Selection between Michaelis-Menten and target-mediated drug disposition pharmacokinetic models

Validity conditions of approximations for a target-mediated drug disposition model: A novel first-order approximation and its comparison to other approximations

Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments.

Mechanism-based pharmacokinetic and pharmacodynamic modeling for bispecific antibodies: challenges and opportunities

INTRODUCTION

Unlike conventional antibodies, bispecific antibodies (bsAbs) are engineered antibody- or antibody fragment-based molecules that can simultaneously recognize two different epitopes or antigens. Over the past decade, there has been an explosion of bsAbs being developed across therapeutic areas. Development of bsAbs presents unique challenges and mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling has served as a powerful tool to optimize their development and realize their clinical utility.

AREAS COVERED

In this review, the guiding principles and case examples of how fit-for-purpose, mechanism-based PK/PD models have been applied to answer questions commonly encountered in bsAb development are presented. Such models characterize the key pharmacological elements of bsAbs, and they can be utilized for model-informed drug development. We also include the discussion of challenges, knowledge gaps and future direction for such models.

EXPERT OPINION

Mechanistic PK/PD modeling is a powerful tool to support the development of bsAbs. These models can be extrapolated to predict treatment outcomes based on mechanisms of action (MoA) and clinical observations to form positive learn-and-confirm cycles during drug development, due to their abilities to differentiate system- and drug-specific parameters. Meanwhile, the models should keep being adapted according to novel drug design and MoA, providing continuous opportunities for model-informed drug development.

Pharmacodynamic-Mediated Drug Disposition (PDMDD) Model of Daratumumab Monotherapy in Patients with Multiple Myeloma

BACKGROUND AND OBJECTIVE

We aimed to quantify the daratumumab concentration- and CD38 dynamics-dependent pharmacokinetics using a pharmacodynamic mediated disposition model (PDMDD) in patients with multiple myeloma (MMY) following daratumumab IV or SC monotherapy. Daratumumab, a human IgG monoclonal antibody targeting CD38 with a direct on-tumor and immunomodulatory mechanism of action, has been approved to treat patients with multiple myeloma (MM).

METHODS

In total, 7788 daratumumab plasma samples from 850 patients with diagnosis of MMY were used. The serum concentration-time data of daratumumab were analysed using nonlinear mixed-effects modeling with NONMEM^®. The PDMDD with quasi steady-state approximation (QSS) was compared to the previously developed Michaelis-Menten (MM) approximation with respect to the parameter estimates, the goodness-of-fit plots and prediction-corrected visual predictive check, as well as model-based simulations. The effect of patients' covariates on daratumumab pharmacokinetics was also investigated.

RESULTS

The QSS approximation characterized the concentration- and CD38 dynamics-dependency of daratumumab pharmacokinetics within the doses ranging from 0.1 to 24 mg/kg after IV administration and 1200 and 1800 mg after SC administration in patients with MMY, mechanistically describing the binding of daratumumab and CD38, the internalization of the daratumumab-CD38 complex and the CD38 turnover. Compared to the previously developed MM approximation, the MM approximation with the non-constant total target and dose-correction provided substantial improvement of the model fit, but it was still not as good as the QSS approximation. The effect of the previously identified covariates as well as the newly identified covariate (baseline M protein) on daratumumab pharmacokinetics was confirmed, but the magnitude of the effect was deemed not clinically relevant.

CONCLUSIONS

Accounting for the CD38 turnover and its binding capacity to daratumumab, the QSS approximation provided a mechanistic interpretation of daratumumab PK parameters and consequently well described the concentration- and CD38 dynamics-dependency of daratumumab pharmacokinetics. CLINICAL STUDIES INCLUDED IN THE ANALYSIS WERE REGISTERED WITH THE NCT NUMBER BELOW AT HTTP://WWW.

CLINICALTRIALS

GOV : MMY1002 (ClinicalTrials.gov: NCT02116569), MMY1003 (NCT02852837), MMY1004 (NCT02519452), MMY1008 (NCT03242889), GEN501 (NCT00574288), MMY2002 (NCT01985126), MMY3012 (NCT03277105).

Physiologically-Based Pharmacokinetic Modeling of Omalizumab to Predict the Pharmacokinetics and Pharmacodynamics in Pediatric Patients

Omalizumab is widely used in clinical practice; however, knowledge gaps in the dosage of omalizumab for children aged 2-6 years with moderate-to-severe persistent allergic asthma have been identified. The aim of this study was to explore dosing regimens for moderately-to-severely allergic pediatric patients aged 2-6 years. The physiologically-based pharmacokinetic (PBPK) model of omalizumab was developed and verified in adult patients, extrapolated to pediatric patients, and simulated for omalizumab by adding two observation chambers (free IgE and total IgE). The simulation results showed that the fold errors of the predicted and observed values of the area under the curve (AUC) and peak plasma concentration (C_max ) were between 0.5 and 2.0, and the average folding error and the absolute average folding error values for all concentration-time data points were 1.09 and 1.48, respectively. The PBPK model combined with pharmacokinetic/pharmacodynamic analysis of omalizumab demonstrated that both the model-derived dose and the original dose could control the average free IgE of 2-6-year-old children with moderate-to-severe allergic asthma below 25 ng/mL, and some of the model-derived doses were lower. This conclusion provides a basis for the selection of dosage in clinical practice reference.

Systems model identifies baseline cytokine concentrations as potential predictors of rheumatoid arthritis inflammatory response to biologics

BACKGROUND AND PURPOSE

Circulating cytokines are central pathological mediators of inflammatory autoimmune diseases like rheumatoid arthritis (RA). Immunological diversity in patients might contribute to inadequate responses to biological drugs. To address this therapeutic challenge, we developed a mathematical model that simultaneously describes temporal patterns of drug disposition for several biologics and their corresponding targeted cytokines, which were linked to triggering inflammatory responses.

EXPERIMENTAL APPROACH

A modeling framework was applied to RA-relevant cytokines regulating C-reactive protein (CRP) as an inflammatory marker. Clinical data were extracted from the literature for anakinra, canakinumab, infliximab, secukinumab, and tocilizumab, along with their corresponding cytokines: interleukin-1 receptor antagonist, IL-1β, tumor necrosis factor α (TNFα), IL-17A, and IL-6 receptor (IL-6R). Based on prior knowledge of regulatory mechanisms, cytokines were integrated with CRP profiles.

KEY RESULTS

The model well captured all serum concentration-time profiles of cytokines and CRP ratios to respective baselines following drug treatment with good precision. On external validation, reasonable model-performance on CRP dynamics, including rebound effects, was confirmed with clinical data not used in model development. Model-based simulations demonstrated that serum infliximab concentrations were accurately recapitulated in both a dose- and baseline TNFα-dependent manner. Furthermore, high baseline profiles of both IL-1β and/or targeted cytokines could be predictors of poor responses to biologics targeting TNFα and IL-6R, although the impact of IL-1β must be carefully interpreted.

CONCLUSIONS AND IMPLICATION

Our model provides a quantitative platform to guide targeting and dosing strategies, including combination and/or sequential therapy, according to distinct baseline cytokine patterns in RA patients.

An Extended Model Including Target Turnover, Ligand-Target Complex Kinetics, and Binding Properties to Describe Drug-Receptor Interactions

Since the beginning of this century, target-mediated drug disposition has become a central concept in modeling drug action in drug development. It combines a range of processes, such as turnover, protein binding, internalization, and non-specific elimination, and often serves as a nucleus of more complex pharmacokinetic models. It is simple enough to comprehend but complex enough to be able to describe a wide range of phenomena and data sets. However, the complexity comes at a price: many parameters. In this chapter, we present an overview of the temporal development of the compounds involved after different types of drug doses and offer convenient handles for dissecting data sets in a sophisticated manner in order to estimate the values of these parameters, such as rate constants and pertinent concentrations.

