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

Physiology-based pharmacokinetic model with relative transcriptomics to evaluate tissue distribution and receptor occupancy of anifrolumab

Type I interferons contribute to the pathogenesis of several autoimmune disorders, including systemic lupus erythematosus (SLE), systemic sclerosis, cutaneous lupus erythematosus, and myositis. Anifrolumab is a monoclonal antibody that binds to subunit 1 of the type I interferon receptor (IFNAR1). Results of phase IIb and phase III trials led to the approval of intravenous anifrolumab 300 mg every 4 weeks (Q4W) alongside standard therapy in patients with moderate-to-severe SLE. Here, we built a population physiology-based pharmacokinetic (PBPK) model of anifrolumab by utilizing the physiochemical properties of anifrolumab, binding kinetics to the Fc gamma neonatal receptor, and target-mediated drug disposition properties. A novel relative transcriptomics approach was employed to determine IFNAR1 expression in tissues (blood, skin, gastrointestinal tract, lungs, and muscle) using mRNA abundances from bioinformatic databases. The IFNAR1 expression and PBPK model were validated by testing their ability to predict clinical pharmacokinetics over a large dose range from different clinical scenarios after subcutaneous and intravenous anifrolumab dosing. The validated PBPK model predicted high unbound local concentrations of anifrolumab in blood, skin, gastrointestinal tract, lungs, and muscle, which exceeded its IFNAR1 dissociation equilibrium constant values. The model also predicted high IFNAR1 occupancy with subcutaneous and intravenous anifrolumab dosing. The model predicted more sustained IFNAR1 occupancy ≥90% with subcutaneous anifrolumab 120 mg once-weekly dosing vs. intravenous 300 mg Q4W dosing. The results informed the dosing of phase III studies of anifrolumab in new indications and present a novel approach to PBPK modeling coupled with relative transcriptomics in simulating pharmacokinetics of therapeutic monoclonal antibodies.

A Physiologically Based Pharmacokinetic Model Relates the Subcutaneous Bioavailability of Monoclonal Antibodies to the Saturation of FcRn-Mediated Recycling in Injection-Site-Draining Lymph Nodes

The bioavailability of a monoclonal antibody (mAb) or another therapeutic protein after subcutaneous (SC) dosing is challenging to predict from first principles, even if the impact of injection site physiology and drug properties on mAb bioavailability is generally understood. We used a physiologically based pharmacokinetic model to predict pre-systemic clearance after SC administration mechanistically by incorporating the FcRn salvage pathway in antigen-presenting cells (APCs) in peripheral lymph nodes, draining the injection site. Clinically observed data of the removal rate of IgG from the arm as well as its plasma concentration after SC dosing were mostly predicted within the 95% confidence interval. The bioavailability of IgG was predicted to be 70%, which mechanistically relates to macropinocytosis in the draining lymph nodes and transient local dose-dependent partial saturation of the FcRn receptor in the APCs, resulting in higher catabolism and consequently less drug reaching the systemic circulation. The predicted free FcRn concentration was reduced to 40-45%, reaching the minimum 1-2 days after the SC administration of IgG, and returned to baseline after 8-12 days, depending on the site of injection. The model predicted the uptake into APCs, the binding affinity to FcRn, and the dose to be important factors impacting the bioavailability of a mAb.

Assessment of Epithelial Lining Fluid Partitioning of Systemically Administered Monoclonal Antibodies in Rats

For systemically administered monoclonal antibodies (mAbs) with pharmacological targets in the epithelial lining fluid (ELF), information on the partitioning of mAb between plasma and ELF is instrumental for dose predictions. Bronchoalveolar lavage (BAL) combined with measurements of urea as indicator of sample dilution is often used to estimate ELF concentrations of a drug. However, unbalanced extraction of mAb and urea could potentially lead to a systematic bias in the back-calculated ELF concentration. In the present study 0.5, 1, or 4 mL phosphate-buffered saline was instilled to lungs of rats to obtain lavage samples after systemic dosing of mAb and tool small molecule (n≥4/group). Furthermore, extraction of urea, mAb and the small molecule was assessed by repeatedly lavaging the lung (n = 4). There was no statistically significant difference in the calculated partitioning into ELF between the evaluated instillation volumes. Repeated BAL demonstrated that urea and the small molecule were extracted from other sources than the ELF. In contrast, there was limited to none in-flow of mAb into the lavage fluid. The unbalanced extraction of urea and mAb could theoretically result in underestimated ELF concentrations and the calculated partitioning of 0.17±0.062 might therefore constitute a lower boundary for the true partitioning.

