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

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.

Monoclonal antibodies: Pharmacokinetics as a basis for new dosage regimens?

Complete monoclonal IgG antibodies which are in use in clinical practice share some pharmacological properties resulting in high concentrations in plasma. This fact is reflected in their low volumes of distribution, which can also be correlated with a high molecular weight and water solubility. This feature allows a novel approach to be applied to the dosing schedule for this group of drugs with fixed doses being used instead of the initially developed weight- or body surface-adjusted dosing schedules. In addition, the development of a new formulation containing hyaluronidase allows a subcutaneous route of administration to be used, because hyaluronidase creates a space in the subcutaneous tissue that helps antibody absorption. This method requires higher doses, but has allowed testing the feasibility of administering a fixed dose, with no individual dose adjustments based on weight or body surface. Moreover, loading doses are not needed, because the first dose results, within 3 weeks, in minimum concentrations that are higher than effective concentrations.

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.

Emerging advances in nanomedicine with engineered gold nanostructures

Gold nanostructures possess unique characteristics that enable their use as contrast agents, as therapeutic entities, and as scaffolds to adhere functional molecules, therapeutic cargo, and targeting ligands. Due to their ease of synthesis, straightforward surface functionalization, and non-toxicity, gold nanostructures have emerged as powerful nanoagents for cancer detection and treatment. This comprehensive review summarizes the progress made in nanomedicine with gold nanostructures (1) as probes for various bioimaging techniques including dark-field, one-photon and two-photon fluorescence, photothermal optical coherence tomography, photoacoustic tomography, positron emission tomography, and surface-enhanced Raman scattering based imaging, (2) as therapeutic components for photothermal therapy, gene and drug delivery, and radiofrequency ablation, and (3) as a theranostic platform to simultaneously achieve both cancer detection and treatment. Distinct from other published reviews, this article also discusses the recent advances of gold nanostructures as contrast agents and therapeutic actuators for inflammatory diseases including atherosclerotic plaque and arthritis. For each of the topics discussed above, the fundamental principles and progress made in the past five years are discussed. The review concludes with a detailed future outlook discussing the challenges in using gold nanostructures, cellular trafficking, and translational considerations that are imperative for rapid clinical viability of plasmonic nanostructures, as well as the significance of emerging technologies such as Fano resonant gold nanostructures in nanomedicine.

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.

Prediction of drug disposition on the basis of its chemical structure

The chemical structure of any drug determines its pharmacokinetics and pharmacodynamics. Detailed understanding of relationships between the drug chemical structure and individual disposition pathways (i.e., distribution and elimination) is required for efficient use of existing drugs and effective development of new drugs. Different approaches have been developed for this purpose, ranging from statistics-based quantitative structure-property (or structure-pharmacokinetic) relationships (QSPR) analysis to physiologically based pharmacokinetic (PBPK) models. This review critically analyzes currently available approaches for analysis and prediction of drug disposition on the basis of chemical structure. Models that can be used to predict different aspects of disposition are presented, including: (a) value of the individual pharmacokinetic parameter (e.g., clearance or volume of distribution), (b) efficiency of the specific disposition pathway (e.g., biliary drug excretion or cytochrome P450 3A4 metabolism), (c) accumulation in a specific organ or tissue (e.g., permeability of the placenta or accumulation in the brain), and (d) the whole-body disposition in the individual patients. Examples of presented pharmacological agents include "classical" low-molecular-weight compounds, biopharmaceuticals, and drugs encapsulated in specialized drug-delivery systems. The clinical efficiency of agents from all these groups can be suboptimal, because of inefficient permeability of the drug to the site of action and/or excessive accumulation in other organs and tissues. Therefore, robust and reliable approaches for chemical structure-based prediction of drug disposition are required to overcome these limitations. PBPK models are increasingly being used for prediction of drug disposition. These models can reflect the complex interplay of factors that determine drug disposition in a mechanistically correct fashion and can be combined with other approaches, for example QSPR-based prediction of drug permeability and metabolism, pharmacogenomic data and tools, pharmacokinetic-pharmacodynamic modeling approaches, etc. Moreover, the PBPK models enable detailed analysis of clinically relevant scenarios, for example the effect of the specific conditions on the time course of the analyzed drug in the individual organs and tissues, including the site of action. It is expected that further development of such combined approaches will increase their precision, enhance the effectiveness of drugs, and lead to individualized drug therapy for different patient populations (geriatric, pediatric, specific diseases, etc.).

