Simplification of complex physiologically based pharmacokinetic models of monoclonal antibodies

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.

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.

Whole-Body Physiologically Based Pharmacokinetic Modeling of Trastuzumab and Prediction of Human Pharmacokinetics

In the present study, we evaluated the pharmacokinetics (PK) of trastuzumab and sought to predict human PK based on animal studies, through the use of optical imaging and a whole-body physiologically based pharmacokinetic (WB-PBPK) modeling approach. The PK study was conducted in 24 mice, where serial blood samples were withdrawn and major organs were isolated after the last blood withdrawal. The drug concentrations in blood and major organs were measured via optical imaging. The WB-PBPK model was constructed using known physiological values including the volumes of major organs and blood/lymphatic flow. The NONMEM software (version 7.3) was used to determine tissue partition coefficients. Using the WB-PBPK model, a clinical trial simulation was performed with reference to human physiological values acquired from the literature. The simulated human PK was then compared with the actual PK observed in the previous study in which healthy male subjects received 6 mg/kg trastuzumab (Herceptin^®) via intravenous route. The ratio of the simulated versus observed area under the concentration-time curve was 1.02 and that of maximal concentration was 0.72. The current study describes the potential synergistic applications of WB-PBPK and optical imaging in human PK prediction based on preclinical data obtained in early-stage drug development.

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

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

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.

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.

An Extended Minimal Physiologically Based Pharmacokinetic Model: Evaluation of Type II Diabetes Mellitus and Diabetic Nephropathy on Human IgG Pharmacokinetics in Rats

Although many studies have evaluated the effects of type 2 diabetes mellitus (T2DM) on the pharmacokinetics (PK) of low molecular weight molecules, there is limited information regarding effects on monoclonal antibodies. Our previous studies have reported significant increases in total (2-4 fold) and renal (100-300 fold) clearance of human IgG, an antibody isotype, in Zucker diabetic fatty (ZDF) rats. Pioglitazone treatment incompletely reversed the disease-related PK changes. The objective of this study was to construct a mechanistic model for simultaneous fitting plasma and urine data, to yield physiologically relevant PK parameters. We propose an extended minimal physiologically based PK (mPBPK) model specifically for IgG by classifying organs as either leaky or tight vascular tissues, and adding a kidney compartment. The model incorporates convection as the primary mechanism of IgG movement from plasma into tissues, interstitial fluid (ISF) in extravascular distribution space, and glomerular filtration rate (GFR), sieving coefficient and fraction reabsorbed in the kidney. The model captured the plasma and urine PK profiles well, and simulated concentrations in ISF. The model estimated a 2-4 fold increase in nonrenal clearance from plasma and 30-120 fold increase in renal clearance with T2DM, consistent with the experimental findings, and these differences in renal clearance were related to changes in GFR, sieving coefficient, and proximal tubular reabsorption. In conclusion, the mPBPK model offers a more relevant approach for analyzing plasma and urine IgG concentration-time data than conventional models and provides insight regarding alterations in distributional and elimination parameters occurring with T2DM.

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.