Population Pharmacokinetic Modeling of Inebilizumab in Subjects with Neuromyelitis Optica Spectrum Disorders, Systemic Sclerosis, or Relapsing Multiple Sclerosis

Background and Objective

Inebilizumab is a humanized, affinity-optimized, afucosylated immunoglobulin (Ig)-G1κ monoclonal antibody that binds to CD19, resulting in effective depletion of peripheral B cells. It is being developed to treat various autoimmune diseases, including neuromyelitis optica spectrum disorders (NMOSD), systemic sclerosis (SSc), and relapsing multiple sclerosis (MS).

Methods

Pharmacokinetic data from a pivotal study in adult subjects with NMOSD and two early-stage studies in subjects with SSc or relapsing MS were pooled and simultaneously analyzed using a population approach.

Results

Upon intravenous administration, the pharmacokinetics of inebilizumab were adequately described by a two-compartment model with parallel first-order and time-dependent nonlinear elimination pathways. An asymptotic nonlinear elimination suggests that inebilizumab undergoes receptor (CD19)-mediated clearance. The estimated systemic clearance (CL) of the first-order elimination pathway (0.188 L/day) and the volume of distribution (V_d) (5.52 L) were typical for therapeutic immunoglobulins. The elimination half-life was approximately 18 days. The maximum velocity (V_max) of the nonlinear elimination pathway decreased with time, presumably due to the depletion of B cells upon inebilizumab administration. As for other therapeutic monoclonal antibodies, the CL and V_d of inebilizumab increased with body weight.

Conclusions

The presence of antidrug antibodies, status of hepatic or renal function, and use of small-molecule drugs commonly used by subjects with NMOSD had no clinically relevant impact on the pharmacokinetics of inebilizumab. The nonlinear elimination pathway at the 300 mg therapeutic dose level is not considered clinically relevant.

Comparison of Various Approaches to Translate Non-Linear Pharmacokinetics of Monoclonal Antibodies from Cynomolgus Monkey to Human

BACKGROUND AND OBJECTIVES

The prediction of pharmacokinetics of monoclonal antibodies (mAbs) exhibiting non-linear pharmacokinetics in preclinical species to human is challenging, and very limited scientific work has been published in this field of research. Therefore, we have conducted an elaborate comparative assessment to determine the most reliable preclinical to clinical scaling strategy for mAbs with non-linear pharmacokinetics.

METHODS

We have compared three different scaling approaches to predict human pharmacokinetics from cynomolgus monkey. In the first approach, cynomolgus monkey pharmacokinetic parameters estimated using a two-compartment model with parallel linear and non-linear elimination were allometrically scaled to simulate human pharmacokinetics. In the second approach, allometric exponents were integrated with a minimal physiologically based pharmacokinetic (mPBPK) model to translate human pharmacokinetics. In the third approach, we have employed a species time-invariant method, wherein a two-compartment model with parallel linear and non-linear elimination was used as a framework model for simulation of the human profile.

RESULTS

Human exposure parameters projected by an integrated allometric method were only within two fold for approximately 45-70% of predictions at different doses of five mAbs evaluated, while approximately 70-80% of Cmax and AUC predictions by integrated mPBPK modelling as well as the species time-invariant method were within two-fold error. The average fold error for clearance predictions by the integrated mPBPK method was 1.10-1.45 fold, whilst for the species time-variant and integrated allometric methods, the average fold error was between 1.04 and 1.37 fold and 1.24 and 2.13 fold, respectively.

CONCLUSIONS

Our findings suggest that the species time-variant method and mPBPK proposed by us can be employed to reliably translate non-linear pharmacokinetics of mAbs from cynomolgus monkey to human.

Simple Approach to Accurately Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies after Subcutaneous Injection in Humans

BACKGROUND AND OBJECTIVE

The subcutaneous injection of therapeutic monoclonal antibodies is increasingly used in the treatment of several diseases because of its convenience. Thus, a simple and accurate method of predicting the pharmacokinetics of monoclonal antibodies after a subcutaneous injection in humans would be a valuable tool for preclinical/clinical development. In this study, we investigated whether the pharmacokinetics of monoclonal antibodies after a subcutaneous injection in humans can be predicted using only pharmacokinetic data after a subcutaneous injection in cynomolgus monkeys.

METHODS

First, we compared the accuracy of three approaches to predict the apparent clearance (CL/F) and apparent volume of distribution (V_d/F) for 15 monoclonal antibodies in humans (1) allometric scaling from cynomolgus monkeys; (2) geometric mean of reported values in humans; (3) estimation from a regression line based on CL/F in humans [only V_d/F]). Then, using the predicted CL/F and V_d/F, and the geometric mean of reported absorption rate constant of mAbs the plasma concentration-time profiles of 13 monoclonal antibodies after subcutaneous injections in humans were simulated.

RESULTS

In a comparison of approaches, the first approach showed the best prediction accuracy for CL/F with an exponent of 0.9 (100% and 73% prediction accuracy within 2- and 1.5-fold of the observed value),and the third approach was the best for V_d/F (100% prediction accuracy within 1.5-fold of the observed value). Next, using the first approach for CL/F and the third approach for V_d/F, we accurately predicted the plasma concentration-time profiles of 13 monoclonal antibodies after subcutaneous injections in humans.

CONCLUSION

This simple approach can be applied in preclinical and clinical settings to predict the pharmacokinetics of monoclonal antibodies after subcutaneous injections in humans. Further, this approach requires only CL/F after a subcutaneous injection in cynomolgus monkeys, contributing to animal welfare and reducing costs.

A clinical population pharmacokinetic/pharmacodynamic model for BIIB059, a monoclonal antibody for the treatment of systemic and cutaneous lupus erythematosus

A population pharmacokinetic/pharmacodynamic (popPK/PD) model for BIIB059 (anti-blood dendritic cell antigen 2 [anti-BDCA2]), a humanized immunoglobulin G1 monoclonal antibody currently under development for the treatment of SLE and CLE, is presented. BIIB059 binds BDCA2, a plasmacytoid dendritic cell (pDC)-specific receptor that inhibits the production of IFN-I and other inflammatory mediators when ligated. Phase 1 PK and PD data of healthy adult volunteers (HV, n = 87) and SLE subjects (n = 22) were utilized for the development of the popPK/PD model. The data included single and multiple dosing of intravenous and subcutaneous BIIB059. BDCA2 internalization (PD marker) was measured for all subjects by monitoring reduction of BDCA2 on pDC cell surface and used for development of the popPD model. A two-compartment popPK model with linear plus non-linear elimination was found to best describe BIIB059 PK. BDCA2 levels were best captured using an indirect response model with stimulation of the elimination of BDCA2. Clearance in SLE subjects was 25% higher compared to HV (6.87 vs 5.52 mL/h). Bodyweight was identified as only other covariate on clearance and central volume. The estimates of EC₅₀ and E_max were 0.35 μg/mL and 8.92, respectively. No difference in EC₅₀ and E_max was observed between SLE and HV. The popPK/PD model described the data accurately, as evaluated by pcVPCs and bootstrap. The presented popPK/PD model for BIIB059 provides valuable insight into the dynamics and dose-response relationship of BIIB059 for the treatment of SLE and CLE and was used to guide dose selection for the Phase 2 clinical study (NCT02847598).

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.