Toward systems-informed models for biologics disposition: covariates of the abundance of the neonatal Fc Receptor (FcRn) in human tissues and implications for pharmacokinetic modelling

Biologics are a fast-growing therapeutic class, with intertwined pharmacokinetics and pharmacodynamics, affected by the abundance and function of the FcRn receptor. While many investigators assume adequacy of classical models, such as allometry, for pharmacokinetic characterization of biologics, advocates of physiologically-based pharmacokinetics (PBPK) propose consideration of known systems parameters that affect the fate of biologics to enable a priori predictions, which go beyond allometry. The aim of this study was to deploy a systems-informed modelling approach to predict the disposition of Fc-containing biologics. We used global proteomics to quantify the FcRn receptor [p51 and β₂-microglobulin (B2M) subunits] in 167 samples of human tissue (liver, intestine, kidney and skin) and assessed covariates of its expression. FcRn p51 subunit was highest in liver relative to other tissues, and B2M was 1-2 orders of magnitude more abundant than FcRn p51 across all sets. There were no sex-related differences, while higher expression was confirmed in neonate liver compared with adult liver. Trends of expression in liver and kidney indicated a moderate effect of body mass index, which should be confirmed in a larger sample size. Expression of FcRn p51 subunit was approximately 2-fold lower in histologically normal liver tissue adjacent to cancer compared with healthy liver. FcRn mRNA in plasma-derived exosomes correlated moderately with protein abundance in matching liver tissue, opening the possibility of use as a potential clinical tool. Predicted effects of trends in FcRn abundance in healthy and disease (cancer and psoriasis) populations using trastuzumab and efalizumab PBPK models were in line with clinical observations, and global sensitivity analysis revealed endogenous IgG plasma concentration and tissue FcRn abundance as key systems parameters influencing exposure to Fc-conjugated biologics.

Learn-confirm in model-informed drug development: Assessing an immunogenicity quantitative systems pharmacology platform

Immunogenicity against therapeutic proteins frequently causes attrition owing to its potential impact on pharmacokinetics, pharmacodynamics, efficacy, and safety. Predicting immunogenicity is complex because of its multifactorial drivers, including compound properties, subject characteristics, and treatment parameters. To integrate these, the Immunogenicity Simulator was developed using published, predominantly late-stage trial data from 15 therapeutic proteins. This single-blinded evaluation with subject-level data from 10 further monoclonals assesses the Immunogenicity Simulator's credibility for application during the drug development process.

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

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

Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients.

Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations.

Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old.

Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C_min, C_max, and AUC_tau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults.

Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Opportunities and Challenges for PBPK Model of mAbs in Paediatrics and Pregnancy

New drugs may in some cases need to be tested in paediatric and pregnant patients. However, it is difficult to recruit such patients and there are many ethical issues around their inclusion in clinical trials. Modelling and simulation can help to plan well-designed clinical trials with a reduced number of participants and to bridge gaps where recruitment is difficult. Physiologically based pharmacokinetic (PBPK) models for small molecule drugs have been used to aid study design and dose adjustments in paediatrics and pregnancy, with several publications in the literature. However, published PBPK models for monoclonal antibodies (mAb) in these populations are scarce. Here, the current status of mAb PBPK models in paediatrics and pregnancy is discussed. Seven mAb PBPK models published for paediatrics were found, which report good prediction accuracy across a wide age range. No mAb PBPK models for pregnant women have been published to date. Current challenges to the development of such PBPK models are discussed, including gaps in our knowledge of relevant physiological processes and availability of clinical data to verify models. As the availability of such data increases, it will help to improve our confidence in the PBPK model predictive ability. Advantages for using PBPK models to predict mAb PK in paediatrics and pregnancy are discussed. For example, the ability to incorporate ontogeny and gestational changes in physiology, prediction of maternal, placental and foetal exposure and the ability to make predictions from in vitro and preclinical data prior to clinical data being available.