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.

Modeling, simulation, and translation framework for the preclinical development of monoclonal antibodies

The industry-wide biopharmaceutical (i.e., biologic, biotherapeutic) pipeline has been growing at an astonishing rate over the last decade with the proportion of approved new biological entities to new chemical entities on the rise. As biopharmaceuticals appear to be growing in complexity in terms of their structure and mechanism of action, so are interpretation, analysis, and prediction of their quantitative pharmacology. We present here a modeling and simulation (M&S) framework for the successful preclinical development of monoclonal antibodies (as an illustrative example of biopharmaceuticals) and discuss M&S strategies for its implementation. Critical activities during early discovery, lead optimization, and the selection of starting doses for the first-in-human study are discussed in the context of pharmacokinetic-pharmacodynamic (PKPD) and M&S. It was shown that these stages of preclinical development are and should be reliant on M&S activities including systems biology (SB), systems pharmacology (SP), and translational pharmacology (TP). SB, SP, and TP provide an integrated and rationalized framework for decision making during the preclinical development phase. In addition, they provide increased target and systems understanding, describe and interpret data generated in vitro and in vivo, predict human PKPD, and provide a rationalized approach to designing the first-in-human study.

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.

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.

Local versus systemic anti-tumour necrosis factor-α effects of adalimumab in rheumatoid arthritis: pharmacokinetic modelling analysis of interaction between a soluble target and a drug

BACKGROUND AND OBJECTIVE

The pharmacokinetic models that are applied to describe the disposition of therapeutic antibodies assume that the interaction between an antibody and its target takes place in the central compartment. However, an increasing number of therapeutic antibodies are directed towards soluble/mobile targets. A flawed conclusion can be reached if the pharmacokinetic and pharmacodynamic analysis assumes that the interaction between the therapeutic antibody and its target takes place in the central compartment. The objective of this study was to assess the relative importance of local versus systemic interactions between adalimumab and tumour necrosis factor (TNF)-α in rheumatoid arthritis (RA), identify localization of the site of adalimumab action and assess the efficacy of local (intra-articular) versus systemic adalimumab administration for treatment of RA.

METHODS

The clinical and preclinical data on adalimumab and TNFα disposition were analysed using a pharmacokinetic modelling and simulation approach. The disposition of adalimumab and TNFα and the interaction between them at the individual compartments (the synovial fluid of the affected joints, central and peripheral compartments) following different routes of adalimumab administration were studied.

RESULTS

Outcomes of modelling and simulation using the pharmacokinetic model developed indicate that adalimumab can efficiently permeate from the diseased joints to the central circulation in RA patients. Permeability of TNFα, which is excessively secreted in the joints, is even higher than that of adalimumab. As a result, subcutaneous, intravenous and intra-articular administration of the clinically used dose of adalimumab (40 mg) exert similar effects on the time course of TNFα concentrations at different locations in the body and efficiently deplete the TNFα in all of the compartments for a prolonged period of time (8-10 weeks). At this dose, adalimumab exhibits predominantly systemic anti-TNFα effects at the central and peripheral compartments (∼93% of the overall effect) and the contribution of the local effects in the rheumatic joints is ∼7% for all of the studied routes, including the local intra-articular injections. The major pathway of TNFα elimination from the synovial fluid (∼77% for subcutaneous administration, and ∼72% for intravenous and intra-articular administration of adalimumab 40 mg) is interaction with adalimumab, which reaches the joints following local or systemic administration.