Dose Correction for a Michaelis-Menten Approximation of a Target-Mediated Drug Disposition Model with a Multiple Intravenous Dosing Regimens

This study aimed to develop a method for implementing dose correction in a Michaelis-Menten (M-M) approximation of a target-mediated drug disposition (TMDD) model with multiple intravenous (IV) bolus administrations. We derived the formula of a correction factor (Fcorr) for each dose in a multiple IV bolus dosing regimens for M-M model. Fcorr depends on the residual free drug amount prior IV bolus dosing event and dose amount. We conducted a stochastic simulation and estimation (SSE) exercise based on therapeutic antibody PK parameters to evaluate the effect of Fcorr on parameter estimation. Previously published clinical PK data of recombinant human erythropoietin (rHuEPO) from four clinical trials in healthy subjects receiving multiple IV bolus doses were analyzed by both M-M model with and without dose correction (MMC and MMNC) as well as the rapid-binding/quasi-steady-state (RB/QSS) TMDD models. Our results showed that MMNC introduced bias to fixed-effect parameter estimates and overestimated random-effect variables. Compared with MMC, MMNC was not able to adequately characterize the nonlinearity in the PK data of antibody and rHuEPO. The MMC-based simulation demonstrated that thricely weekly 10 IU/kg rHuEPO dosing regimen yielded Fcorr = 0.5. This result suggested that the lower-than-expected exposure for rHuEPO at low dose is due to target binding. An M-M approximation of the TMDD model should include a dose correction to avoid model misfitting and potential bias in the estimated PK parameters.

Pharmacokinetics of the Monocarboxylate Transporter 1 Inhibitor AZD3965 in Mice: Potential Enterohepatic Circulation and Target-Mediated Disposition

PURPOSE

To evaluate the pharmacokinetics (PK) of the monocarboxylate transporter 1 (MCT1) inhibitor AZD3965 in mice after IV and oral administration and to develop mechanistic PK models to assess the potential enterohepatic circulation (EHC) and target-mediated drug disposition (TMDD) of AZD3965.

METHODS

Female BALB/c mice were administered AZD3965 by IV injection (10, 50 and 100 mg/kg) or oral gavage (100 mg/kg). Plasma samples were analyzed using LC/MS/MS, and PK parameters determined by compartmental and non-compartmental analyses.

RESULTS

AZD3965 exhibited a large volume of distribution and rapid oral absorption, with a high oral bioavailability. Prominent reentry peaks were observed after both oral and IV administration, suggesting potential EHC of AZD3965 or of a potential glucuronide conjugate. The dose-dependent studies indicated greater than proportional increases in exposure, an increase in the terminal half-life, and decrease in clearance and volume of distribution with increasing IV doses, indicating nonlinear pharmacokinetics and potential TMDD of AZD3965. Mechanistic compartmental models were developed to characterize the complex pharmacokinetics of AZD3965.

CONCLUSIONS

The current study represents the first comprehensive report of the pharmacokinetics of AZD3965 in mice, indicating the potential contribution of EHC and TMDD in the disposition of AZD3965.

Concept of Pharmacologic Target-Mediated Drug Disposition in Large-Molecule and Small-Molecule Compounds

Target-mediated drug disposition (TMDD) is a term to describe a nonlinear pharmacokinetic (PK) phenomenon that is caused by high-affinity binding of a compound to its pharmacologic targets. As the interaction between a drug and its pharmacologic target belongs to the process of pharmacodynamics (PD), TMDD can be viewed as a consequence of "PD affecting PK." Although there are numerous TMDD-related articles in the literature, most of them focus on characterizing TMDD using various mathematical models, which may not be suitable for those readers who have little interest in mathematical modeling and only want to have an understanding of the basic concept. The goal of this review is to serve as a "primer" on TMDD. This review explains (1) how TMDD happens; (2) why large-molecule and small-molecule compounds exhibiting TMDD demonstrate substantially different nonlinear PK behaviors; (3) what nonlinear PK profiles look like in large-molecule and small-molecule compounds exhibiting TMDD, using pegfilgrastim, erythropoietin, ABT-384, and linagliptin as case examples; and (4) how to identify whether the nonlinear PK of a compound is because of TMDD.

Population Pharmacokinetics of Alemtuzumab (Campath) in Pediatric Hematopoietic Cell Transplantation: Towards Individualized Dosing to Improve Outcome

BACKGROUND AND OBJECTIVE

Alemtuzumab (Campath^®) is used to prevent graft-versus-host disease and graft failure following pediatric allogeneic hematopoietic cell transplantation. The main toxicity includes delayed immune reconstitution, subsequent viral reactivations, and leukemia relapse. Exposure to alemtuzumab is highly variable upon empirical milligram/kilogram dosing.

METHODS

A population pharmacokinetic (PK) model for alemtuzumab was developed based on a total of 1146 concentration samples from 206 patients, aged 0.2-19 years, receiving a cumulative intravenous dose of 0.2-1.5 mg/kg, and treated between 2003 and 2015 in two centers.

RESULTS

Alemtuzumab PK were best described using a two-compartment model with a parallel saturable and linear elimination pathway. The linear clearance pathway, central volume of distribution, and intercompartmental distribution increased with body weight. Blood lymphocyte counts, a potential substrate for alemtuzumab, did not impact clearance.

CONCLUSION

The current practice with uniform milligram/kilogram doses leads to highly variable exposures in children due to the non-linear relationship between body weight and alemtuzumab PK. This model may be used for individualized dosing of alemtuzumab.

Population Pharmacokinetics of Sarilumab in Patients with Rheumatoid Arthritis

BACKGROUND AND OBJECTIVE

Sarilumab binds to the interleukin-6 receptor with high affinity, inhibiting cis and trans signaling by interleukin-6. Sarilumab has demonstrated efficacy and safety in patients with rheumatoid arthritis. The objective of this study was to develop a population-pharmacokinetic model using data from 1770 patients with rheumatoid arthritis across phase I-III studies.

METHODS

Potential covariates were identified using a stepwise forward-addition and backward-deletion strategy, and the final model was evaluated by visual predictive check and bootstrap methods.

RESULTS

Sarilumab pharmacokinetics is described by a two-compartment model with first-order absorption and parallel linear and nonlinear Michaelis-Menten elimination. A subcutaneous dose of sarilumab 200 mg every 2 weeks resulted in more pronounced saturation of the nonlinear clearance pathway over the dosing interval than 150 mg every 2 weeks. Steady-state exposure (area under the plasma concentration-time curve from day 0 to day 14) increased twofold with dose escalation from 150 to 200 mg every 2 weeks. Body weight, anti-drug antibody status, sarilumab drug product, sex, creatinine clearance, albumin, and baseline C-reactive protein levels were identified as significant covariates according to the predefined statistical significance criteria in stepwise covariate searches. The main intrinsic source of pharmacokinetic variability in exposure was body weight. Compared with a typical 71-kg patient, the area under the plasma concentration-time curve from day 0 to day 14 was 20-23% lower for an 83-kg patient and 20-25% higher for a 62-kg patient.

CONCLUSIONS

These findings, combined with the safety and efficacy data, indicated limited clinical relevance of body-weight effect on sarilumab exposure. No adjustment in sarilumab dose is required for body weight or any other demographics assessed.

