Quantitative prediction of human pharmacokinetics for mAbs exhibiting target-mediated disposition

Developing a mechanistic translational PK/PD model for a trifunctional NK cell engager to predict the first-in-human dose for acute myeloid leukemia

Natural killer cell engagers (NKCEs), a treatment that stimulates innate immunity, have lately gained attention owing to their favorable safety profile, and their efficacy. Natural killer (NK) cell activation is driven by immune synapse formation between drugs, NK cells, and tumor cells. However, no clear translational modeling approach has been reported for first-in-human (FIH) dose estimation of humanized NKCEs. We developed the first translational mechanistic synapse-driven pharmacokinetic/pharmacodynamic (PK/PD) model for a trifunctional NKp46/CD16a-CD123 (CD123-NKCE) by integrating (i) in vitro target cell cytotoxicity in MOLM-13 tumor cell lines at varying effector-to-tumor cell ratios and incubation intervals; (ii) nonhuman primate PK and profiles of CD123+ cells and NKP46+ NK cells; and (iii) healthy human or patients with acute myeloid leukemia system-specific parameters. To depict direct tumor cell killing by the innate immunity, no transit compartment was included in PK/PD model structures. Model predictions suggested an intrapatient dose escalation of 10/30/100 μg/kg twice weekly to be selected as the starting dose in the FIH trial. However, sensitivity analyses revealed that CD123+ cell growth rate constant and maximal tumor killing rate constant were the key uncertainties to the recommended active dose. This novel translational model structure can be used as the basis to predict clinical PK/PD data for CD123-NKCE, and the translational strategy may serve as a foundation for future advancements of NKCEs.

Prospective approaches to gene therapy computational modeling - spotlight on viral gene therapy

Clinical studies have found there still exists a lack of gene therapy dose-toxicity and dose-efficacy data that causes gene therapy dose selection to remain elusive. Model informed drug development (MIDD) has become a standard tool implemented throughout the discovery, development, and approval of pharmaceutical therapies, and has the potential to inform dose-toxicity and dose-efficacy relationships to support gene therapy dose selection. Despite this potential, MIDD approaches for gene therapy remain immature and require standardization to be useful for gene therapy clinical programs. With the goal to advance MIDD approaches for gene therapy, in this review we first provide an overview of gene therapy types and how they differ from a bioanalytical, formulation, route of administration, and regulatory standpoint. With this biological and regulatory background, we propose how MIDD can be advanced for AAV-based gene therapies by utilizing physiological based pharmacokinetic modeling and quantitative systems pharmacology to holistically inform AAV and target protein dynamics following dosing. We discuss how this proposed model, allowing for in-depth exploration of AAV pharmacology, could be the key the field needs to treat these unmet disease populations.

Application of Allometric Scaling to Nanochelator Pharmacokinetics

Deferoxamine (DFO) is an effective FDA-approved iron chelator; however, its use is considerably limited by off-target toxicities and an extremely cumbersome dose regimen involving daily infusions. The recent development of a deferoxamine-based nanochelator (DFO-NP) with selective renal excretion has shown promise in ameliorating iron overload and associated physiological complications in rodent models with a substantially improved safety profile. While the dose- and administration route-dependent pharmacokinetics (PK) of DFO-NPs have been recently characterized, the optimized PK model was not validated, and the prior studies did not directly address the clinical translatability of DFO-NPs into humans. In the present work, these gaps were addressed by applying allometric scaling of DFO-NP PK in rats to predict those in mice and humans. First, this approach predicted serum concentration-time profiles of DFO-NPs, which were similar to those experimentally measured in mice, validating the nonlinear disposition and absorption models for DFO-NPs across the species. Subsequently, we explored the utility of allometric scaling by predicting the PK profile of DFO-NPs in humans under clinically relevant dosing schemes. These in silico efforts demonstrated that the novel nanochelator is expected to improve the PK of DFO when compared to standard infusion regimens of native DFO. Moreover, reasonable formulation strategies were identified and discussed for both early clinical development and more sophisticated formulation development.

Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection

The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.