Bone Morphogenetic Protein Signaling in Cancer; Some Topics in the Recent 10 Years

Bone morphogenetic proteins (BMPs), members of the transforming growth factor-β (TGF-β) family, are multifunctional cytokines. BMPs have a broad range of functions, and abnormalities in BMP signaling pathways are involved in cancer progression. BMPs activate the proliferation of certain cancer cells. Malignant phenotypes of cancer cells, such as increased motility, invasiveness, and stemness, are enhanced by BMPs. Simultaneously, BMPs act on various cellular components and regulate angiogenesis in the tumor microenvironment. Thus, BMPs function as pro-tumorigenic factors in various types of cancer. However, similar to TGF-β, which shows both positive and negative effects on tumorigenesis, BMPs also act as tumor suppressors in other types of cancers. In this article, we review important findings published in the recent decade and summarize the pro-oncogenic functions of BMPs and their underlying mechanisms. The current status of BMP-targeted therapies for cancers is also discussed.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

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

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

A population physiologically-based pharmacokinetic model to characterize antibody disposition in pediatrics and evaluation of the model using infliximab

AIMS

In order to better predict the pharmacokinetics (PK) of antibodies in children, and to facilitate dose optimization of antibodies in paediatric patients, there is a need to develop systems PK models that integrate ontogeny-related changes in human physiological parameters.

METHODS

A population-based physiological-based PK (PBPK) model to characterize antibody PK in paediatrics has been developed, by incorporating age-related changes in body weight, organ weight, organ blood flow rate and interstitial volumes in a previously published platform model. The model was further used to perform Monte Carlo simulations to investigate clearance vs. age and dose-exposure relationships for infliximab.

RESULTS

By estimating only one parameter and associated interindividual variability, the model was able to characterize clinical PK of infliximab from two paediatric cohorts (n = 141, 4-19 years) reasonably well. Model simulations demonstrated that only 50% of children reached desired trough concentrations when receiving FDA-labelled dosing regimen for infliximab, suggesting that higher doses and/or more frequent dosing are needed to achieve target trough concentrations of this antibody.

CONCLUSION

The paediatric PBPK model presented here can serve as a framework to characterize the PK of antibodies in paediatric patients. The model can also be applied to other protein therapeutics to advance precision medicine paradigm and optimize antibody dosing regimens in children.

Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper

Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.

Biopharmaceutics 4.0, Advanced Pre-Clinical Development of mRNA-Encoded Monoclonal Antibodies to Immunosuppressed Murine Models

Administration of mRNA against SARS-CoV-2 has demonstrated sufficient efficacy, tolerability and clinical potential to disrupt the vaccination field. A multiple-arm, cohort randomized, mixed blind, placebo-controlled study was designed to investigate the in vivo expression of mRNA antibodies to immunosuppressed murine models to conduct efficacy, safety and bioavailability evaluation. Enabling 4.0 tools we reduced animal sacrifice, while interventions were designed compliant to HARRP and SPIRIT engagement: (a) Randomization, blinding; (b) pharmaceutical grade formulation, monitoring; (c) biochemical and histological analysis; and (d) theoretic, statistical analysis. Risk assessment molded the study orientations, according to the ARRIVE guidelines. The primary target of this protocol is the validation of the research hypothesis that autologous translation of Trastuzumab by in vitro transcribed mRNA-encoded antibodies to immunosuppressed animal models, is non-inferior to classical treatments. The secondary target is the comparative pharmacokinetic assessment of the novel scheme, between immunodeficient and healthy subjects. Herein, the debut clinical protocol, investigating the pharmacokinetic/pharmacodynamic impact of mRNA vaccination to immunodeficient organisms. Our design, contributes novel methodology to guide the preclinical development of RNA antibody modalities by resolving efficacy, tolerability and dose regime adjustment for special populations that are incapable of humoral defense.