Comparing Model Performance in Characterizing the PK/PD of the Anti-Myostatin Antibody Domagrozumab

Modeling and simulation provides quantitative information on target coverage for dose selection. Optimal model selection often relies on fit criteria and is not necessarily mechanistically driven. One such case is discussed where healthy volunteer data of an anti‐myostatin monoclonal antibody domagrozumab were used to develop different target‐mediated drug disposition models; a quasi‐steady state (QSS) rapid binding approximation model, a Michaelis−Menten (MM)‐binding kinetics (MM‐BK) model, and an MM‐indirect response (MM‐IDR) model. Whereas the MM‐BK model was identified as optimal in fitting the data, with all parameters estimated with high precision, the QSS model also converged but was not able to capture the nonlinear decline. Although the least mechanistic model, MM‐IDR, had the lowest objective function value, the MM‐BK model was further developed as it provided a reasonable fit and allowed simulations regarding growth differentiation factor‐8 target coverage for phase II dose selection with sufficient certainty to allow for testing of the underlying mechanistic assumptions.

Population Pharmacokinetic Modeling of Olaratumab, an Anti-PDGFRα Human Monoclonal Antibody, in Patients with Advanced and/or Metastatic Cancer

Background and Objectives

Olaratumab is a recombinant human monoclonal antibody that binds to platelet-derived growth factor receptor-α (PDGFRα). In a randomized phase II study, olaratumab plus doxorubicin met its predefined primary endpoint for progression-free survival and achieved a highly significant improvement in overall survival versus doxorubicin alone in patients with advanced or metastatic soft tissue sarcoma (STS). In this study, we characterize the pharmacokinetics (PKs) of olaratumab in a cancer patient population.

Methods

Olaratumab was tested at 15 or 20 mg/kg in four phase II studies (in patients with nonsmall cell lung cancer, glioblastoma multiforme, STS, and gastrointestinal stromal tumors) as a single agent or in combination with chemotherapy. PK sampling was performed to measure olaratumab serum levels. PK data were analyzed by nonlinear mixed-effect modeling techniques using NONMEM^®.

Results

The PKs of olaratumab were best described by a two-compartment PK model with linear clearance (CL). Patient body weight was found to have a significant effect on both CL and central volume of distribution (V₁), whereas tumor size significantly affected CL. A small subset of patients developed treatment-emergent anti-drug antibodies (TE-ADAs); however, TE-ADAs did not have any effect on CL or PK time course of olaratumab. There was no difference in the PKs of olaratumab between patients who received olaratumab as a single agent or in combination with chemotherapy.

Conclusion

The PKs of olaratumab were best described by a model with linear disposition. Patient body weight and tumor size were found to be significant covariates. The PKs of olaratumab were not affected by immunogenicity or chemotherapeutic agents.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-017-0562-0) contains supplementary material, which is available to authorized users.

Prediction of non-linear pharmacokinetics in humans of an antibody-drug conjugate (ADC) when evaluation of higher doses in animals is limited by tolerability: Case study with an anti-CD33 ADC

For antibody-drug conjugates (ADCs) that carry a cytotoxic drug, doses that can be administered in preclinical studies are typically limited by tolerability, leading to a narrow dose range that can be tested. For molecules with non-linear pharmacokinetics (PK), this limited dose range may be insufficient to fully characterize the PK of the ADC and limits translation to humans. Mathematical PK models are frequently used for molecule selection during preclinical drug development and for translational predictions to guide clinical study design. Here, we present a practical approach that uses limited PK and receptor occupancy (RO) data of the corresponding unconjugated antibody to predict ADC PK when conjugation does not alter the non-specific clearance or the antibody-target interaction. We used a 2-compartment model incorporating non-specific and specific (target mediated) clearances, where the latter is a function of RO, to describe the PK of anti-CD33 ADC with dose-limiting neutropenia in cynomolgus monkeys. We tested our model by comparing PK predictions based on the unconjugated antibody to observed ADC PK data that was not utilized for model development. Prospective prediction of human PK was performed by incorporating in vitro binding affinity differences between species for varying levels of CD33 target expression. Additionally, this approach was used to predict human PK of other previously tested anti-CD33 molecules with published clinical data. The findings showed that, for a cytotoxic ADC with non-linear PK and limited preclinical PK data, incorporating RO in the PK model and using data from the corresponding unconjugated antibody at higher doses allowed the identification of parameters to characterize monkey PK and enabled human PK predictions.

Reduced and optimized trial designs for drugs described by a target mediated drug disposition model

Monoclonal antibodies against soluble targets are often rich and include the sampling of multiple analytes over a lengthy period of time. Predictive models built on data obtained in such studies can be useful in all drug development phases. If adequate model predictions can be maintained with a reduced design (e.g. fewer samples or shorter duration) the use of such designs may be advocated. The effect of reducing and optimizing a rich design based on a published study for Omalizumab (OMA) was evaluated as an example. OMA pharmacokinetics were characterized using a target-mediated drug disposition model considering the binding of OMA to free IgE and the subsequent formation of an OMA–IgE complex. The performance of the reduced and optimized designs was evaluated with respect to: efficiency, parameter uncertainty and predictions of free target. It was possible to reduce the number of samples in the study by 30% while still maintaining an efficiency of almost 90%. A reduction in sampling duration by two-thirds resulted in an efficiency of 75%. Omission of any analyte measurement or a reduction of the number of dose levels was detrimental to the efficiency of the designs (efficiency ≤ 51%). However, other metrics were, in some cases, relatively unaffected, showing that multiple metrics may be needed to obtain balanced assessments of design performance.

Translational Pharmacokinetic/Pharmacodynamic Characterization and Target-Mediated Drug Disposition Modeling of an Anti-Tissue Factor Pathway Inhibitor Antibody, PF-06741086

Tissue factor pathway inhibitor (TFPI) exhibits multiple isoforms, which are known to present in multiple locations such as plasma, endothelium, and platelets. TFPI is an endogenous negative modulator of the coagulation pathway, and therefore, neutralization of TFPI function can potentially increase coagulation activity. A human monoclonal antibody, PF-06741086, which interacts with all isoforms of TFPI is currently being tested in clinic for treating hemophilia patients with and without inhibitors. To support clinical development of PF-06741086, pharmacokinetics (PK) and pharmacodynamics of PF-06741086 were characterized in monkeys. In addition, a mechanistic model approach was used to estimate PK parameters in monkeys and simulate PK profiles in human. The results show that PF-06741086 exhibited target-mediated drug disposition and had specific effects on various hemostatic markers including diluted prothrombin time, thrombin generation, and thrombin-antithrombin complex in monkeys after administration. The model-predicted and observed human exposures were compared retrospectively, and the result indicates that the exposure prediction was reasonable within less than 2-fold deviation. This study demonstrated in vivo efficacy of PF-06741086 in monkeys and the utility of a rational mechanistic approach to describe PK for a monoclonal antibody with complex target binding.