Translational pharmacokinetics of a novel bispecific antibody against Ebola virus (MBS77E) from animal to human by PBPK modeling & simulation

The goal of this study was to construct a PBPK model to accelerate the translation of MBS77E, a humanized bispecific antibody against the Ebola virus. In-depth nonclinical pharmacokinetic studies in rats, monkeys, wild-type mice and transgenic mice were conducted. The pH-dependent affinities (K_D) of MBS77E to recombinant FcRn of different species were determined by surface plasmon resonance analysis. A mechanistic whole-body PBPK model of MBS77E was developed and validated in the assessment of PK profiles and tissue distributions in preclinical models. This PBPK model was finally used to predict human PK behaviors of MBS77E. Simulations from the PBPK model with measured and fitted parameters were able to yield good predictions of the serum and tissue pharmacokinetic parameters of MBS77E within 2-fold errors. The predicted serum concentration in humans was able to maintain a sufficiently high level for more than 14 days after 50 mg/kg i.v. administrating. This achievement unlocks that PBPK modeling is a powerful tool to gain insights into the properties of antibody drugs. It guided experimental efforts to obtain necessary information before entry into humans.

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

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

Characterizing the pharmacokinetics and biodistribution of therapeutic proteins: an industry white paper

Characterization of the pharmacokinetics (PK) and biodistribution of therapeutic proteins (TPs) is a hot topic within the pharmaceutical industry, particularly with an ever-increasing catalog of novel modality TPs. Here, we review the current practices, and provide a summary of extensive cross-company discussions as well as a survey completed by International Consortium for Innovation and Quality (IQ consortium) members on this theme. A wide variety of in vitro, in vivo and in silico techniques are currently used to assess PK and biodistribution of TPs, and we discuss the relevance of these from an industry perspective, focusing on PK/PD understanding at the preclinical stage of development, and translation to human. We consider that the 'traditional in vivo biodistribution study' is becoming insufficient as a standalone tool, and thorough characterization of the interaction of the TP with its target(s), target biology, and off-target interactions at a microscopic scale are key to understand the overall biodistribution at a full-body scale. Our summary of the current challenges and our recommendations to address these issues could provide insight into the implementation of best practices in this area of drug development, and continued cross-company collaboration will be of tremendous value. Significance Statement The Innovation & Quality Consortium (IQ) Translational and ADME Sciences Leadership Group (TALG) working group for the ADME of therapeutic proteins evaluates the current practices, recent advances, and challenges in characterizing the PK and biodistribution of therapeutic proteins during drug development, and proposes recommendations to address these issues. Incorporating the in vitro, in vivo and in silico approaches discussed herein may provide a pragmatic framework to increase early understanding of PK/PD relationships, and aid translational modelling for first-in-human dose predictions.

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

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

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.

Translational PK/PD and model-informed development of JNJ-67842125, a Fab reversal agent for JNJ-64179375, a long-acting thrombin inhibitor

BACKGROUND AND PURPOSE

Antigen-binding fragment (F_ab ) reversal agents were developed to reverse, in bleeding emergency, the long-acting anticoagulant effect of JNJ-64179375 (JNJ-9375), a monoclonal antibody that binds exosite-1 on thrombin.

EXPERIMENTAL APPROACH

The pharmacokinetic and pharmacodynamic (PK/PD) activities of three reversal agents of varying in vitro binding affinities to JNJ-9375 were characterised in cynomolgus monkeys. The time course of JNJ-9375 anticoagulant activity and reversal effects of each agent were evaluated. A mechanism-based PK/PD model, which integrated free serum concentrations of reversal agent, total and free serum concentrations of JNJ-9375, and thrombin time, was developed to quantitatively relate JNJ-9375 neutralisation to reversal of induced thrombin time prolongation. Model-based allometric scale-up of the lead reversal agent and the PK/PD relationship of JNJ-9375 in healthy volunteers were utilised to predict clinical dosing regimens.

KEY RESULTS

Lowering of free JNJ-9375 by the reversal agents corresponded with reversal of thrombin time prolongation. Total JNJ-9375 displayed typical mAb clearance at 2.75 ml·day^-1 ·kg^-1 , whereas reversal agents cleared faster between 1400 and 2400 ml·day^-1 ·kg^-1 . The model-estimated in vivo K_D values for JNJ-9375 reversal agents were 9 nM (ICHB-256), 0.4 nM (ICHB-281) and 13.7 pM (ICHB-164), in rank-ordered agreement of their K_D values determined in vitro. The three reversal agents exhibited different neutralisation characteristics in vivo, governed primarily by their binding kinetics to JNJ-9375. The model predicted a priori free JNJ-9375 kinetics after dosing ICHB-164 (JNJ-67842125) and JNJ-9375 under a different regimen.