Development and verification of an endogenous PBPK model to inform hydrocortisone replacement dosing in children and adults with cortisol deficiency

The goal of hormone replacement is to mirror physiology. Hydrocortisone granules and modified release formulations are being developed to optimise cortisol replacement in the rare disease of adrenal insufficiency. To facilitate clinical development, we built and verified a physiologically based pharmacokinetic (PBPK) model for the endogenous hormone cortisol (hydrocortisone) in healthy adults, and children and adults with adrenal insufficiency. The model predicted immediate-release hydrocortisone pharmacokinetics in adults across the dose range 0.5 to 20 mg, with predicted/observed AUCs within 0.8 to 1.25-fold.  The model also tightly predicted pharmacokinetic parameters for modified-release formulations, with AUCs within 0.8 to 1.25-fold after single and multiple dosing.  Predicted modified-release formulation pharmacokinetics (PK) in 12 to 18-year olds showed PK to be similar to adults. This hydrocortisone PBPK model is a useful tool to predict adult and paediatric pharmacokinetics of both immediate- and modified-release hydrocortisone formulations, and develop clinical dosing regimens.

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

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

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

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

Does Hepatic Impairment Affect the Exposure of Monoclonal Antibodies?

Limited information is available regarding the effect of hepatic impairment (HI) on the pharmacokinetics of monoclonal antibodies (mAbs). The results of an earlier report based on therapeutic proteins, including mAbs, approved through the end of 2012 were inconclusive due to limited HI data available at that time. New HI data for mAbs or antibody-drug conjugates (ADCs; with a focus on the mAb component) available between 2013 and 2018 were evaluated. The investigation indicates there is almost no data for severe HI, limited data for moderate HI, and abundant data for mild HI. A significant exposure decrease was found for several mAbs or ADCs and a trend for decreasing area under the concentration-time curve (AUC) was observed for other mAbs. Multiple potential mechanisms may contribute to the exposure decrease. Dose may need to be adjusted for patients with HI, after taking into account the exposure-response relationships for both efficacy and safety.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

A systems pharmacokinetic/pharmacodynamic model for concizumab to explore the potential of anti-TFPI recycling antibodies

Concizumab is a humanized monoclonal antibody in clinical investigation directed against membrane-bound and soluble tissue factor pathway inhibitor (mTFPI and sTFPI) for treatment of hemophilia. Concizumab displays a non-linear pharmacokinetic (PK) profile due to mTFPI-mediated endocytosis and necessitates a high dose and frequent dosing to suppress the abundant sTFPI, a negative regulator of coagulation. Recycling antibodies that can dissociate bound mTFPI/sTFPI in endosomes for degradation and rescue antibody from degradation have a potential in reducing the dose by extending antibody systemic persistence and sTFPI suppression. We developed a systems PK/pharmacodynamics (PD) model with nested endosome compartments to simulate the effect of decreased antibody binding to mTFPI/sTFPI in endosomes on antibody clearance and sTFPI suppression for exploring the potential of anti-TFPI recycling antibodies in reducing the dose. A dynamic model-building strategy was taken. A reduced PK/PD model without the endosome compartments was developed to optimize unknown target turnover parameters using concizumab PK data. The optimized parameters were then employed in the systems PK/PD model for simulations. The obtained systems PK/PD model adequately described the PK of concizumab in rabbits, monkeys, and humans and the PD in humans. The systems PK/PD model predicted that an anti-TFPI recycling antibody with a 100-fold higher mTFPI/sTFPI dissociation constant in endosomes than concizumab can extend sTFPI suppression from 12 days to 1 month. Thus, the systems PK/PD model provides a quantitative platform for guiding the engineering and translational development of anti-TFPI recycling antibodies.