CONCLUSIONS

The kinetics of adalimumab permeation to the synovial fluid (0.00422 L/h clearance of permeation) versus the rate of TNFα turnover in the affected joints (1.84 pmol/h synthesis rate and 0.877 h(-1) degradation rate constant) are apparently the major parameters that determine the time course of TNFα concentrations in the synovial fluid and the TNFα-neutralizing effects of adalimumab in RA patients. Outcomes of this study suggest that intra-articular administration of adalimumab is not preferable to subcutaneous or intravenous treatment. Local and systemic permeability, turnover and interactions between the drug and the target should be taken into account for optimization of the use of drugs acting on soluble targets (growth factors, interferons, interleukins, immunoglobulins, etc.).

Comprehensive mechanism-based antibody pharmacokinetic modeling

Pharmacokinetic models of antibody distribution and dynamics are useful for predicting and optimizing therapeutic behavior. Targeted antigens are produced and distributed in various tissues in specific patterns in disease phenotypes. Existing models leave out significant mechanistic detail which would enable an understanding of how to modify therapeutics in an optimal manner to allow appropriate tissue penetration in either a healthy or diseased state. The model presented here incorporates additional complexity such as diffusion through endothelial barriers, differential transcytosis properties, FcRn-mediated recycling, and incorporates these properties in an organ-specific manner. This creates a platform which can be expanded upon to include understanding of the effect of target on therapeutic distribution and clearance, differences in dynamics during a diseased versus healthy state, differential dose strategies, and mechanistic translation between animal models and human disease state. This model represents a superior alternative to typical and potentially over-simplified scaling strategies utilized in most existing physiologically-based pharmacokinetic models. Ultimately, this will enable better therapeutic design and greater pharmacological effects.

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.

Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling

Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. Later stages of the drug development processes, however, rely on pharmacokinetic compartment models while cell-level dynamics are typically neglected. We here present a systematic approach to integrate cell-level kinetic models and pharmacokinetic compartment models. Incorporating target dynamics into pharmacokinetic models is especially useful for the development of therapeutic antibodies because their effect and pharmacokinetics are inherently interdependent. The approach is illustrated by analysing the F(ab)-mediated inhibitory effect of therapeutic antibodies targeting the epidermal growth factor receptor. We build a multi-level model for anti-EGFR antibodies by combining a systems biology model with in vitro determined parameters and a pharmacokinetic model based on in vivo pharmacokinetic data. Using this model, we investigated in silico the impact of biochemical properties of anti-EGFR antibodies on their F(ab)-mediated inhibitory effect. The multi-level model suggests that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity, thereby limiting the impact of increasing antibody affinity on improving the effect. This indicates that observed differences in the therapeutic effects of high affinity antibodies in the market and in clinical development may result mainly from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity.

Physiologically based pharmacokinetic modeling of PLGA nanoparticles with varied mPEG content

Biodistribution of nanoparticles is dependent on their physicochemical properties (such as size, surface charge, and surface hydrophilicity). Clear and systematic understanding of nanoparticle properties’ effects on their in vivo performance is of fundamental significance in nanoparticle design, development and optimization for medical applications, and toxicity evaluation. In the present study, a physiologically based pharmacokinetic model was utilized to interpret the effects of nanoparticle properties on previously published biodistribution data. Biodistribution data for five poly(lactic-co-glycolic) acid (PLGA) nanoparticle formulations prepared with varied content of monomethoxypoly (ethyleneglycol) (mPEG) (PLGA, PLGA-mPEG256, PLGA-mPEG153, PLGA-mPEG51, PLGA-mPEG34) were collected in mice after intravenous injection. A physiologically based pharmacokinetic model was developed and evaluated to simulate the mass-time profiles of nanoparticle distribution in tissues. In anticipation that the biodistribution of new nanoparticle formulations could be predicted from the physiologically based pharmacokinetic model, multivariate regression analysis was performed to build the relationship between nanoparticle properties (size, zeta potential, and number of PEG molecules per unit surface area) and biodistribution parameters. Based on these relationships, characterized physicochemical properties of PLGA-mPEG495 nanoparticles (a sixth formulation) were used to calculate (predict) biodistribution profiles. For all five initial formulations, the developed model adequately simulates the experimental data indicating that the model is suitable for description of PLGA-mPEG nanoparticle biodistribution. Further, the predicted biodistribution profiles of PLGA-mPEG495 were close to experimental data, reflecting properly developed property–biodistribution relationships.

