In this work, we extended the previously described model to account for the influence of lymphocyte proteins on mAb PK in man. To account for the dynamic behavior of lymphocytes in the circulation, lymphocyte cycling between blood and lymphoid organs was described using first-order transfer rate constants. Use of lymphocyte cycling and reported target turnover rates in the model allowed the accurate prediction of the pharmacokinetics and pharmacodynamics (PD) of 4 mAbs (TRX1, MTRX1011a, rituximab, daclizumab) directed against 3 lymphocyte targets (CD4, CD20, CD25). The results described here suggest that the proposed model structure may be useful in the a priori prediction of the PK/PD properties of mAbs directed against antigens in the circulation.

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.

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.

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

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

Application of a catenary PBPK model to predict the disposition of "catch and release" anti-PCSK9 antibodies

The development of 'catch and release', or pH-sensitive, monoclonal antibodies (mAb) has become of interest to groups seeking to reduce the influence of target-mediated elimination on pharmacokinetics and pharmacodynamics. In this work, a catenary physiologically-based pharmacokinetic (PBPK) model is described to predict the pharmacokinetic benefit conferred by engineering mAbs for 'catch and release' binding. Our previously published PBPK model was adapted for consideration of the production and elimination of proprotein convertase subtilisin/kexin type 9 (PCSK9) in mice, and the model was then applied to predict the pharmacokinetics of anti-PCSK9 mAb with pH-stable (J10) and pH-sensitive binding (J17). The model was able to generate reasonable predictions of both J10 and J17 plasma pharmacokinetics. For J10, mean (±standard deviation) predicted vs. observed areas under the plasma concentration curve (AUCinf) were: 217 (77.1) vs. 103nMday (1mg/kg), 1.14×10(3) (858) vs. 769nMday (3mg/kg), and 6.60×10(3) (5.58×10(3)) vs. 2.86×10(3)nMday (10mg/kg), and for J17 the values were: 838 (161) vs. 818nMday (1mg/kg), 2.30×10(3) (441) vs. 2.57×10(3)nMday (3mg/kg), and 8.42×10(3) (1.50×10(3)) vs. 9.17×10(3)nMday (10mg/kg). Further simulations with the model predicted that target turnover and the magnitude of change in the complex dissociation rate constant between pH 7.4 and pH 6.0 are key determinants of the improvements in pharmacokinetics associated with 'catch and release' mAbs. The model described here may be useful for prediction of the pharmacokinetics of 'catch and release' mAbs directed against other targets.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Incorporation of FcRn-mediated disposition model to describe the population pharmacokinetics of therapeutic monoclonal IgG antibody in clinical patients

PURPOSE

The two-compartment linear model used to describe the population pharmacokinetics (PK) of many therapeutic monoclonal antibodies (TMAbs) offered little biological insight to antibody disposition in humans. The purpose of this study is to develop a semi-mechanistic FcRn-mediated IgG disposition model to describe the population PK of TMAbs in clinical patients.

METHODS

A standard two-compartment linear PK model from a previously published population PK model of pertuzumab was used to simulate intensive PK data of 100 subjects for model development. Two different semi-mechanistic FcRn-mediated IgG disposition models were developed and First Order Conditional Estimation (FOCE) with the interaction method in NONMEM was used to obtain the final model estimates. The performances of these models were then compared with the two-compartment linear PK model used to simulate the data for model development.

RESULTS

A semi-mechanistic FcRn-mediated IgG disposition model consisting of a peripheral tissue compartment and FcRn-containing endosomes in the central compartment best describes the simulated pertuzumab population PK data. This developed semi-mechanistic population PK model had the same number of model parameters, produced very similar concentration-time profiles but provided additional biological insight to the FcRn-mediated IgG disposition in human subjects compared with the standard linear two-compartment linear PK model.

CONCLUSION

This first reported semi-mechanistic model may serve as an important model framework for developing future population PK models of TMAbs in clinical patients.

Challenges and considerations for development of therapeutic proteins in pediatric patients

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

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.

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.