CONCLUSION AND IMPLICATIONS

The results enabled selection of JNJ-67842125 as the reversal agent for JNJ-9375.

Preclinical characterization of the ADME properties of a surrogate anti-IL-36R monoclonal antibody antagonist in mouse serum and tissues

The decision to pursue a monoclonal antibody (mAb) as a therapeutic for disease intervention requires the assessment of many factors, such as target-biology, including the total target burden and its accessibility at the intended site of action, as well as mAb-specific properties like binding affinity and the pharmacokinetics in serum and tissue. Interleukin-36 receptor (IL-36 R) is a member of the IL-1 family cytokine receptors and an attractive target to treat numerous epithelial-mediated inflammatory conditions, including psoriatic and rheumatoid arthritis, asthma, and chronic obstructive pulmonary disease. However, information concerning the expression profile of IL-36 R at the protein level is minimal, so the feasibility of developing a therapeutic mAb against this target is uncertain. Here, we present a characterization of the properties associated with absorption, distribution, metabolism, and excretion of a high-affinity IL-36 R-targeted surrogate rat (IgG2a) mAb antagonist in preclinical mouse models. The presence of IL-36 R in the periphery was confirmed unequivocally as the driver of non-linear pharmacokinetics in blood/serum, although a predominant site of tissue accumulation was not observed based upon the kinetics of radiotracer. Additionally, the contribution of IL-36 R-mediated catabolism of mAb in kidney was tested in a 5/6 nephrectomized mouse model where minimal effects on serum pharmacokinetics were observed, although analysis of functional mAb in urine suggests that target can influence the amount of mAb excreted. Our data highlight an interesting case of target-mediated drug disposition (TMDD) where low, yet broadly expressed levels of membrane-bound target result in a cumulative effect to drive TMDD behavior typical of a large, saturable target sink. The potential differences between our mouse model and IL-36 R target profile in humans are also presented.

Predicting Method for the Human Plasma Concentration-Time Profile of a Monoclonal Antibody from the Half-life of Non-human Primates

Efficiency (speed and cost) and animal welfare are important factors in the development of new drugs. A novel method (the half-life method) was developed to predict the human plasma concentration-time profile of a monoclonal antibody (mAb) after intravenous (i.v.) administration using less data compared to the conventional approach; moreover, predicted results were comparable to conventional method. This new method use human geometric means of pharmacokinetics (PK) parameters and the non-human primates (NHP) half-life of each mAb. PK data on mAbs in humans and NHPs were collected from literature focusing on linear elimination, and the two-compartment model was used for analysis. The following features were revealed in humans: 1) the coefficient of variation in the distribution volume of the central compartment and at steady state of mAbs was small (22.6 and 23.8%, respectively) and 2) half-life at the elimination phase (t1/2_β) was the main contributor to plasma clearance. Moreover, distribution volume showed no significant correlation between humans and NHPs, and human t1/2_β showed a good correlation with allometrically scaled t1/2_β of NHP. Based on the features revealed in this study, we propose a new method for predicting the human plasma concentration-time profile of mAbs after i.v. dosing. When tested, this half-life method showed reasonable human prediction compared with a conventional empirical approach. The half-life method only requires t1/2_β to predict human PK, and is therefore able to improve animal welfare and potentially accelerate the drug development process.

Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings

Constant technological advancement enabled the production of therapeutic monoclonal antibodies (mAbs) and will continue to contribute to their rapid expansion. Compared to small-molecule drugs, mAbs have favorable characteristics, but also more complex pharmacokinetics (PK), e.g., target-mediated nonlinear elimination and recycling by neonatal Fc-receptor. This review briefly discusses mAb biology, similarities and differences in PK processes across species and within human, and provides a detailed overview of allometric scaling approaches for translating mAb PK from preclinical species to human and extrapolating from adults to children. The approaches described here will remain vital in mAb drug development, although more data are needed, for example, from very young patients and mAbs with nonlinear PK, to allow for more confident conclusions and contribute to further growth of this field. Improving mAb PK predictions will facilitate better planning of (pediatric) clinical studies and enable progression toward the ultimate goal of expediting drug development.