In vivo potency revisited - Keep the target in sight

Potency is a central parameter in pharmacological and biochemical sciences, as well as in drug discovery and development endeavors. It is however typically defined in terms only of ligand to target binding affinity also in in vivo experimentation, thus in a manner analogous to in in vitro studies. As in vivo potency is in fact a conglomerate of events involving ligand, target, and target-ligand complex processes, overlooking some of the fundamental differences between in vivo and in vitro may result in serious mispredictions of in vivo efficacious dose and exposure. The analysis presented in this paper compares potency measures derived from three model situations. Model A represents the closed in vitro system, defining target binding of a ligand when total target and ligand concentrations remain static and constant. Model B describes an open in vivo system with ligand input and clearance (Cl_(L)), adding in parallel to the turnover (k_syn, k_deg) of the target. Model C further adds to the open in vivo system in Model B also the elimination of the target-ligand complex (k_e(RL)) via a first-order process. We formulate corresponding equations of the equilibrium (steady-state) relationships between target and ligand, and complex and ligand for each of the three model systems and graphically illustrate the resulting simulations. These equilibrium relationships demonstrate the relative impact of target and target-ligand complex turnover, and are easier to interpret than the more commonly used ligand-, target- and complex concentration-time courses. A new potency expression, labeled L₅₀, is then derived. L₅₀ is the ligand concentration at half-maximal target and complex concentrations and is an amalgamation of target turnover, target-ligand binding and complex elimination parameters estimated from concentration-time data. L₅₀ is then compared to the dissociation constant K_d (target-ligand binding affinity), the conventional Black & Leff potency estimate EC₅₀, and the derived Michaelis-Menten parameter K_m (target-ligand binding and complex removal) across a set of literature data. It is evident from a comparison between parameters derived from in vitro vs. in vivo experiments that L₅₀ can be either numerically greater or smaller than the K_d (or K_m) parameter, primarily depending on the ratio of k_deg-to-k_e(RL). Contrasting the limit values of target R and target-ligand complex RL for ligand concentrations approaching infinity demonstrates that the outcome of the three models differs to a great extent. Based on the analysis we propose that a better understanding of in vivo pharmacological potency requires simultaneous assessment of the impact of its underlying determinants in the open system setting. We propose that L₅₀ will be a useful parameter guiding predictions of the effective concentration range, for translational purposes, and assessment of in vivo target occupancy/suppression by ligand, since it also encompasses target turnover - in turn also subject to influence by pathophysiology and drug treatment. Different compounds may have similar binding affinity for a target in vitro (same K_d), but vastly different potencies in vivo. L₅₀ points to what parameters need to be taken into account, and particularly that closed-system (in vitro) parameters should not be first choice when ranking compounds in vivo (open system).

Population pharmacokinetics of exenatide

AIM

The aim of the present analysis was to develop a core population pharmacokinetic model for the pharmacokinetic properties of immediate-release (IR) exenatide, which can be used in subsequent analyses of novel sustained-release formulations.

METHODS

Data from eight clinical trials, evaluating a wide range of doses and different administration routes, were available for analysis. All modelling and simulations were conducted using the nonlinear mixed-effect modelling program NONMEM. External model validation was performed using data from the phase III clinical trials programme through standard visual predictive checks.

RESULTS

The pharmacokinetics of IR exenatide was described by a two-compartment model, and the absorption of subcutaneous exenatide was described with a sequential zero-order rate constant followed by a saturable nonlinear absorption process. Drug elimination was characterized by two parallel routes (linear and nonlinear), with significant relationships between renal function and the linear elimination route, and between body weight and volume of distribution. For a subject with normal renal function, the linear clearance was estimated to be 5.06 l hr^-1 . The nonlinear elimination was quantified with a Michaelis-Menten constant (K_m ) of 567 pg ml^-1 and a maximum rate of metabolism (V_max ) of 1.6 μg h^-1 . For subcutaneous administration, 37% of the subcutaneous dose is absorbed via the zero-order process, and the remaining 63% via the nonlinear pathway.

CONCLUSIONS

The present analysis provides a comprehensive population pharmacokinetic model for exenatide, expanding the elimination process to include both linear and nonlinear components, providing a suitable platform for a broad range of concentrations and patient conditions that can be leveraged in future modelling efforts of sustained-release exenatide formulations.

Population pharmacokinetic and pharmacodynamic analysis of BIIB023, an anti-TNF-like weak inducer of apoptosis (anti-TWEAK) monoclonal antibody

AIMS

Tumour necrosis factor-like weak inducer of apoptosis (TWEAK) is implicated in the pathogenesis of lupus nephritis. This study evaluated the pharmacokinetics, using the population approach, and pharmacodynamics of BIIB023, an anti-TWEAK monoclonal antibody, in healthy Chinese, Japanese and Caucasian volunteers.

METHODS

In this single-dose, randomized, double-blind, phase 1 study of BIIB023 in healthy volunteers, BIIB023 was administered by intravenous infusion (3 or 20 mg kg(-1) ) on Day 1; follow-up occurred through Day 71. BIIB023 serum concentration was measured using a validated enzyme-linked immunosorbent assay; BIIB023 concentration-time data were subjected to noncompartmental analysis. Population pharmacokinetic analysis was performed using data from this study and a prior phase 1 study of BIIB023 in subjects with rheumatoid arthritis. Soluble TWEAK and

TWEAK

BIIB023 complex were evaluated.

RESULTS

There were no differences in BIIB023 pharmacokinetics requiring dose adjustment among the three ethnic groups or between healthy volunteers and arthritis patients. BIIB023 central compartment volume (3050 ml) and clearance (7.42 ml h(-1) ) were comparable to those observed for other monoclonal antibody drugs. BIIB023 serum exposure increased in a dose-dependent manner in all groups, but not in direct proportion to dose level; at concentrations below ~10 μg ml(-1) , nonlinear clearance was observed. Soluble TWEAK levels decreased to below the level of quantitation after BIIB023 treatment, with concomitant changes in

TWEAK

BIIB023 complex levels.

CONCLUSIONS

No clinically meaningful differences were observed in BIIB023 pharmacokinetic and pharmacodynamic properties in healthy Chinese, Japanese and Caucasian volunteers; pharmacodynamic measures suggested target engagement. TWEAK may be an attractive therapeutic target for lupus nephritis treatment.

FG-3019, a Human Monoclonal Antibody Recognizing Connective Tissue Growth Factor, is Subject to Target-Mediated Drug Disposition

Purpose

To evaluate and model the pharmacokinetic and pharmacodynamic behavior in rats of FG-3019, a human monoclonal antibody targeting connective tissue growth factor (CTGF).

Methods

FG-3019, human CTGF (rhCTGF), or the N-terminal domain of rhCTGF were administered intravenously to rats and concentrations of these proteins as well as endogenous CTGF were determined by immunoassays. FG-3019, or ¹²⁵I-labeled FG-3019, and human CTGF (rhCTGF) were co-administered to assess the impact of CTGF on the elimination rate and tissue localization of FG-3019, which was further characterized by immunohistochemical analysis. A PK/PD model for target-mediated elimination of FG-3019 was developed to fit the kinetic data.

Results

FG-3019 exhibited non-linear pharmacokinetics in rats. Circulating concentrations of the N-terminal half of CTGF increased after dosing with FG-3019, reached maximal levels after 1–5 days, and returned toward baseline levels as FG-3019 cleared from the circulation, whereas the concentration of intact CTGF was unaffected by administration of FG-3019. Co-administration of rhCTGF dramatically enhanced the rate of FG-3019 elimination, redistributing the majority of ¹²⁵I-labeled FG-3019 from the blood to the liver, kidney, spleen and adrenal gland. FG-3019 co-administered with CTGF was found along the sinusoids of the liver and adrenal glands, the capillaries of the kidney glomeruli and in the spleen. A pharmacokinetic model for target-mediated elimination of FG-3019 was used to fit the time courses of FG-3019 and endogenous CTGF plasma concentrations, as well as time courses of rhCTGF and rhCTGF N-fragment after intravenous administration of these species.

Conclusions

FG-3019 is subject to target mediated elimination in rats.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-016-1918-0) contains supplementary material, which is available to authorized users.

Population pharmacokinetics of tanezumab in phase 3 clinical trials for osteoarthritis pain

Aims

The aims were to 1) develop the pharmacokinetics model to describe and predict observed tanezumab concentrations over time, 2) test possible covariate parameter relationships that could influence clearance and distribution and 3) assess the impact of fixed dosing vs. a dosing regimen adjusted by body weight.