Physiologically based pharmacokinetic modeling for nanoparticle toxicity study

This chapter introduces the principles and development procedures for physiologically based pharmacokinetic (PBPK) models, and their application for nanoparticle toxicity studies. PBPK models describe the concentration-time or mass-time profiles of chemicals or nanoparticles in individual tissues and organs within the body. They have been used mostly for toxicology and pharmacology studies of small molecules, and their application for nanoparticles are in the early stages. Due to the biodistribution differences between nanoparticles and small molecules, modification may be necessary to build PBPK models for nanoparticles. PBPK models for nanoparticles may be applied to biodistribution predictions, data extrapolation, and property-biodistribution relationships, and, thus, can be a powerful tool in toxicity evaluation.

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.

Physiologically-based pharmacokinetics in drug development and regulatory science

The application of physiologically-based pharmacokinetic (PBPK) modeling is coming of age in drug development and regulation, reflecting significant advances over the past 10 years in the predictability of key pharmacokinetic (PK) parameters from human in vitro data and in the availability of dedicated software platforms and associated databases. Specific advances and contemporary challenges with respect to predicting the processes of drug clearance, distribution, and absorption are reviewed, together with the ability to anticipate the quantitative extent of PK-based drug-drug interactions and the impact of age, genetics, disease, and formulation. The value of this capability in selecting and designing appropriate clinical studies, its implications for resource-sparing techniques, and a more holistic view of the application of PK across the preclinical/clinical divide are considered. Finally, some attention is given to the positioning of PBPK within the drug development and approval paradigm and its future application in truly personalized medicine.

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.

A new stochastic approach to multi-compartment pharmacokinetic models: probability of traveling route and distribution of residence time in linear and nonlinear systems

Drug kinetics in human has been studied from both deterministic and stochastic perspectives. However, little research has been done to systematically determine the probability for a drug molecule to follow a specific traveling route. Recently a method was developed to estimate this probability and the probability density function of residence time in linear systems. In this paper, we provide a rigorous proof of the main results of the previous paper and extend the method to nonlinear multi-compartment systems. A novel concept of compartment expansion is introduced to facilitate the development of our method. This formulation resolves computational difficulties associated with nonlinear systems, allowing for direct estimation of the probability intensity coefficients, and subsequently the transition probability and probability density function of the residence time. With such expansion of the methodology, it becomes both practical and feasible to apply it in the real-world drug development where drug disposition patterns are often nonlinear. The method can be used to estimate drug exposure at any site of interest, thus may help us to gain better understanding about the impact of drug exposure on efficacy and safety.

Physiologically based pharmacokinetic modeling of nanoparticles

Rapid expansion of nanoparticle research demands new technologies that will enable better interpretation of experimental data and assistance in the rational design of future nanoparticles. The use of physiologically based pharmacokinetic (PBPK) models may serve as powerful tools to meet these needs. PBPK models have been successfully applied for the study of the absorption, distribution, metabolism, and excretion (ADME) of small molecules, such as drugs. Preliminary application of PBPK models to nanoparticles illustrated their potential usefulness for nanoparticle ADME research. However, due to the differences between nanoparticles and small molecules, modifications are needed to build appropriate PBPK models for nanoparticles. This review is divided into two sections, with the first discussing nanoparticle ADME research, emphasizing the interaction of nanoparticles with living systems, including transportation kinetics across biobarriers. In the second section, the basic principles of PBPK model development are introduced, and research pertaining to PBPK models of nanoparticles is reviewed. Factors that need to be considered for developing PBPK models for nanoparticles are also discussed. Finally, perspective applications of nanoparticle PBPK models are summarized.