Studies of nontarget-mediated distribution of human full-length IgG1 antibody and its FAb fragment in cardiovascular and metabolic-related tissues

Tissue distribution and pharmacokinetics (PK) of full-length nontargeted antibody and its antigen-binding fragment (FAb) were evaluated for a range of tissues primarily of interest for cardiovascular and metabolic diseases. Mice were intravenously injected with a dose of 10 mg/kg of either human IgG1or its FAb fragment; perfused tissues were collected at a range of time points over 3 weeks for the human IgG1 antibody and 1 week for the human FAb antibody. Tissues were homogenized and antibody concentrations were measured by specific immunoassays on the Gyros system. Exposure in terms of maximum concentration (Cmax ) and area under the curve was assessed for all nine tissues. Tissue exposure of full-length antibody relative to plasma exposure was found to be between 1% and 10%, except for brain (0.2%). Relative concentrations of FAb antibody were the same, except for kidney tissue, where the antibody concentration was found to be ten times higher than in plasma. However, the absolute tissue uptake of full-length IgG was significantly higher than the absolute tissue uptake of the FAb antibody. This study provides a reference PK state for full-length whole and FAb antibodies in tissues related to cardiovascular and metabolic diseases that do not include antigen or antibody binding.

Development of a physiologically based pharmacokinetic model for a domain antibody in mice using the two-pore theory

Domain antibodies (dAbs) are the smallest antigen-binding fragments of immunoglobulins. To date, there is limited insight into the pharmacokinetics of dAbs, especially their distribution into tissues and elimination. The objective of this work was to develop a physiologically-based pharmacokinetic model to investigate the biodisposition of a non-specific dAb construct in mice. Following a single IV administration of 10 mg/kg dummy dAb protein to twenty four female mice, frequent blood samples were collected and whole body lateral sections were analyzed by quantitative whole-body autoradiography. The model is based on the two-pore hypothesis of extravasation where organ-specific isogravimetric flow rates (Jorg,ISO) and permeability-surface area products (PSorg) are expressed as linear functions of the lymph flow rate (Jorg) and the kidney compartment is modified to account for glomerular filtration of dAb. As a result, only Jorg, glomerular filtration coefficient and the combined volume of Bowman's capsule, proximal and distal renal tubules and loop of Henle were optimized by fitting simultaneously all blood and organ data to the model. Our model captures the pharmacokinetic profiles of dAb in blood and all organs and shows that extravasation into interstitial space is a predominantly diffusion-driven process. The parameter values were estimated with good precision (%RMSE ≈ 30) and low cross-correlation (R(2) < 0.2). We developed a flexible model with a limited parameter number that may be applied to other biotherapeutics after adapting for size-related effects on extravasation and renal elimination processes.

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.

Multichannel imaging to quantify four classes of pharmacokinetic distribution in tumors

Low and heterogeneous delivery of drugs and imaging agents to tumors results in decreased efficacy and poor imaging results. Systemic delivery involves a complex interplay of drug properties and physiological factors, and heterogeneity in the tumor microenvironment makes predicting and overcoming these limitations exceptionally difficult. Theoretical models have indicated that there are four different classes of pharmacokinetic behavior in tissue, depending on the fundamental steps in distribution. In order to study these limiting behaviors, we used multichannel fluorescence microscopy and stitching of high-resolution images to examine the distribution of four agents in the same tumor microenvironment. A validated generic partial differential equation model with a graphical user interface was used to select fluorescent agents exhibiting these four classes of behavior, and the imaging results agreed with predictions. BODIPY-FL exhibited higher concentrations in tissue with high blood flow, cetuximab gave perivascular distribution limited by permeability, high plasma protein and target binding resulted in diffusion-limited distribution for Hoechst 33342, and Integrisense 680 was limited by the number of binding sites in the tissue. Together, the probes and simulations can be used to investigate distribution in other tumor models, predict tumor drug distribution profiles, and design and interpret in vivo experiments.

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.

A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design

The objectives of this retrospective analysis were (1) to characterize the population pharmacokinetics (popPK) of four different monoclonal antibodies (mAbs) in a combined analysis of individual data collected during first-in-human (FIH) studies and (2) to provide a scientific rationale for prospective design of FIH studies with mAbs. The data set was composed of 171 subjects contributing a total of 2716 mAb serum concentrations, following intravenous (IV) and subcutaneous (SC) doses. mAb PK was described by an open 2-compartment model with first-order elimination from the central compartment and a depot compartment with first-order absorption. Parameter values obtained from the popPK model were further used to generate optimal sampling times for a single dose study. A robust fit to the combined data from four mAbs was obtained using the 2-compartment model. Population parameter estimates for systemic clearance and central volume of distribution were 0.20 L/day and 3.6 L with intersubject variability of 31% and 34%, respectively. The random residual error was 14%. Differences (> 2-fold) in PK parameters were not apparent across mAbs. Rich designs (22 samples/subject), minimal designs for popPK (5 samples/subject), and optimal designs for non-compartmental analysis (NCA) and popPK (10 samples/subject) were examined by stochastic simulation and estimation. Single-dose PK studies for linear mAbs executed using the optimal designs are expected to yield high-quality model estimates, and accurate capture of NCA estimations. This model-based meta-analysis has determined typical popPK values for four mAbs with linear elimination and enabled prospective optimization of FIH study designs, potentially improving the efficiency of FIH studies for this class of therapeutics.