A target-mediated drug disposition population pharmacokinetic model of GC1118, a novel anti-EGFR antibody, in patients with solid tumors

Abstract

GC1118 is a monoclonal antibody for epidermal growth factor receptor (EGFR) that is currently under clinical development to treat patients with solid tumors. In this study, the pharmacokinetics (PKs) of GC1118 were modeled in solid tumor patients who received a 2‐h intravenous infusion of GC1118 at 0.3, 1, 3, 5, or 4 mg/kg once‐weekly (Q1W) on days 1, 8, 15, and 22 or 8 mg/kg every other week on days 1 and 15. A target‐mediated drug disposition population PK model adequately described the concentration‐time profiles of GC1118. Monte‐Carlo simulation experiments of the PK profiles and EGFR occupancies (ROs) by GC1118 based on the final model showed that Q1W at 4 or 5 mg/kg will produce a better antitumor effect than Q2W at 8 mg/kg. Because GC1118 was safer at 4 mg/kg than 5 mg/kg in the phase I study, we suggest to test the 4 mg/kg Q1W regimen in further clinical trials with GC1118.

Evolution of the Systems Pharmacokinetics-Pharmacodynamics Model for Antibody-Drug Conjugates to Characterize Tumor Heterogeneity and In Vivo Bystander Effect

The objective of this work was to develop a systems pharmacokinetics-pharmacodynamics (PK-PD) model that can characterize in vivo bystander effect of antibody-drug conjugate (ADC) in a heterogeneous tumor. To accomplish this goal, a coculture xenograft tumor with 50% GFP-MCF7 (HER2-low) and 50% N87 (HER2-high) cells was developed. The relative composition of a heterogeneous tumor for each cell type was experimentally determined by immunohistochemistry analysis. Trastuzumab-vc-MMAE (T-vc-MMAE) was used as a tool ADC. Plasma and tumor PK of T-vc-MMAE was analyzed in N87, GFP-MCF7, and coculture tumor-bearing mice. In addition, tumor growth inhibition (TGI) studies were conducted in all three xenografts at different T-vc-MMAE dose levels. To characterize the PK of ADC in coculture tumors, our previously published tumor distribution model was evolved to account for different cell populations. The evolved tumor PK model was able to a priori predict the PK of all ADC analytes in the coculture tumors reasonably well. The tumor PK model was subsequently integrated with a PD model that used intracellular tubulin occupancy to drive ADC efficacy in each cell type. The final systems PK-PD model was able to simultaneously characterize all the TGI data reasonably well, with a common set of parameters for MMAE-induced cytotoxicity. The model was later used to simulate the effect of different dosing regimens and tumor compositions on the bystander effect of ADC. The model simulations suggested that dose-fractionation regimen may further improve overall efficacy and bystander effect of ADCs by prolonging the tubulin occupancy in each cell type. SIGNIFICANCE STATEMENT: A PK-PD analysis is presented to understand bystander effect of Trastuzumab-vc-MMAE ADC in antigen (Ag)-low, Ag-high, and coculture (i.e., Ag-high + Ag-low) xenograft mice. This study also describes a novel single cell-level systems PK-PD model to characterize in vivo bystander effect of ADCs. The proposed model can serve as a platform to mathematically characterize multiple cell populations and their interactions in tumor tissues. Our analysis also suggests that fractionated dosing regimen may help improve the bystander effect of ADCs.