Translational considerations for cancer nanomedicine

There are many important considerations during preclinical development of cancer nanomedicines, including: 1) unique aspects of animal study design; 2) the difficulties in evaluating biological potency, especially for complex formulations; 3) the importance of analytical methods that can determine platform stability in vivo, and differentiate bound and free active pharmaceutical ingredient (API) in biological matrices; and 4) the appropriateness of current dose scaling techniques for estimation of clinical first-in-man dose from preclinical data. Biologics share many commonalities with nanotechnology products with regard to complexity and biological attributes, and can, in some cases, provide context for dealing with these preclinical issues. In other instances, such as the case of in vivo stability analysis, new approaches are required. This paper will discuss the significance of these preclinical issues, and present examples of current methods and best practices for addressing them. Where possible, these recommendations are justified using the existing regulatory guidance literature.

Interspecies scaling of therapeutic monoclonal antibodies: initial look

The authors evaluated interspecies scaling for the prediction of human clearance of 18 therapeutic monoclonal antibodies (mAbs). Human and monkey/chimpanzee data of 14 mAbs were classified based on the targeted antigens (soluble or membrane bound). Simple allometry and/or a time-invariant method (elementary Dedrick plot) were performed. Results indicate that human clearance might be accurately predicted from monkey data for mAbs targeting soluble receptors or membrane-bound receptors with limited tissue distribution using simplified allometry. The optimal exponents were estimated to be 0.85 or 0.90. If nonlinearity is anticipated at the human efficacious dose, pharmacokinetic parameters obtained at high doses in animals might not be sufficient for full pharmacokinetic characterization and prediction. Using prespecified criteria, including predicted human clearance (< or = or > 10 mL/d/kg), simplified allometric scaling might be helpful in predicting the effect of receptor-mediated clearance for mAbs targeting membrane-bound antigens. Furthermore, simplified allometry and an elementary Dedrick plot provide similar results in predicted clearance. Given the significant advantages offered by simplified allometry, it should be used when data are available from only 1 species. When reasonable data from > or =3 species are available, traditional allometry should be explored. Overall, clearance prediction is useful for human dose prediction in drug discovery and development.

The ratio of maximum percent tumour accumulations of the pretargeting agent and the radiolabelled effector is independent of tumour size

Our previous studies have indicated that the optimal dosage ratio of pretargeting antibody to effector is proportional to their maximum percent tumour accumulations (MPTAs). This study quantitatively describes how both MPTAs and their ratio change with tumour size, to simplify pretargeting optimisation when tumour size varies. The CC49 antibody dosages below saturation of the tumour antigen level were first examined for the LS174T tumour mouse model. Then the MPTAs of the antibody in mice bearing tumours of different sizes were determined, always at antibody dosages below antigen saturation. Historical data from this laboratory were used to collect the MPTAs of the (99m)Tc-cMORF effector for different tumour sizes, always at effector dosages below that required to saturate the MORF in tumour. The MPTAs versus tumour sizes for both the antibody and the effector were fitted non-linearly. The best fit of the antibody MPTA (Y(antibody)) with tumour size (x) in grams was Y(antibody)=19.00 x(-0.65) while that for the effector was Y(effector)=4.51x(-0.66). Thus, even though the MPTAs of both vary with tumour size, the ratio (Y(antibody)/Y(effector)) is a constant at 4.21. In conclusion, the MPTA ratio of the antibody to the effector was found to be constant with tumour size, an observation that will simplify pretargeting optimisation because remeasurement of the optimum dosage ratio for different tumour sizes can be avoided. Theoretical considerations also suggest that this relationship may be universal for alternative antibody/effector pairs and for different target models, but this must be experimentally confirmed.

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

BACKGROUND

Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination.

OBJECTIVES

To review the current state of WB-PBPK model use in the clinical phases of drug development.

METHODS

A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed.

CONCLUSIONS

This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.