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

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

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

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

Physiologically-based modeling of monoclonal antibody pharmacokinetics in drug discovery and development

Over the past few decades, monoclonal antibodies (mAbs) have become one of the most important and fastest growing classes of therapeutic molecules, with applications in a wide variety of disease areas. As such, understanding of the determinants of mAb pharmacokinetic (PK) processes (absorption, distribution, metabolism, and elimination) is crucial in developing safe and efficacious therapeutics. In the present review, we discuss the use of physiologically-based pharmacokinetic (PBPK) models as an approach to characterize the in vivo behavior of mAbs, in the context of the key PK processes that should be considered in these models. Additionally, we discuss current and potential future applications of PBPK in the drug discovery and development timeline for mAbs, spanning from identification of potential target molecules to prediction of potential drug-drug interactions. Finally, we conclude with a discussion of currently available PBPK models for mAbs that could be implemented in the drug development process.

Minimal physiologically-based pharmacokinetic model to investigate the effect of pH dependent FcRn affinity and the endothelial endocytosis on the pharmacokinetics of anti-VEGF humanized IgG1 antibody in cynomolgus monkey

In this study, we developed a first minimal physiologically-based pharmacokinetic (mPBPK) model to investigate the complex interaction effects of endocytosis rate/FcRn binding affinity at both acidic/physiological pH on the pharmacokinetics (PK) of the anti-VEGF IgG₁ antibodies. The data used in this study were the PK of the native IgG and humanized anti-VEGF IgG₁ antibodies with a wide range FcRn-binding at both acidic and physiological pH in the cynomolgus monkey. The basic structure of the developed mPBPK models consisted of plasma, tissue and lymph compartments. The tissue compartment was subdivided into vascular, endothelial and interstitial spaces. Non-equilibrium binding mechanism was used to describe the FcRn-IgG interaction in the endosome. The fittings in the final model with three pH systems in the endosome compartment showed a good fit based on the visualization of the fitted graphs and the coefficient of variations of the estimated parameters (CV < 50%). The quantitative endocytosis/FcRn binding affinity PK relationships was constructed using the final model to provide better understanding of complex interaction effects of endocytosis rate and FcRn binding on PK of anti-VEGF IgG₁ antibodies. This result may serve as an important model-based drug discovery platform to guide the design and development of the future generation of anti-VEGF IgG₁ or other therapeutic IgG₁ antibodies. In addition, the mPBPK model developed in cynomolgus monkey was successfully used to predict the PK of the anti-VEGF IgG₁ antibody (bevacizumab) in human subjects.

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

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

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

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

Quantitative translational modeling to facilitate preclinical to clinical efficacy & toxicity translation in oncology

Significant scientific advances in biomedical research have expanded our knowledge of the molecular basis of carcinogenesis, mechanisms of cancer growth, and the importance of the cancer immunity cycle. However, despite scientific advances in the understanding of cancer biology, the success rate of oncology drug development remains the lowest among all therapeutic areas. In this review, some of the key translational drug development objectives in oncology will be outlined. The literature evidence of how mathematical modeling could be used to build a unifying framework to answer these questions will be summarized with recommendations on the strategies for building such a mathematical framework to facilitate the prediction of clinical efficacy and toxicity of investigational antineoplastic agents. Together, the literature evidence suggests that a rigorous and unifying preclinical to clinical translational framework based on mathematical models is extremely valuable for making go/no-go decisions in preclinical development, and for planning early clinical studies.

A Minimal Physiologically Based Pharmacokinetic Model with a Nested Endosome Compartment for Novel Engineered Antibodies

We proposed here a minimal physiologically based pharmacokinetic (mPBPK) model for a group of novel engineered antibodies in mice and humans. These antibodies are designed with altered binding properties of their Fc domain with neonatal Fc receptor (FcRn) or the Fab domain with their cognate targets (recycling antibodies) in acidic endosomes. To enable simulations of such binding features in the change of antibody pharmacokinetics and its target suppression, we nested an endothelial endosome compartment in parallel with plasma compartment based on our previously established mPBPK model. The fluid-phase pinocytosis rate from plasma to endothelial endosomes was reflected by the clearance of antibodies in FcRn dysfunctional humans or FcRn-knockout mice. The endosomal recycling rate of FcRn-bound antibodies was calculated based on the reported endosomal transit time. The nonspecific catabolism in endosomes was fitted using pharmacokinetic data of a human wild-type IgG₁ adalimumab in humans and B21M in human FcRn (hFcRn) transgenic mice. The developed model adequately predicted the pharmacokinetics of infliximab, motavizumab, and an Fc variant of motavizumab in humans and the pharmacokinetics of bevacizumab, an Fc variant of bevacizumab, and a recycling antibody PH-IgG₁ and its non-pH dependent counterpart NPH-IgG₁ in hFcRn transgenic mice. Our proposed model provides a platform for evaluation of the pharmacokinetics and disposition behaviors of Fc-engineered antibodies and recycling antibodies.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Application of Pharmacokinetics Modelling to Predict Human Exposure of a Cationic Liposomal Subunit Antigen Vaccine System