Retrospective analysis of model-based predictivity of human pharmacokinetics for anti-IL-36R monoclonal antibody MAB92 using a rat anti-mouse IL-36R monoclonal antibody and RNA expression data (FANTOM5)

Accurate prediction of the human pharmacokinetics (PK) of a candidate monoclonal antibody from nonclinical data is critical to maximize the success of clinical trials. However, for monoclonal antibodies exhibiting nonlinear clearance due to target-mediated drug disposition, PK predictions are particularly challenging. That challenge is further compounded for molecules lacking cross-reactivity in a nonhuman primate, in which case a surrogate antibody selective for the target in rodent may be required. For these cases, prediction of human PK must account for any interspecies differences in binding kinetics, target expression, target turnover, and potentially epitope. We present here a model-based method for predicting the human PK of MAB92 (also known as BI 655130), a humanized IgG1 κ monoclonal antibody directed against human IL-36R. Preclinical PK was generated in the mouse with a chimeric rat anti-mouse IgG2a surrogate antibody cross-reactive against mouse IL-36R. Target-specific parameters such as antibody binding affinity (K_D), internalization rate of the drug target complex (k_int), target degradation rate (k_deg), and target abundance (R₀) were integrated into the model. Two different methods of assigning human R₀ were evaluated: the first assumed comparable expression between human and mouse and the second used high-resolution mRNA transcriptome data (FANTOM5) as a surrogate for expression. Utilizing the mouse R₀ to predict human PK, AUC_0-∞ was substantially underpredicted for nonsaturating doses; however, after correcting for differences in RNA transcriptome between species, AUC_0-∞ was predicted largely within 1.5-fold of observations in first-in-human studies, demonstrating the validity of the modeling approach. Our results suggest that semi-mechanistic models incorporating RNA transcriptome data and target-specific parameters may improve the predictivity of first-in-human PK.

A Cell-Level Systems PK-PD Model to Characterize In Vivo Efficacy of ADCs

Here, we have presented the development of a systems pharmacokinetics-pharmacodynamics (PK-PD) model for antibody-drug conjugates (ADCs), which uses intracellular target occupancy to drive in-vivo efficacy. The model is built based on PK and efficacy data generated using Trastuzumab-Valine-Citrulline-Monomethyl Auristatin E (T-vc-MMAE) ADC in N87 (high-HER2) and GFP-MCF7 (low-HER2) tumor bearing mice. It was observed that plasma PK of all ADC analytes was similar between the two tumor models; however, total trastuzumab, unconjugated MMAE, and total MMAE exposures were >10-fold, ~1.6-fold, and ~1.8-fold higher in N87 tumors. In addition, a prolonged retention of MMAE was observed within the tumors of both the mouse models, suggesting intracellular binding of MMAE to tubulin. A systems PK model, developed by integrating single-cell PK model with tumor distribution model, was able to capture all in vivo PK data reasonably well. Intracellular occupancy of tubulin predicted by the PK model was used to drive the efficacy of ADC using a novel PK-PD model. It was found that the same set of PD parameters was able to capture MMAE induced killing of GFP-MCF7 and N87 cells in vivo. These observations highlight the benefit of adopting a systems approach for ADC and provide a robust and predictive framework for successful clinical translation of ADCs.

Design and Conduct Considerations for First-in-Human Trials

A milestone step in translational science to transform basic scientific discoveries into therapeutic applications is the advancement of a drug candidate from preclinical studies to initial human testing. First-in-human (FIH) trials serve as the link to advance new promising drug candidates and are conducted primarily to determine the safe dose range for further clinical development. Cross-functional collaboration is essential to ensure efficient and successful FIH trials. The aim of this publication is to serve as a tutorial for conducting FIH trials for both small molecule and biological drug candidates with topics covering regulatory requirements, preclinical safety testing, study design considerations, safety monitoring, biomarker assessment, and global considerations. An emphasis is placed on FIH trial design considerations, including starting dose selection, study size and population, dose escalation scheme, and implementation of adaptive designs. In light of the recent revision of the European Medicines Agency (EMA) guideline on FIH trials to promote safety and mitigate risk, we also discuss new measures introduced in the guideline that impact FIH trial design.

Utilization of data below the analytical limit of quantitation in pharmacokinetic analysis and modeling: promoting interdisciplinary debate

Traditionally, bioanalytical laboratories do not report actual concentrations for samples with results below the LOQ (BLQ) in pharmacokinetic studies. BLQ values are outside the method calibration range established during validation and no data are available to support the reliability of these values. However, ignoring BLQ data can contribute to bias and imprecision in model-based pharmacokinetic analyses. From this perspective, routine use of BLQ data would be advantageous. We would like to initiate an interdisciplinary debate on this important topic by summarizing the current concepts and use of BLQ data by regulators, pharmacometricians and bioanalysts. Through introducing the limit of detection and evaluating its variability, BLQ data could be released and utilized appropriately for pharmacokinetic research.