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

The structure, interpretation and parameterization of classical compartment models as well as physiologically-based pharmacokinetic (PBPK) models for monoclonal antibody (mAb) disposition are very diverse, with no apparent consensus. In addition, there is a remarkable discrepancy between the simplicity of experimental plasma and tissue profiles and the complexity of published PBPK models. We present a simplified PBPK model based on an extravasation rate-limited tissue model with elimination potentially occurring from various tissues and plasma. Based on model reduction (lumping), we derive several classical compartment model structures that are consistent with the simplified PBPK model and experimental data. We show that a common interpretation of classical two-compartment models for mAb disposition-identifying the central compartment with the total plasma volume and the peripheral compartment with the interstitial space (or part of it)-is not consistent with current knowledge. Results are illustrated for the monoclonal antibodies 7E3 and T84.66 in mice.

Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies

Minimal physiologically-based pharmacokinetic (mPBPK) models provide a sensible modeling approach when fitting only plasma (or blood) data yielding physiologically-relevant PK parameters that may provide more practical value than parameters of mammillary models. We propose a second-generation mPBPK model specifically for monoclonal antibodies (mAb) by including (lumping) several essential components of mAb PK used in full PBPK models. These components include convection as the primary mechanism of antibody movement from plasma into tissues and return to plasma with interstitial fluid as the major extravascular distribution space. The model divides tissue spaces into two groups according to their vascular endothelial structure, leaky and tight, which consequently allows discernment of two types and general sites of distribution. This mPBPK model was applied to two mAbs in mice and ten mAbs with linear kinetics in humans. The model captured their plasma PK profiles well with predictions of concentrations in interstitial fluid for two types of tissues. Predictions of tissue concentrations for mAb 7E3 and 8C2 were consistent with actual measurements in mice, indicating the feasibility of this model in assessing extravascular distribution in the two categories of tissues. The vascular reflection coefficients (σ₁) of tight tissues (V(tight)) ranged 0.883-0.987 and coefficients (σ₂) for leaky tissues (V(leaky)) ranged 0.311 to 0.837. The plasma clearance (CL(p)) varied among the mAbs in humans from 0.0054 to 0.03 L/h. In addition, applying this model generates parameters for mAb transcapillary escape rates and assesses major sites of elimination. Four of ten mAbs exhibited better fitting statistics premised on elimination from interstitial fluid than from plasma. This approach allows comparisons of mAb PK when only plasma data are available, provides more realistic parameters and predictions than mammillary models, and may provide an intermediate step towards utilizing full PBPK models for mAbs.

Are endosomal trafficking parameters better targets for improving mAb pharmacokinetics than FcRn binding affinity?

F.W.R. Brambell deduced the existence of a protective receptor for IgG, the neonatal Fc receptor (FcRn), long before its discovery in the early to mid-1990s. With the coincident, explosive development of IgG-based drugs, FcRn became a popular target for tuning the pharmacokinetics of monoclonal antibodies (mAbs). One aspect of Brambell's initial observation, however, that is seldom discussed since the discovery of the receptor, is the compliance in the mechanism that Brambell observed (saturating at 10s-100s of μM concentration), vs. the comparative stiffness of the receptor kinetics (saturating in the nM range for most species). Although some studies reported that increasing the already very high Fc-FcRn affinity at pH 6.0 further improved mAb half-life, in fact the results were mixed, with later studies increasingly implicating non-FcRn-dependent mechanisms as determinants of mAb pharmacokinetics. Mathematical modelling of the FcRn system has also indicated that the processes determining the pharmacokinetics of mAbs have more nuances than had at first been hypothesised. We propose, in keeping with the latest modelling and experimental evidence reviewed here, that the dynamics of endosomal sorting and trafficking have important roles in the compliant salvage mechanism that Brambell first observed nearly 50 years ago, and therefore also in the pharmacokinetics of mAbs. These ideas lead to many open questions regarding the endosomal trafficking of both FcRn and mAbs and also to what properties of a mAb can be altered to achieve an improvement in pharmacokinetics.