The pharmacokinetics of a liposomal subunit antigen vaccine system composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and the immunostimulatory agent trehalose 6,6-dibehenate (TDB) (8:1 molar ratio) combined with the Ag85B-ESAT-6 (H1) antigen were modelled using mouse in-vivo data. Compartment modelling and physiologically based pharmacokinetics (PBPK) were used to predict the administration site (muscle) and target site (lymph) temporal concentration profiles and factors governing these. Initial estimates using compartmental modelling established that quadriceps pharmacokinetics for the liposome demonstrated a long half-life (22.6 days) compared to the associated antigen (2.62 days). A mouse minimal-PBPK model was developed and successfully predicted quadriceps liposome and antigen pharmacokinetics. Predictions for the popliteal lymph node (PLN) aligned well at earlier time-points. A local sensitivity analysis highlighted that the predicted AUC_muscle was sensitive to the antigen degradation constant k_deg (resulting in a 3-log change) more so than the fraction escaping the quadriceps (f_e) (resulting in a 10-fold change), and the predicted AUC_PLN was highly sensitive to f_e. A global sensitivity analysis of the antigen in the muscle demonstrated that model predictions were within the 50th percentile for predictions and showed acceptable fits. To further translate in-vitro data previously generated by our group, the mouse minimal-PBPK model was extrapolated to humans and predictions made for antigen pharmacokinetics in muscle and PLN. Global analysis demonstrated that both k_deg and f_e had a minimal impact on the resulting simulations in the muscle but a greater impact in the PLN. In summary, this study has predicted the in-vivo fate of DDA:TDB:H1 in humans and demonstrated the roles that formulation degradation and fraction escaping the depot site can play upon the overall depot effect within the site of administration.

Qualitative and quantitative characterization of protein biotherapeutics with liquid chromatography mass spectrometry

In the last decade, the advancement of liquid chromatography mass spectrometry (LC/MS) techniques has enabled their broad application in protein characterization, both quantitatively and qualitatively. Owing to certain important merits of LC/MS techniques (e.g., high selectivity, flexibility, and rapid method development), LC/MS assays are often deemed as preferable alternatives to conventional methods (e.g., ligand-binding assays) for the analysis of protein biotherapeutics. At the discovery and development stages, LC/MS is generally employed for two purposes absolute quantification of protein biotherapeutics in biological samples and qualitative characterization of proteins. For absolute quantification of a target protein in bio-matrices, recent work has led to improvements in the efficiency of LC/MS method development, sample treatment, enrichment and digestion, and high-performance low-flow-LC separation. These advances have enhanced analytical sensitivity, specificity, and robustness. As to qualitative analysis, a range of techniques have been developed to characterize intramolecular disulfide bonds, glycosylation, charge variants, primary sequence heterogeneity, and the drug-to-antibody ratio of antibody drug conjugate (ADC), which has enabled a refined ability to assess product quality. In this review, we will focus on the discussion of technical challenges and strategies of LC/MS-based quantification and characterization of biotherapeutics, with the emphasis on the analysis of antibody-based biotherapeutics such as monoclonal antibodies (mAbs) and ADCs. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:734-754, 2017.