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.

Linear pharmacokinetic parameters for monoclonal antibodies are similar within a species and across different pharmacological targets: A comparison between human, cynomolgus monkey and hFcRn Tg32 transgenic mouse using a population-modeling approach

The linear pharmacokinetics (PK) of therapeutic monoclonal antibodies (mAbs) can be considered a class property with values that are similar to endogenous IgG. Knowledge of these parameters across species could be used to avoid unnecessary in vivo PK studies and to enable early PK predictions and pharmacokinetic/pharmacodynamic (PK/PD) simulations. In this work, population-pharmacokinetic (popPK) modeling was used to determine a single set of ‘typical’ popPK parameters describing the linear PK of mAbs in human, cynomolgus monkey and transgenic mice expressing the human neonatal Fc receptor (hFcRn Tg32), using a rich dataset of 27 mAbs. Non-linear PK was excluded from the datasets and a 2-compartment model was applied to describe mAb disposition. Typical human popPK estimates compared well with data from comparator mAbs with linear PK in the clinic. Outliers with higher than typical clearance were found to have non-specific interactions in an affinity-capture self-interaction nanoparticle spectroscopy assay, offering a potential tool to screen out these mAbs at an early stage. Translational strategies were investigated for prediction of human linear PK of mAbs, including use of typical human popPK parameters and allometric exponents from cynomolgus monkey and Tg32 mouse. Each method gave good prediction of human PK with parameters predicted within 2-fold. These strategies offer alternative options to the use of cynomolgus monkeys for human PK predictions of linear mAbs, based on in silico methods (typical human popPK parameters) or using a rodent species (Tg32 mouse), and call into question the value of completing extensive in vivo preclinical PK to inform linear mAb PK.

Translational PK-PD modeling analysis of MCLA-128, a HER2/HER3 bispecific monoclonal antibody, to predict clinical efficacious exposure and dose

Introduction MCLA-128 is a bispecific monoclonal antibody targeting the HER2 and HER3 receptors. Pharmacokinetics (PK) and pharmacodynamics (PD) of MCLA-128 have been evaluated in preclinical studies in cynomolgus monkeys and mice. The aim of this study was to characterize the PK and PD of MCLA-128 and to predict a safe starting dose and efficacious clinical dose for the First-In-Human study. Methods A PK-PD model was developed based on PK data from cynomolgus monkeys and tumor growth data from a mouse JIMT-1 xenograft model. Allometric scaling was used to scale PK parameters between species. Simulations were performed to predict the safe and efficacious clinical dose, based on AUCs, receptor occupancies and PK-PD model simulations. Results MCLA-128 PK in cynomolgus monkeys was described by a two-compartment model with parallel linear and nonlinear clearance. The xenograft tumor growth model consisted of a tumor compartment with a zero-order growth rate and a first-order dying rate, both affected by MCLA-128. Human doses of 10 to 480 mg q3wk were predicted to show a safety margin of >10-fold compared to the cynomolgus monkey AUC at the no-observed-adverse-effect-level (NOAEL). Doses of ≥360 mg resulted in predicted receptor occupancies above 99% (C_max and C_ave). These doses showed anti-tumor efficacy in the PK-PD model. Conclusions This analysis predicts that a flat dose of 10 to 480 mg q3wk is suitable as starting dose for a First-in-Human study with MCLA-128. Flat doses ≥360 mg q3wk are expected to be efficacious in human, based on receptor occupancies and PK-PD model simulations.