Pharmacokinetics, pharmacodynamics and physiologically-based pharmacokinetic modelling of monoclonal antibodies

Development of monoclonal antibodies (mAbs) and their functional derivatives represents a growing segment of the development pipeline in the pharmaceutical industry. More than 25 mAbs and derivatives have been approved for a variety of therapeutic applications. In addition, around 500 mAbs and derivatives are currently in different stages of development. mAbs are considered to be large molecule therapeutics (in general, they are 2-3 orders of magnitude larger than small chemical molecule therapeutics), but they are not just big chemicals. These compounds demonstrate much more complex pharmacokinetic and pharmacodynamic behaviour than small molecules. Because of their large size and relatively poor membrane permeability and instability in the conditions of the gastrointestinal tract, parenteral administration is the most usual route of administration. The rate and extent of mAb distribution is very slow and depends on extravasation in tissue, distribution within the particular tissue, and degradation. Elimination primarily happens via catabolism to peptides and amino acids. Although not definitive, work has been published to define the human tissues mainly involved in the elimination of mAbs, and it seems that many cells throughout the body are involved. mAbs can be targeted against many soluble or membrane-bound targets, thus these compounds may act by a variety of mechanisms to achieve their pharmacological effect. mAbs targeting soluble antigen generally exhibit linear elimination, whereas those targeting membrane-bound antigen often exhibit non-linear elimination, mainly due to target-mediated drug disposition (TMDD). The high-affinity interaction of mAbs and their derivatives with the pharmacological target can often result in non-linear pharmacokinetics. Because of species differences (particularly due to differences in target affinity and abundance) in the pharmacokinetics and pharmacodynamics of mAbs, pharmacokinetic/pharmacodynamic modelling of mAbs has been used routinely to expedite the development of mAbs and their derivatives and has been utilized to help in the selection of appropriate dose regimens. Although modelling approaches have helped to explain variability in both pharmacokinetic and pharmacodynamic properties of these drugs, there is a clear need for more complex models to improve understanding of pharmacokinetic processes and pharmacodynamic interactions of mAbs with the immune system. There are different approaches applied to physiologically based pharmacokinetic (PBPK) modelling of mAbs and important differences between the models developed. Some key additional features that need to be accounted for in PBPK models of mAbs are neonatal Fc receptor (FcRn; an important salvage mechanism for antibodies) binding, TMDD and lymph flow. Several models have been described incorporating some or all of these features and the use of PBPK models are expected to expand over the next few years.

Issues, challenges, and opportunities in model-based drug development for monoclonal antibodies

Over the last two decades, there has been a simultaneous explosion in the levels of activity and capability in both monoclonal antibody (mAb) drug development and in the use of quantitative pharmacologic models to facilitate drug development. Both of these topics are currently areas of great interest to academia, the pharmaceutical and biotechnology industries, and to regulatory authorities. In this article, we summarize convergence of these two areas and discuss some of the current and historical applications of the use of mathematical-model-based techniques to facilitate the discovery and development of mAb therapeutics. We also consider some of the current issues and limitations in model-based antibody discovery/development and highlight areas of further opportunity.

Antibody biodistribution coefficients: inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human

Tissue vs. plasma concentration profiles have been generated from a physiologically-based pharmacokinetic model of monoclonal antibody (mAb). Based on the profiles, we hypothesized that a linear relationship between the plasma and tissue concentrations of non-binding mAbs could exist; and that the relationship may be generally constant irrespective of the absolute mAb concentration, time, and animal species being analyzed. The hypothesis was verified for various tissues in mice, rat, monkey, and human using mAb or antibody-drug conjugate tissue distribution data collected from diverse literature. The relationship between the plasma and various tissue concentrations was mathematically characterized using the antibody biodistribution coefficient (ABC). Estimated ABC values suggest that typically the concentration of mAb in lung is 14.9%, heart 10.2%, kidney 13.7%, muscle 3.97%, skin 15.7%, small intestine 5.22%, large intestine 5.03%, spleen 12.8%, liver 12.1%, bone 7.27%, stomach 4.98%, lymph node 8.46%, adipose 4.78%, brain 0.351%, pancreas 6.4%, testes 5.88%, thyroid 67.5% and thymus is 6.62% of the plasma concentration. The validity of using the ABC to predict mAb concentrations in different tissues of mouse, rat, monkey, and human species was evaluated by generating validation data sets, which demonstrated that predicted concentrations were within 2-fold of the observed concentrations. The use of ABC to infer tissue concentrations of mAbs and related molecules provides a valuable tool for investigating preclinical or clinical disposition of these molecules. It can also help eliminate or optimize biodistribution studies, and interpret efficacy or toxicity of the drug in a particular tissue.