Methods

Individual concentration–time data were determined from 1608 patients in four phase 3 studies conducted to assess efficacy and safety of intravenous tanezumab. Patients received two or three intravenous doses (2.5, 5 or 10 mg) every 8 weeks. Blood samples for assessment of tanezumab PK were collected at baseline, 1 h post‐dose and at weeks 4, 8, 16 and 24 (or early termination) in all studies. Blood samples were collected at week 32 in two studies. Plasma samples were analyzed using a sensitive, specific, validated enzyme‐linked immunosorbent assay.

Results

A two compartment model with parallel linear and non‐linear elimination processes adequately described the data. Population estimates for clearance (CL), central volume (V₁), peripheral volume (V₂), inter‐compartmental clearance, maximum elimination capacity (VM) and concentration at half‐maximum elimination capacity were 0.135 l day^–1, 2.71 l, 1.98 l, 0.371 l day^–1, 8.03 μg day^–1 and 27.7 ng ml^–1, respectively. Inter‐individual variability (IIV) was included on CL, V₁, V₂ and VM. A mixture model accounted for the distribution of residual error. While gender, dose and creatinine clearance were significant covariates, only body weight as a covariate of CL, V₁ and V₂ significantly reduced IIV.

Conclusions

The small increase in variability associated with fixed dosing is consistent with other monoclonal antibodies and does not change risk : benefit.

Mathematical PKPD and safety model of bispecific TfR/BACE1 antibodies for the optimization of antibody uptake in brain

Treatment of diseases of the central nervous system by monoclonal antibodies may be limited by the restricted uptake of antibodies across the blood-brain barrier (BBB). An antibody targeting transferrin receptor (TfR) has been shown to take advantage of the receptor-mediated transcytosis properties of TfR in order to cross the BBB in mice, with the uptake in the brain being dependent on the affinity to TfR. In the bispecific format with arms targeting both TfR and β-secretase 1 (BACE1), altering the affinity to TfR has been shown to impact systemic exposure and safety profiles. In this work, a mathematical model incorporating pharmacokinetic/pharmacodynamic (PKPD) and safety profiles is developed for bispecific TfR/BACE1 antibodies with a range of affinities to TfR in order to guide candidate selection. The model captures the dependence of both systemic and brain exposure on TfR affinity and the subsequent impact on brain Aβ40 lowering and circulating reticulocyte levels. Model simulations identify the optimal affinity for the TfR arm of the bispecific to maximize Aβ reduction while maintaining reticulocyte levels. The model serves as a useful tool to prioritize and optimize preclinical studies and has been used to support the selection of additional candidates for further development.

Population pharmacokinetic modeling of Thymoglobulin(®) in children receiving allogeneic-hematopoietic cell transplantation: towards improved survival through individualized dosing

BACKGROUND AND OBJECTIVES

To prevent graft-versus-host disease and rejection in hematopoietic cell transplantation (HCT), children receive Thymoglobulin(®), a polyclonal antibody acting mainly by depleting T cells. The therapeutic window is critical as over-exposure may result in delayed immune reconstitution of donor T cells. In this study, we describe the population pharmacokinetics of Thymoglobulin(®) as a first step towards an evidence-based dosing regimen of Thymoglobulin(®) in pediatric HCT.

METHODS

Serum active Thymoglobulin(®) concentrations were measured in all pediatric HCTs performed between 2004 and 2012 in two pediatric HCT centers in The Netherlands. Population pharmacokinetic analysis was performed using NONMEM(®) version 7.2.

RESULTS

A total of 3,113 concentration samples from 280 pediatric HCTs were analyzed, with age ranging from 3 months to 23 years old. The cumulative Thymoglobulin(®) dose was 10 mg/kg in 94 % of the patients given in 4 consecutive days. A model incorporating parallel linear and concentration-dependent clearance of Thymoglobulin(®) was identified. Body weight [for linear clearance (CL) and central volume of distribution] as well as lymphocyte count pre-Thymoglobulin(®) infusion (for CL) were important covariates. As such, the current dosing regimen results in higher exposure in children with a higher bodyweight and/or a lower lymphocyte count pre-Thymoglobulin(®) infusion.

CONCLUSION

This model can be used to develop an individual dosing regimen for Thymoglobulin(®), based on both body weight and lymphocyte counts, once the therapeutic window has been determined. This individualized regimen may contribute to a better immune reconstitution and thus outcome of allogeneic HCT.

A Priori Identifiability of Target-Mediated Drug Disposition Models and Approximations

A priori identifiability of mathematical models assures that for a given input/output experiment, the parameter set has one unique solution within a defined space, independent of the experimental design. Many biologic therapeutics exhibit target-mediated drug disposition (TMDD), and use of the full compartmental model describing this system is well documented. In practice, estimation of the full parameter set for TMDD models, given real-world clinical data, is characterized by convergence difficulties and unstable solutions. Still, the formal assessment of the a priori identifiability of these systems has yet to be reported. The exact arithmetic rank (EAR) approach was used to test the a priori identifiability of a TMDD model as well as model approximations. The full TMDD and quasi-equilibrium/rapid binding (QE/RB), quasi-steady state (QSS), and Michaelis-Menten (MM) approximations were fully identifiable, a priori, regardless of whether observations were taken from a single or multiple compartments. The results of these identifiability analyses indicated that the difficulty with TMDD model convergence, a posteriori, lies in the experimental design, not in the mathematical identifiability in the lack of samples from several compartments. Experiments can be tailored to resolve these structurally non-identifiable parameters, notwithstanding practical implementation challenges. This work highlights the importance of identifiability analyses, specifically how they can influence experimental design and selection of the appropriate model structure to describe a dynamic biological system.

A Tutorial on Target-Mediated Drug Disposition (TMDD) Models

Target-mediated drug disposition (TMDD) is the phenomenon in which a drug binds with high affinity to its pharmacological target site (such as a receptor) to such an extent that this affects its pharmacokinetic characteristics.1 The aim of this Tutorial is to provide an introductory guide to the mathematical aspects of TMDD models for pharmaceutical researchers. Examples of Berkeley Madonna2 code for some models discussed in this Tutorial are provided in the Supplementary Materials.

Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection

Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.

Translating slow-binding inhibition kinetics into cellular and in vivo effects

Many drug candidates fail in clinical trials owing to a lack of efficacy from limited target engagement or an insufficient therapeutic index. Minimizing off-target effects while retaining the desired pharmacodynamic (PD) response can be achieved by reduced exposure for drugs that display kinetic selectivity in which the drug-target complex has a longer half-life than off-target-drug complexes. However, though slow-binding inhibition kinetics are a key feature of many marketed drugs, prospective tools that integrate drug-target residence time into predictions of drug efficacy are lacking, hindering the integration of drug-target kinetics into the drug discovery cascade. Here we describe a mechanistic PD model that includes drug-target kinetic parameters, including the on- and off-rates for the formation and breakdown of the drug-target complex. We demonstrate the utility of this model by using it to predict dose response curves for inhibitors of the LpxC enzyme from Pseudomonas aeruginosa in an animal model of infection.