Quantitative Systems Pharmacology Model of hUGT1A1-modRNA Encoding for the UGT1A1 Enzyme to Treat Crigler-Najjar Syndrome Type 1

Crigler‐Najjar syndrome type 1 (CN1) is an autosomal recessive disease caused by a marked decrease in uridine‐diphosphate‐glucuronosyltransferase (UGT1A1) enzyme activity. Delivery of hUGT1A1‐modRNA (a modified messenger RNA encoding for UGT1A1) as a lipid nanoparticle is anticipated to restore hepatic expression of UGT1A1, allowing normal glucuronidation and clearance of bilirubin in patients. To support translation from preclinical to clinical studies, and first‐in‐human studies, a quantitative systems pharmacology (QSP) model was developed. The QSP model was calibrated to plasma and liver mRNA, and total serum bilirubin in Gunn rats, an animal model of CN1. This QSP model adequately captured the observed plasma and liver biomarker behavior across a range of doses and dose regimens in Gunn rats. First‐in‐human dose projections made using the translated model indicated that 0.5 mg/kg Q4W dose should provide a clinically meaningful and sustained reduction of >5 mg/dL in total bilirubin levels.

AFIR: A Dimensionless Potency Metric for Characterizing the Activity of Monoclonal Antibodies

For monoclonal antibody (mAb) drugs, soluble targets may accumulate several thousand fold after binding to the drug. Time course data of mAb and total target is often collected and, although free target is more closely related to clinical effect, it is difficult to measure. Therefore, mathematical models of this data are used to predict target engagement. In this article, a “potency factor” is introduced as an approximation for the model‐predicted target inhibition. This potency factor is defined to be the time‐Averaged Free target concentration to Initial target concentration Ratio (AFIR), and it depends on three key quantities: the average drug concentration at steady state; the binding affinity; and the degree of target accumulation. AFIR provides the intuition for how changes in dosing regimen and binding affinity affect target capture and AFIR can be used to predict the druggability of new targets and the expected benefits of more potent, second‐generation mAbs.

Application of a PK-PD Modeling and Simulation-Based Strategy for Clinical Translation of Antibody-Drug Conjugates: a Case Study with Trastuzumab Emtansine (T-DM1)

Successful clinical translation of antibody-drug conjugates (ADCs) can be challenging due to complex pharmacokinetics and differences between preclinical and clinical tumors. To facilitate this translation, we have developed a general pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation (M&S)-based strategy for ADCs. Here we present the validation of this strategy using T-DM1 as a case study. A previously developed preclinical tumor disposition model for T-DM1 (Singh and Shah, AAPSJ. 2015; 18(4):861-875) was used to develop a PK-PD model that can characterize in vivo efficacy of T-DM1 in preclinical tumor models. The preclinical data was used to estimate the efficacy parameters for T-DM1. Human PK of T-DM1 was a priori predicted using allometric scaling of monkey PK parameters. The predicted human PK, preclinically estimated efficacy parameters, and clinically observed volume and growth parameters for breast cancer were combined to develop a translated clinical PK-PD model for T-DM1. Clinical trial simulations were performed using the translated PK-PD model to predict progression-free survival (PFS) and objective response rates (ORRs) for T-DM1. The model simulated PFS rates for HER2 1+ and 3+ populations were comparable to the rates observed in three different clinical trials. The model predicted only a modest improvement in ORR with an increase in clinically approved dose of T-DM1. However, the model suggested that a fractionated dosing regimen (e.g., front loading) may provide an improvement in the efficacy. In general, the PK-PD M&S-based strategy presented here is capable of a priori predicting the clinical efficacy of ADCs, and this strategy has been now retrospectively validated for all clinically approved ADCs.

Optimal Affinity of a Monoclonal Antibody: Guiding Principles Using Mechanistic Modeling

Affinity optimization of monoclonal antibodies (mAbs) is essential for developing drug candidates with the highest likelihood of clinical success; however, a quantitative approach for setting affinity requirements is often lacking. In this study, we computationally analyzed the in vivo mAb-target binding kinetics to delineate general principles for defining optimal equilibrium dissociation constant ([Formula: see text]) of mAbs against soluble and membrane-bound targets. Our analysis shows that in general [Formula: see text] to achieve 90% coverage for a soluble target is one tenth of its baseline concentration ([Formula: see text]), and is independent of the dosing interval, target turnover rate or the presence of competing ligands. For membrane-bound internalizing targets, it is equal to the ratio of internalization rate of mAb-target complex and association rate constant ([Formula: see text]). In cases where soluble and membrane-bound forms of the target co-exist, [Formula: see text] lies within a range determined by the internalization rate ([Formula: see text]) of the mAb-membrane target complex and the ratio of baseline concentrations of soluble and membrane-bound forms ([Formula: see text]). Finally, to demonstrate practical application of these general rules, we collected target expression and turnover data to project [Formula: see text] for a number of marketed mAbs against soluble (TNFα, RANKL, and VEGF) and membrane-bound targets (CD20, EGFR, and HER2).