Describing the effectiveness of immunosuppression drugs and apheresis in the treatment of transplant patients

When any foreign object is found in the human body antibodies are generated that mark it for removal by the immune system. In most cases these are natural and healthy responses; however, when considering organ transplants the immune response to the implanted organ must be kept to a minimum to avoid host rejection. To reduce the host's immune response to the implant, clinicians are able to manipulate the antibody dynamics through drug therapy, to minimise the antibody synthesis (immunosuppression), and by the removal of antibodies directly from the patients' blood, a process known as apheresis. In this paper models are presented that describe the in vivo kinetics of three immune complexes which are routinely measured pre- and post-operatively in implant patients, namely IgA, IgG and IgM. These models are then used to analyse the effective clearance rates of different apheresis methods (plasmapheresis, plasma absorption or plasma exchange) and to quantify the impact immune-suppression drugs have on the underlying antibody synthesis. It is hoped that the simplicity of the mathematical models, and associated implementation, will allow the translation of knowledge gained of the process dynamics to positively impact future patient diagnosis and treatment.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

Pharmacokinetic and pharmacodynamic modeling of romiplostim in animals

PURPOSE

Romiplostim is a novel thrombopoiesis-stimulating peptibody that targets the thrombopoietin c-Mpl receptor, resulting in increased platelet production. The pharmacodynamic-mediated disposition (PDMDD) and its stimulatory effect on platelet production in Sprague-Dawley rats, rhesus monkeys, and cynomolgus monkeys following IV bolus and SC administration at various dose levels were determined.

METHODS

The pharmacokinetic (PK) profile was described by a PDMDD model that accounts for romiplostim binding to the c-Mpl receptor. The PD model contained a series of aging compartments for precursor cells in bone marrow and platelets. The stimulatory function was described by an on-and-off function operating on the fractional receptor occupancy (RO). The threshold effect, RO(thr), and K(D) parameters were determinants of drug potency, whereas S(max) reflected drug efficacy.

RESULTS

The model implicated that receptor-mediated clearance was negligible. RO(thr) estimated occupancies were 0.288, 0.385, 0.771 for rats, rhesus, and cynomolgus monkeys, respectively. The analogous estimated values of K(D) were 4.05, 2320, and 429 ng/mL, implying that romiplostim was much more potent in rats, which was confirmed by a dose-response (ratio of peak platelet count to baseline) relationship.

CONCLUSIONS

The model adequately described romiplostim serum concentrations and platelet counts in rats, rhesus monkeys, and cynomolgus monkeys, and quantified linear clearance, PDMDD, and potency of romiplostim.

Application of PBPK modeling to predict monoclonal antibody disposition in plasma and tissues in mouse models of human colorectal cancer

This investigation evaluated the utility of a physiologically based pharmacokinetic (PBPK) model, which incorporates model parameters representing key determinants of monoclonal antibody (mAb) target-mediated disposition, to predict, a priori, mAb disposition in plasma and in tissues, including tumors that express target antigens. Monte Carlo simulation techniques were employed to predict the disposition of two mAbs, 8C2 (as a non-binding control mouse IgG1 mAb) and T84.66 (a high-affinity murine IgG1 anti-carcinoembryonic antigen mAb), in mice bearing no tumors, or bearing colorectal HT29 or LS174T xenografts. Model parameters were obtained or derived from the literature. (125)I-T84.66 and (125)I-8C2 were administered to groups of SCID mice, and plasma and tissue concentrations were determined via gamma counting. The PBPK model well-predicted the experimental data. Comparisons of the population predicted versus observed areas under the plasma concentration versus time curve (AUC) for T84.66 were 95.4 ± 67.8 versus 84.0 ± 3.0, 1,859 ± 682 versus 2,370 ± 154, and 5,930 ± 1,375 versus 5,960 ± 317 (nM × day) at 1, 10, and 25 mg/kg in LS174T xenograft-bearing SCID mice; and 215 ± 72 versus 233 ± 30, 3,070 ± 346 versus 3,120 ± 180, and 7,884 ± 714 versus 7,440 ± 626 in HT29 xenograft-bearing mice. Model predicted versus observed 8C2 plasma AUCs were 312.4 ± 30 versus 182 ± 7.6 and 7,619 ± 738 versus 7,840 ± 24.3 (nM × day) at 1 and 25 mg/kg. High correlations were observed between the predicted median plasma concentrations and observed median plasma concentrations (r (2) = 0.927, for all combinations of treatment, dose, and tumor model), highlighting the utility of the PBPK model for the a priori prediction of in vivo data.