Prediction of clinical pharmacokinetics of AMG 181, a human anti-α 4 β 7 monoclonal antibody for treating inflammatory bowel diseases

The purpose of this study was to predict a safe starting dose of AMG 181, a human anti-α₄β₇ antibody for treating inflammatory bowel diseases, based on cynomolgus monkey pharmacokinetic (PK) and pharmacodynamic (PD) data. A two-compartment model with parallel linear and target-mediated drug disposition for AMG 181 PK in cynomolgus monkey was developed. The estimated parameters were allometrically scaled to predict human PK. An E_max PD model was used to relate AMG 181 concentration and free α₄β₇ receptor data in cynomolgus monkey. AMG 181 clinical doses were selected based on observed exposures at the no adverse effect level of 80 mg·kg⁻¹ in monkeys, the predicted human exposures, and AMG 181 concentration expected to produce greater than 50% α₄β₇ receptor occupancy in humans. The predicted human AMG 181 clearance and central volume of distribution were 144 mL·day⁻¹ and 2900 mL, respectively. The estimated EC₅₀ for free α₄β₇ receptor was 14 ng·mL⁻¹. At the 0.7 mg starting dose in humans, the predicted exposure margins were greater than 490,000 and AMG 181 concentrations were predicted to only briefly cover the free α₄β₇ receptor EC₁₀. Predictions for both C_max and AUC matched with those observed in the first-in-human study within the 7 mg subcutaneous to 420 mg intravenous dose range. The developed model aided in selection of a safe starting dose and a pharmacological relevant dose escalation strategy for testing of AMG 181 in humans. The clinically observed human AMG 181 PK data validated the modeling approach based on cynomolgus monkey data alone.

Model-based assessment of dosing strategies in children for monoclonal antibodies exhibiting target-mediated drug disposition

Body weight/body surface area–based and/or tiered fixed dosing strategies are widely utilized for monoclonal antibodies with linear clearance to scale adult clinical doses to children. However, there is limited knowledge on whether or not body weight–based dosing strategies also yield comparable dose-concentration-response relationships in adults and children for monoclonal antibodies that exhibit target-mediated drug disposition. Our findings indicate that it is important to interpret pharmacokinetics information in a pharmacokinetics/pharmacodynamics context as similar systemic drug exposure in adults and children may not be reflective of the corresponding target occupancy. They further indicate that BW-based dosing is superior to fixed dosing for the same target concentration, whereas the opposite holds true for the same target amount in adults and children. Michaelis-Menten approximations yielded similar profiles compared to the full target-mediated drug disposition model for all simulation scenarios and may be used to guide the selection of appropriate dosing regimens in children.

Incorporating target-mediated drug disposition in a minimal physiologically-based pharmacokinetic model for monoclonal antibodies

Target-mediated drug disposition (TMDD) usually accounts for nonlinear pharmacokinetics (PK) of drugs whose distribution and/or clearance are affected by their targets owing to high affinity and limited capacity. TMDD is frequently reported for monoclonal antibodies (mAb) for such reason. Minimal physiologically-based pharmacokinetic models (mPBPK), which accommodate the unique PK behaviors of mAb, provide a general approach for analyzing mAbs PK and predicting mAb interstitial concentrations in two groups of tissues. This study assessed the feasibility of incorporating TMDD into mPBPK models to consider target-binding in either plasma (cTMDD) or interstitial fluid (ISF) (pTMDD). The dose-related signature profiles of the pTMDD model reveal a parallel early decay phase, in contrast with the cTMDD model that exhibits a faster initial decline for low doses. The parallel early phase in the pTMDD model is associated with the slow perivascular extravasation of mAb, which restricts the initial decline regardless of interstitial target-mediated elimination. The cTMDD and pTMDD models both preserve the long terminal phase that is typically perceived in conventional two-compartment (2CM) and TMDD models. Having TMDD in ISF impacts the typical relationships between plasma concentrations and receptor occupancy, and between saturation of apparent nonlinear clearance and saturation of receptors. The vascular reflection coefficient (σ v ) was found to affect receptor occupancy in ISF. In the cTMDD model, saturation of nonlinear clearance is equivalent to saturation of receptors. However, in the pTMDD model, they are no longer equal and all parameters pertaining to receptors or receptor binding (R total , K D , K ss , k int ) shifts such relationships. Different TMDD models were utilized in analyzing PK for seven mAbs from digitized literature data. When the target is in plasma, the cTMDD model performed similarly to the 2CM and TMDD models, but with one less system parameter. When the target exists in ISF, the pTMDD functioned well in analyzing only plasma data to reflect interstitial target binding properties. Assigning TMDD consistent with target-expressing tissues is important to obtain reliable characterizations of receptors and receptor binding. The mPBPK model exhibits excellent feasibility in integrating TMDD not only in plasma but also in ISF.

Target-mediated drug disposition model and its approximations for antibody-drug conjugates

Antibody-drug conjugate (ADC) is a complex structure composed of an antibody linked to several molecules of a biologically active cytotoxic drug. The number of ADC compounds in clinical development now exceeds 30, with two of them already on the market. However, there is no rigorous mechanistic model that describes pharmacokinetic (PK) properties of these compounds. PK modeling of ADCs is even more complicated than that of other biologics as the model should describe distribution, binding, and elimination of antibodies with different toxin load, and also the deconjugation process and PK of the released toxin. This work extends the target-mediated drug disposition (TMDD) model to describe ADCs, derives the rapid binding (quasi-equilibrium), quasi-steady-state, and Michaelis-Menten approximations of the TMDD model as applied to ADCs, derives the TMDD model and its approximations for ADCs with load-independent properties, and discusses further simplifications of the system under various assumptions. The developed models are shown to describe data simulated from the available clinical population PK models of trastuzumab emtansine (T-DM1), one of the two currently approved ADCs. Identifiability of model parameters is also discussed and illustrated on the simulated T-DM1 examples.

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.

Monoclonal Antibodies for Therapeutic Use: Specific Characteristics of Clinical Development, Evaluation by the Agencies, and Long-term Monitoring of Safety

Monoclonal antibodies (MoAb) are very different from other drugs. The Round Table aimed to determine whether the specific characteristics of MoAb have repercussions on their clinical development, evaluation by the health authorities, and long-term monitoring. As regards the structure-activity relationship of MoAb, classification according to mechanism of action (neutralising or agonist MoAb, cytolytic MoAb) is more relevant than to their degree of humanisation. Recommendations on their clinical development would be useful since the early phases give rise to a number of problems and are insufficiently codified. The pharmacokinetic profile is very different from that of other drugs. The concentration-effect relationship is difficult to study since the biomarkers may be apparently disconnected from the therapeutic effect. The methodology for evaluation of MoAb by the agencies, and postmarketing surveillance do not differ from the procedures used for other drugs; however, MoAb bring together a number of specific characteristics as compared with other drugs.

Semi-mechanistic population pharmacokinetic model of multivalent trastuzumab emtansine in patients with metastatic breast cancer

Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate (ADC) composed of multiple molecules of the antimicrotubule agent DM1 linked to trastuzumab, a humanized anti-human epidermal growth factor receptor 2 (HER2) monoclonal antibody. Pharmacokinetics data from phase I (n = 52) and phase II (n = 111) studies in HER2-positive metastatic breast cancer patients show a shorter terminal half-life for T-DM1 than for total trastuzumab (TTmAb). In this work, we translated prior preclinical modeling in monkeys to develop a semi-mechanistic population pharmacokinetics model to characterize T-DM1 and TTmAb concentration profiles. A series of transit compartments with the same disposition parameters was used to describe the deconjugation process from higher to lower drug-to-antibody ratios (DARs). The structure could explain the shorter terminal half-life of T-DM1 relative to TTmab. The final model integrates prior knowledge of T-DM1 DARs from preclinical studies and could provide a platform for understanding and characterizing the pharmacokinetics of other ADC systems.