Translational Pharmacokinetic/Pharmacodynamic Analysis of MYO-029 Antibody for Muscular Dystrophy

Suppression of the myostatin (GDF‐8) pathway has emerged as an important therapeutic paradigm for muscle‐wasting disorders. In this study, we conducted a translational pharmacokinetic/pharmacodynamic (PK/PD) analysis of MYO‐029, an anti‐myostatin monoclonal antibody, using PK data in mice, rats, monkeys, humans, mouse tissue distribution data with ¹²⁵I‐labeled MYO‐029, muscle weight increase in SCID mice, and muscle circumference changes in monkeys. This analysis revealed significant in vivo potency shift between mice and monkeys (72 nM vs. 1.3 μM for 50% effect on quadriceps). Estimated central clearance of MYO‐029 (0.38 mL/h/kg) in humans was greater than twofold higher than typical IgG mAbs. Peak and trough steady‐state exposures of MYO‐029 in patients at biweekly intravenous doses of 10 mg/kg MYO‐029 are predicted to achieve only 50% and 10% of the maximum effect seen in monkeys, respectively. These retrospective analyses results suggest that the MYO‐029 exposures in this trial had a low probability of producing robust efficacy.

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.

Mathematical modeling of receptor occupancy data: A valuable technology for biotherapeutic drug development

BACKGROUND

In drug development, in vivo assessment of target engagement provides confidence when testing the drug's mechanism of action and improves the likelihood of clinical success. For biologics, receptor occupancy (RO) determined from circulating cells can provide evidence of target engagement. Integrating this information with mathematical modeling can further enhance the understanding of drug-target interactions and the biological factors that are critical to the successful modulation of the target and ultimately the disease state.

METHODS

This mini-review presents two specific types of mathematical models used to describe antibody-receptor systems and highlights how experimental data can inform the model parameters. Simulations are used to illustrate how various mechanisms influence RO, PK and total cellular receptor profiles.

RESULTS

The simulations demonstrate the effect antibody-receptor internalization, affinity and receptor turnover have on commonly acquired data in drug development.

CONCLUSIONS

Integrating RO data with mathematical models such as the two presented here (target-mediated drug disposition and site-of-action models) can provide a more comprehensive view of the biological system, which can be used to test hypotheses, extrapolate preclinical findings to humans and impact clinical study designs and risk assessments for the successful development of biotherapeutics.

Measurement of Free Versus Total Therapeutic Monoclonal Antibody in Pharmacokinetic Assessment is Modulated by Affinity, Incubation Time, and Bioanalytical Platform

Decisions about efficacy and safety of therapeutic proteins (TP) designed to target soluble ligands are made in part by their ex vivo quantification. Ligand binding assays (LBAs) are critical tools in measuring serum TP levels in pharmacokinetic, toxicokinetic, and pharmacodynamic studies. This study evaluated the impact of reagent antibody affinities, assay incubation times, and analytical platform on free or total TP quantitation. An ELISA-based LBA that measures monoclonal anti-sclerostin antibody (TPx) was used as the model system. To determine whether the method measures free or total TPx, the effects of K on, K off, and K D were determined. An 8:1 molar ratio of sclerostin (Scl) to TPx compared to a 1:1 molar ratio produced by rabbit polyclonal antibodies to TPx was required to achieve IC50, a measure of TPx interference effectiveness, making it unclear whether the ELISA truly measured free TPx. Kinetic analysis revealed that Scl had a rapid dissociation rate (K off) from TPx and that capture and detection antibodies had significantly higher binding affinities (K D) to TPx. These kinetic limitations along with long ELISA incubation times lead to the higher molar ratios (8:1) required for achieving 50% inhibition of TPx. However, a microfluidic platform with the same reagent pairs required shorter incubations to achieve a lower Scl IC50 molar ratio (1:1). The findings from this study provide the bioanalytical community with a deeper understanding of how reagent and platform selection for LBAs can affect what a particular method measures, either free or total TP concentrations.