Application of pharmacokinetics-pharmacodynamics/clinical response modeling and simulation for biologics drug development

Biologics, specifically monoclonal antibody (mAb) drugs, have unique pharmacokinetic (PK) and pharmacodynamic (PD) characteristics as opposed to small molecules. Under the paradigm of model-based drug development, PK-PD/clinical response models offer critical insight in guiding biologics development at various stages. On the basis of the molecular structure and corresponding properties of biologics, typical mechanism-based [target-mediated drug disposition (TMDD)], physiologically based PK, PK-PD, and dose-response meta-analysis models are summarized. Examples of using TMDD, PK-PD, and meta-analysis in helping starting dose determination in first-in-human studies and dosing regimen optimization in phase II/III trials are discussed. Instead of covering the entirety of model-based biologics development, this review focuses on the guiding principles and the core mathematical descriptions underlying the PK or PK-PD models most used.

Evaluation of a catenary PBPK model for predicting the in vivo disposition of mAbs engineered for high-affinity binding to FcRn

Efforts have been made to extend the biological half-life of monoclonal antibody drugs (mAbs) by increasing the affinity of mAb-neonatal Fc receptor (FcRn) binding; however, mixed results have been reported. One possible reason for a poor correlation between the equilibrium affinity of mAb-FcRn binding and mAb systemic pharmacokinetics is that the timecourse of endosomal transit is too brief to allow binding to reach equilibrium. In the present work, a new physiologically based pharmacokinetic (PBPK) model has been developed to approximate the pH and time-dependent endosomal trafficking of immunoglobulin G (IgG). In this model, a catenary sub-model was utilized to describe the endosomal transit of IgG and the time dependencies in IgG-FcRn association and dissociation. The model performs as well as a previously published PBPK model, with assumed equilibrium kinetics of mAb-FcRn binding, in capturing the disposition profile of murine mAb from wild-type and FcRn knockout mice (catenary vs. equilibrium model: r (2), 0.971 vs. 0.978; median prediction error, 3.38% vs. 3.79%). Compared to the PBPK model with equilibrium binding, the present catenary PBPK model predicts much more moderate changes in half-life with altered FcRn binding. For example, for a 10-fold increase in binding affinity, the catenary model predicts <2.5-fold change in half-life compared to an ∼8-fold increase as predicted by the equilibrium model; for a 100-fold increase in binding affinity, the catenary model predicts ∼7-fold change in half-life compared to >70-fold increase as predicted by the equilibrium model. Predictions of the new catenary PBPK model are more consistent with experimental results in the published literature.

A mechanistic compartmental model for total antibody uptake in tumors

Antibodies are under development to treat a variety of cancers, such as lymphomas, colon, and breast cancer. A major limitation to greater efficacy for this class of drugs is poor distribution in vivo. Localization of antibodies occurs slowly, often in insufficient therapeutic amounts, and distributes heterogeneously throughout the tumor. While the microdistribution around individual vessels is important for many therapies, the total amount of antibody localized in the tumor is paramount for many applications such as imaging, determining the therapeutic index with antibody drug conjugates, and dosing in radioimmunotherapy. With imaging and pretargeted therapeutic strategies, the time course of uptake is critical in determining when to take an image or deliver a secondary reagent. We present here a simple mechanistic model of antibody uptake and retention that captures the major rates that determine the time course of antibody concentration within a tumor including dose, affinity, plasma clearance, target expression, internalization, permeability, and vascularization. Since many of the parameters are known or can be estimated in vitro, this model can approximate the time course of antibody concentration in tumors to aid in experimental design, data interpretation, and strategies to improve localization.

Nano-scale liquid chromatography/mass spectrometry and on-the-fly orthogonal array optimization for quantification of therapeutic monoclonal antibodies and the application in preclinical analysis

Therapeutic monoclonal antibodies (mAbs) constitute a group of highly effective agents for treating various refractory diseases. Nonetheless it is challenging to achieve selective and accurate quantification of mAb in pharmaceutical matrices, which is required by PK studies. Liquid chromatography/mass spectrometry under selected reaction monitoring mode (LC/SRM-MS) is emerging as an attractive alternative to immunoassays because of the high specificity and multiplexing capacity it provides, but may fall short in terms of sensitivity, reliability and quantitative accuracy. Moreover, the strategy for optimization of the MS conditions for many candidates of signature peptides (SP) and the selection of the optimal SP for quantification remains elusive. In this study, we employed a suite of technical advances to overcome these difficulties, which include: (i) a nano-LC/SRM-MS approach to achieve high analytical sensitivity, (ii) a high-resolution nano-LC/LTQ/Orbitrap for confident identification of candidate peptides, (iii) an on-the-fly orthogonal array optimization (OAO) method for the high-throughput, accurate and reproducible optimization for numerous candidate peptides in a single LC/MS run without using synthesized peptides, (iv) a comprehensive evaluation of stability of candidates in matrix using the optimized SRM parameters, (v) the use of two unique SP for quantification of one mAb to gauge possible degradation/modification in biological system and thus enhancing data reliability (e.g. rejection of data if the deviation between the two SP is greater than 25%) and (vi) the utilization of purified target protein as the calibrator to eliminate the risk of severe negative biases that could occur when a synthesized peptide is used as calibrator. To show a proof of concept, this strategy is applied in the quantification of cT84.66, a chimeric, anti-CEA antibody, in preclinical mouse models. A low detection limit of the mAb down to 3.2 ng/mL was achieved, which is substantially more sensitive than established immunoassay methods for anti-CEA antibodies. The quantitative method showed good linearity (within the range of 12.9 ng/mL to 32.3 μg/mL in plasma), accuracy and precision. Additionally, the ultra-low sample consumption (2 μL plasma per preparation) permits the acquisition of an entire set of time course data from the same mouse, which represents a prominent advantage for PK study using small-animal models. The developed method enabled an accurate PK investigation of cT84.66 in mice following intravenous and subcutaneous administrations at relatively low doses over an extended period of time. The strategy employed in this study can be easily adapted to the sensitive and accurate analysis of other mAb and therapeutic proteins.