Methods of solving rapid binding target-mediated drug disposition model for two drugs competing for the same receptor

The target-mediated drug disposition (TMDD) model has been adopted to describe pharmacokinetics for two drugs competing for the same receptor. A rapid binding assumption introduces total receptor and total drug concentrations while free drug concentrations C (A) and C (B) are calculated from the equilibrium (Gaddum) equations. The Gaddum equations are polynomials in C (A) and C (B) of second degree that have explicit solutions involving complex numbers. The aim of this study was to develop numerical methods to solve the rapid binding TMDD model for two drugs competing for the same receptor that can be implemented in pharmacokinetic software. Algebra, calculus, and computer simulations were used to develop algorithms and investigate properties of solutions to the TMDD model with two drugs competitively binding to the same receptor. A general rapid binding approximation of the TMDD model for two drugs competing for the same receptor has been proposed. The explicit solutions to the equilibrium equations employ complex numbers, which cannot be easily solved by pharmacokinetic software. Numerical bisection algorithm and differential representation were developed to solve the system instead of obtaining an explicit solution. The numerical solutions were validated by MATLAB 7.2 solver for polynomial roots. The applicability of these algorithms was demonstrated by simulating concentration-time profiles resulting from exogenous and endogenous IgG competing for the neonatal Fc receptor (FcRn), and darbepoetin competing with endogenous erythropoietin for the erythropoietin receptor. These models were implemented in ADAPT 5 and Phoenix WinNonlin 6.0, respectively.

Dynamics of target-mediated drug disposition: characteristic profiles and parameter identification

In this paper we present a mathematical analysis of the basic model for target mediated drug disposition (TMDD). Assuming high affinity of ligand to target, we give a qualitative characterisation of ligand versus time graphs for different dosing regimes and derive accurate analytic approximations of different phases in the temporal behaviour of the system. These approximations are used to estimate model parameters, give analytical approximations of such quantities as area under the ligand curve and clearance. We formulate conditions under which a suitably chosen Michaelis-Menten model provides a good approximation of the full TMDD-model over a specified time interval.

Pharmacokinetics of recombinant bifunctional fusion proteins

INTRODUCTION

The development of biotechnology has enabled the creation of various recombinant fusion proteins as a new class of biotherapeutics. The uniqueness of fusion proteins lies in their ability to fuse two or more protein domains, providing vast opportunities to generate novel combinations of functions. Pharmacokinetic (PK) studies, which are critical components in preclinical and clinical drug development, have not been fully explored for fusion proteins. The lack of general PK models and study guidelines has become a bottleneck for translation of fusion proteins from basic research to the clinic.

AREAS COVERED

This article reviews the current status of PK studies for fusion proteins, covering the processes that affect PK. According to their PK properties, a classification of fusion proteins is suggested along with examples from the clinic or under development. Current limitations and future perspectives for PK of fusion proteins are also discussed.

EXPERT OPINION

A PK model for bifunctional fusion proteins is presented to highlight the importance of mechanistic studies for a thorough understanding of the PK properties of fusion proteins. The model suggests investigating the receptor binding and subsequent intracellular disposition of individual domains, which can have dramatic impact on the PK of fusion proteins.

Population pharmacokinetic meta-analysis of denosumab in healthy subjects and postmenopausal women with osteopenia or osteoporosis

BACKGROUND AND OBJECTIVE

Inhibition of the receptor activator of nuclear factor κ-B ligand (RANKL) is a therapeutic target for treatment of bone disorders associated with increased bone resorption, such as osteoporosis. The objective of this analysis was to characterize the population pharmacokinetics of denosumab (AMG 162; Prolia®), a fully human IgG2 monoclonal antibody that binds to RANKL, in healthy subjects and postmenopausal women with osteopenia or osteoporosis.

METHODS

A total of 22944 serum free denosumab concentrations from 495 healthy subjects and 1069 postmenopausal women with osteopenia or osteoporosis were pooled. Denosumab was administered as either a single intravenous dose (n = 36), a single subcutaneous dose (n = 469) or multiple subcutaneous doses (n = 1059), ranging from 0.01 to 3 mg/kg (or 6-210 mg as fixed mass dosages), every 3 or 6 months for up to 48 months. An open, two-compartment pharmacokinetic model with a quasi-steady-state approximation of the target-mediated drug disposition model was used to describe denosumab pharmacokinetics, using NONMEM Version 7.1.0 software. Subcutaneous absorption was characterized by the first-order absorption rate constant (k(a)), with constant absolute bioavailability over the range of doses that were evaluated. Clearance and volume of distribution parameters were scaled by body weight, using a power model. Model evaluation was performed through visual predictive checks.

RESULTS

The subcutaneous bioavailability of denosumab was 64%, and the k(a) was 0.00883 h-1. The central volume of distribution and linear clearance were 2.49 L/66 kg and 3.06 mL/h/66 kg, respectively. The baseline RANKL level, quasi-steady-state constant and RANKL degradation rate were 614 ng/mL, 138 ng/mL and 0.00148 h-1, respectively. Between-subject variability in model parameters was moderate. A fixed dose of 60 mg provided RANKL inhibition similar to that achieved by equivalent body weight-based dosing. The effects of age and race on the area under the serum concentration-time curve of denosumab were less than 15% over the range of covariate values that were evaluated.

CONCLUSIONS

The non-linearity in denosumab pharmacokinetics is probably due to RANKL binding, and denosumab dose adjustment based on the patient demographics is not warranted.

The Øie-Tozer model of drug distribution and its suitability for drugs with different pharmacokinetic behavior

INTRODUCTION

Drug distribution is a major pharmacokinetic process that affects the time course of drug concentrations in tissues, biological fluids and the resulting pharmacological activities. Drug distribution may follow different pathways and patterns, and is governed by the drug's physicochemical properties and the body's physiology. The classical Øie-Tozer model is frequently used for predicting volume of drug distribution and for pharmacokinetic calculations.

AREAS COVERED

In this review, the suitability of the Øie-Tozer model for drugs that exhibit different distribution patterns is critically analyzed and illustrated. The method used is a pharmacokinetic modeling and simulation approach. It is demonstrated that the major limitation of the Øie-Tozer model stems from its focus on the total drug concentrations and not on the active (unbound) concentrations. Moreover, the Øie-Tozer model may be inappropriate for drugs with nonlinear or complex pharmacokinetic behavior, such as biopharmaceuticals, drug conjugates or for drugs incorporated into drug delivery systems. Distribution mechanisms and alternative distribution models for these drugs are discussed.

EXPERT OPINION

The Øie-Tozer model can serve for predicting unbound volume of drug distribution for 'classical' small molecular mass drugs with linear pharmacokinetics. However, more detailed mechanism-based distribution models should be used in preclinical and clinical settings for drugs that exhibit more complex pharmacokinetic behavior.

Dose correction for the Michaelis-Menten approximation of the target-mediated drug disposition model

The Michaelis-Menten (M-M) approximation of the target-mediated drug disposition (TMDD) pharmacokinetic (PK) model was derived based on the rapid binding (RB) or quasi steady-state (QSS) assumptions that implied that the target and drug binding and dissociation were in equilibrium. However, the initial dose for an IV bolus injection for the M-M model did not account for a fraction bound to the target. We postulated a correction to an initial condition that was consistent with the assumptions underlying the M-M approximation. We determined that the difference between the injected dose and one that should be used for the initial condition is equal to the amount of drug bound to the target upon reaching the equilibrium. We also observed that the corrected initial condition made the internalization rate constant an identifiable parameter that was not for the original M-M model. Finally, we performed a simulation exercise to check if the correction will impact the model performance and the bias of the M-M parameter estimates. We used literature data to simulate plasma drug concentrations described by the RB/QSS TMDD model. The simulated data were refitted by both models. All the parameters estimated from the original M-M model were substantially biased. On the other hand, the corrected M-M is able to accurately estimate these parameters except for equilibrium constant K(m). Weighted sum of square residual and Akaike information criterion suggested a better performance of the corrected M-M model compared with the original M-M model. Further studies are necessary to determine the importance of this correction for the M-M model applications to analysis of TMDD driven PK data.