Potential Sources of Inter-Subject Variability in Monoclonal Antibody Pharmacokinetics

Understanding inter-subject variability in drug pharmacokinetics and pharmacodynamics is important to ensure that all patients attain suitable drug exposure to achieve efficacy and avoid toxicity. Inter-subject variability in the pharmacokinetics of therapeutic monoclonal antibodies (mAbs) is generally moderate to high; however, the factors responsible for the high inter-subject variability have not been comprehensively reviewed. In this review, the extent of inter-subject variability for mAb pharmacokinetics is presented and potential factors contributing to this variability are explored and summarised. Disease status, age, sex, ethnicity, body size, genetic polymorphisms, concomitant medication, co-morbidities, immune status and multiple other patient-specific details have been considered. The inter-subject variability for mAb pharmacokinetics most likely depends on the complex interplay of multiple factors. However, studies aimed at investigating the reasons for the inter-subject variability are sparse. Population pharmacokinetic models and physiologically based pharmacokinetic models are useful tools to identify important covariates, aiding in the understanding of factors contributing to inter-subject variability. Further understanding of inter-subject variability in pharmacokinetics should aid in development of dosing regimens that are more appropriate.

Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability

In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 ([Formula: see text]), the convective flow rate of mAb through vascular pores ([Formula: see text]), the endocytic transport rate of mAb through vascular endothelium ([Formula: see text]), the degradation rate of mAb-HER2 complexes ([Formula: see text]) and the concentration of shed HER2 extracellular domain in circulation ([Formula: see text]). [Formula: see text] was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. [Formula: see text] was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability.

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.

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.

Physiologically-Based Pharmacokinetic-Pharmacodynamic Modeling of 1α,25-Dihydroxyvitamin D3 in Mice

1α,25-Dihydroxyvitamin D3 [1,25(OH)2D3] concentrations are regulated by renal CYP27B1 for synthesis and CYP24A1 for degradation. Published plasma and tissue 1,25(OH)2D3 concentrations and mRNA fold change expression of Cyp24a1 and Cyp27b1 following repetitive i.p. injections to C57BL/6 mice (2.5 μg × kg(-1) every 2 days for 4 doses) were fitted with a minimal and full physiologically-based pharmacokinetic-pharmacodynamic models (PBPK-PD). The minimal physiologically-based pharmacokinetic-pharmacodynamic linked model (mPBPK-PD) related Cyp24a1 mRNA fold changes to linear changes in tissue/tissue baseline 1,25(OH)2D3 concentration ratios, whereas the full physiologically-based pharmacokinetic-pharmacodynamic model (PBPK-PD) related measured tissue Cyp24a1 and Cyp27b1 fold changes to tissue 1,25(OH)2D3 concentrations with indirect response, sigmoidal maximal stimulatory effect/maximal inhibitory effect functions. Moreover, the intestinal segregated flow model (SFM) that describes a low and partial intestinal (blood/plasma) flow to enterocytes was nested within both models for comparison with the traditional model for intestine (TM) where the entire flow perfuses the intestine. Both the mPBPK(SFM)-PD and full PBPK(SFM)-PD models described the i.p. plasma and tissue 1,25(OH)2D3 concentrations and fold changes in mRNA expression significantly better than the TM counterparts with F test comparisons. The full PBPK(SFM)-PD fits showed estimates with good precision (lower percentage of coefficient of variation), and the model was more robust in predicting data from escalating i.v. doses (2, 60, and 120 pmol) and the rebound in 1,25(OH)2D3 tissue concentrations after dosing termination. The full PBPK(SFM)-PD model performed the best among the tested models for describing the complex pharmacokinetic-pharmacodynamic interplay among Cyp27b1, Cyp24a1, and 1,25(OH)2D3.

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.

Towards integrative systems pharmacology models in oncology drug development

Quantitative systems pharmacology (QSP) modeling represents an emerging area of value to further streamline knowledge integration and to better inform decision making processes in drug development. QSP models reside at the interface between systems biology models and pharmacological models, yet their concrete implementation still needs to be established further. This review outlines key modeling techniques in both of these areas and to subsequently discuss challenges and opportunities for further integration, in oncology drug development.

Tools for predicting the PK/PD of therapeutic proteins

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

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.