Pretargeted molecular imaging and radioimmunotherapy

Pretargeting is a multi-step process that first has an unlabeled bispecific antibody (bsMAb) localize within a tumor by virtue of its anti-tumor binding site(s) before administering a small, fast-clearing radiolabeled compound that then attaches to the other portion of the bsMAb. The compound's rapid clearance significantly reduces radiation exposure outside of the tumor and its small size permits speedy delivery to the tumor, creating excellent tumor/nontumor ratios in less than 1 hour. Haptens that bind to an anti-hapten antibody, biotin that binds to streptavidin, or an oligonucleotide binding to a complementary oligonucleotide sequence have all been radiolabeled for use by pretargeting. This review will focus on a highly flexible anti-hapten bsMAb platform that has been used to target a variety of radionuclides to image (SPECT and PET) as well as treat tumors.

Pharmacokinetic models for FcRn-mediated IgG disposition

The objectives were to review available PK models for saturable FcRn-mediated IgG disposition, and to explore an alternative semimechanistic model. Most available empirical and mechanistic PK models assumed equal IgG concentrations in plasma and endosome in addition to other model-specific assumptions. These might have led to inappropriate parameter estimates and model interpretations. Some physiologically based PK (PBPK) models included FcRn-mediated IgG recycling. The nature of PBPK models requires borrowing parameter values from literature, and subtle differences in the assumptions may render dramatic changes in parameter estimates related to the IgG recycling kinetics. These models might have been unnecessarily complicated to address FcRn saturation and nonlinear IgG PK especially in the IVIG setting. A simple semimechanistic PK model (cutoff model) was developed that assumed a constant endogenous IgG production rate and a saturable FcRn-binding capacity. The FcRn-binding capacity was defined as MAX, and IgG concentrations exceeding MAX in endosome resulted in lysosomal degradation. The model parameters were estimated using simulated data from previously published models. The cutoff model adequately described the rat and mouse IgG PK data simulated from published models and allowed reasonable estimation of endogenous IgG turnover rates.

Pharmacokinetics and toxicology of therapeutic proteins: Advances and challenges

Significant progress has been made in understanding pharmacokinetics (PK), pharmacodynamics (PD), as well as toxicity profiles of therapeutic proteins in animals and humans, which have been in commercial development for more than three decades. However, in the PK arena, many fundamental questions remain to be resolved. Investigative and bioanalytical tools need to be established to improve the translation of PK data from animals to humans, and from in vitro assays to in vivo readouts, which would ultimately lead to a higher success rate in drug development. In toxicology, it is known, in general, what studies are needed to safely develop therapeutic proteins, and what studies do not provide relevant information. One of the major complicating factors in nonclinical and clinical programs for therapeutic proteins is the impact of immunogenicity. In this review, we will highlight the emerging science and technology, as well as the challenges around the pharmacokinetic- and safety-related issues in drug development of mAbs and other therapeutic proteins.

Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human

The objectives of the following investigation were (1) development of a physiologically based pharmacokinetic (PBPK) model capable of characterizing the plasma and tissue pharmacokinetics (PK) of nonspecific or antigen specific monoclonal antibodies (mAbs) in wild type, FcRn knockout, tumor bearing and non tumor bearing mice and (2) evaluation of the scale up potential of the model by characterizing the mouse, rat, monkey and human plasma PK of mAbs, simultaneously. A PBPK model containing 15 tissues, a carcass and a tumor compartment was developed by modifying/augmenting previously published PBPK models. Each tissue compartment was subdivided into plasma, blood cell, endothelial, interstitial and cellular sub-compartments. Each tissue was connected through blood and lymph flow to the systemic circulation. Lymph flow was set to a value 500 times lower than plasma flow and vascular reflection coefficients for each tissue were adjusted according to their vascular pore size. In each tissue endothelial space, mAb entered via pinocytosis and the interaction of FcRn with mAb was described by on and off rates. FcRn bound mAb was recycled and unbound mAb was eliminated by a first order process (K(deg)). The PBPK model was simultaneously fit to the following datasets to estimate four system parameters: (1) plasma and tissue PK of nonspecific mAb in wild type mouse with or without simultaneous intravenous immunoglobulin (IVIG) administration, (2) plasma and tissue PK of nonspecific mAb in FcRn knockout mouse, (3) plasma and tissue PK of nonspecific mAb in tumor bearing mouse, (4) plasma and tissue PK of tumor antigen specific mAb in tumor bearing mouse, and (5) plasma PK of mAb in rat, monkey and human. The model was able to characterize all the datasets reasonably well with a common set of parameters. The estimated value of the four system parameters i.e. FcRn concentration (FcRn), rate of pinocytosis per unit endosomal space (CL(up)), K(deg) and the proportionality constant (C_LNLF) between the rate at which antibody transfers from the lymph node compartment to the blood compartment and the plasma flow of the given species, were found to be 4.98E-05 M (CV% = 11.1), 3.66E-02 l/h/l (%CV = 3.48), 42.9 1/h (%CV = 15.7) and 9.1 (CV% > 50). Thus, a platform PBPK model has been developed that can not only simultaneously characterize mAb disposition data obtained from various previously published mouse PBPK models but is also capable of characterizing mAb disposition in various preclinical species and human.

Effects of anti-VEGF on predicted antibody biodistribution: roles of vascular volume, interstitial volume, and blood flow

Background

The identification of clinically meaningful and predictive models of disposition kinetics for cancer therapeutics is an ongoing pursuit in drug development. In particular, the growing interest in preclinical evaluation of anti-angiogenic agents alone or in combination with other drugs requires a complete understanding of the associated physiological consequences.

Methodology/Principal Findings

Technescan™ PYP™, a clinically utilized radiopharmaceutical, was used to measure tissue vascular volumes in beige nude mice that were naïve or administered a single intravenous bolus dose of a murine anti-vascular endothelial growth factor (anti-VEGF) antibody (10 mg/kg) 24 h prior to assay. Anti-VEGF had no significant effect (p>0.05) on the fractional vascular volumes of any tissues studied; these findings were further supported by single photon emission computed tomographic imaging. In addition, apart from a borderline significant increase (p = 0.048) in mean hepatic blood flow, no significant anti-VEGF-induced differences were observed (p>0.05) in two additional physiological parameters, interstitial fluid volume and the organ blood flow rate, measured using indium-111-pentetate and rubidium-86 chloride, respectively. Areas under the concentration-time curves generated by a physiologically-based pharmacokinetic model changed substantially (>25%) in several tissues when model parameters describing compartmental volumes and blood flow rates were switched from literature to our experimentally derived values. However, negligible changes in predicted tissue exposure were observed when comparing simulations based on parameters measured in naïve versus anti-VEGF-administered mice.

Conclusions/Significance

These observations may foster an enhanced understanding of anti-VEGF effects in murine tissues and, in particular, may be useful in modeling antibody uptake alone or in combination with anti-VEGF.

Potential of optimal preloading in anti-CD20 antibody radioimmunotherapy: an investigation based on pharmacokinetic modeling

Recently, it has been suggested that the concept of preloading is limited by using a standard amount of unlabeled antibody. To identify the potential of optimal preloading, a pharmacokinetic model that describes the biodistribution of anti-CD20 antibody was developed. Simulations were conducted for different tumor burdens, spleen sizes, and tumor permeabilities. The optimal amount of unlabeled antibody was determined for each scenario. These simulations show that the currently administered standard amount is not optimal. A preload of 150 mg or lower would result in equal or higher tumor uptake in all cases. For tumors with high permeability, the uptake of labeled antibody could be increased by a factor of 8.5 using the considerably reduced optimal preload. The most sensitive parameter for the choice of the optimal amount of unlabeled antibody is the tumor uptake index. The results indicate that a personalized approach for radioimmunotherapy (RIT) with anti-CD20 antibody is required to account for the interpatient variability. The optimal amount of unlabeled antibody, which has to be determined by using a pharmacokinetic model, could substantially improve tumor uptake and thus RIT with anti-CD20 antibody.