An Integrated Multiple-Analyte Pharmacokinetic Model to Characterize Trastuzumab Emtansine (T-DM1) Clearance Pathways and to Evaluate Reduced Pharmacokinetic Sampling in Patients with HER2-Positive Metastatic Breast Cancer

Application of Pharmacometrics in Advancing the Clinical Research of Antibody-Drug Conjugates: Principles and Modeling Strategies

Antibody-drug conjugates (ADCs) have become a pivotal area in the research and development of antitumor drugs. They provide innovative possibilities for tumor therapy by integrating the tumor-targeting capabilities of monoclonal antibodies with the cytotoxic effect of small molecule drugs. Pharmacometrics, an important discipline, facilitates comprehensive understanding of the pharmacokinetic characteristics of ADCs by integrating clinical trial data through modeling and simulation. However, due to the complex structure of ADCs, their modeling approaches are still unclear. In this review, we analyzed published population pharmacokinetic models for ADCs and classified them into single-analyte, two-analyte, and three-analyte models. We also described the benefits, limitations, and recommendations for each model. Furthermore, we suggested that the development of population pharmacokinetic models for ADCs should be rigorously considered and established based on four key aspects: (1) research objectives; (2) available in vitro and animal data; (3) accessible clinical information; and (4) the capability of bioanalytical methods. This review offered insights to guide the application of pharmacometrics in the clinical research of ADCs, thereby contributing to more effective therapeutic development.

Pharmacokinetics and pharmacodynamics of antibody-drug conjugates for the treatment of patients with breast cancer

INTRODUCTION

Currently three antibody-drug-conjugates (ADC) are approved by the European Medicines Agency (EMA) for treatment of breast cancer (BC) patient: trastuzumab-emtansine, trastuzumab-deruxtecan and sacituzumab-govitecan. ADC are composed of a monoclonal antibody (mAb) targeting a specific antigen, a cytotoxic payload and a linker. Pharmacokinetics (PK) and pharmacodynamics (PD) distinguish ADC from conventional chemotherapy and must be understood by clinicians.

AREAS COVERED

Our review delineates the PK/PD profiles of ADC approved for the treatment of BC with insight for future development. This is an expert opinion literature review based on the EMA's Assessment Reports, enriched by a comprehensive literature search performed on Medline in August 2023.

EXPERT OPINION

All three ADC distributions are described by a two-compartment structure: tissue and serum. Payload concentration peak is immediate but remains at low concentration. The distribution varied for all ADC only with body weight. mAb will be metabolised firstly by the saturable complex formation of ADC/Tumour-Receptor and secondly by binding of FcgRs in immune cells. They are all excreted in the bile and faeces with minimal urine elimination. Dose adjustments, apart from weight, are not recommended. Novel ADC are composed of cleavable linkers with various targets/payloads with the same PK/PD properties, but novel structures of ADC are in development.

Integrated multiple analytes and semi-mechanistic population pharmacokinetic model of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate

Tusamitamab ravtansine (SAR408701) is an antibody-drug conjugate (ADC), combining a humanized monoclonal antibody (IgG1) targeting carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) and a potent cytotoxic maytansinoid derivative, DM4, inhibiting microtubule assembly. SAR408701 is currently in clinical development for the treatment of advanced solid tumors expressing CEACAM5. It is administered intravenously as a conjugated antibody with an average Drug Antibody Ratio (DAR) of 3.8. During SAR408701 clinical development, four entities were measured in plasma: conjugated antibody (SAR408701), naked antibody (NAB), DM4 and its methylated metabolite (MeDM4), both being active. Average DAR and proportions of individual DAR species were also assessed in a subset of patients. An integrated and semi-mechanistic population pharmacokinetic model describing the time-course of all entities in plasma and DAR measurements has been developed. All DAR moieties were assumed to share the same drug disposition parameters, excepted for clearance which differed for DAR0 (i.e. NAB entity). The conversion of higher DAR to lower DAR resulted in a DAR-dependent ADC deconjugation and was represented as an irreversible first-order process. Each conjugated antibody was assumed to contribute to DM4 formation. All data were fitted simultaneously and the model developed was successful in describing the pharmacokinetic profile of each entity. Such a structural model could be translated to other ADCs and gives insight of mechanistic processes governing ADC disposition. This framework will further be expanded to evaluate covariates impact on SAR408701 pharmacokinetics and its derivatives, and thus can help identifying sources of pharmacokinetic variability and potential efficacy and safety pharmacokinetic drivers.

Impact of Physiologically Based Pharmacokinetics, Population Pharmacokinetics and Pharmacokinetics/Pharmacodynamics in the Development of Antibody-Drug Conjugates

Antibody‐drug conjugates are important molecular entities in the treatment of cancer, with 8 antibody‐drug conjugates approved by the US Food and Drug Administration since 2000 and many more in early‐ and late‐stage clinical development. These conjugates combine the target specificity of monoclonal antibodies with the potent anticancer activity of small‐molecule therapeutics. The complex structure of antibody‐drug conjugates poses unique challenges to pharmacokinetic (PK) and pharmacodynamic (PD) characterization because it requires a quantitative understanding of the PK and PD properties of multiple different molecular species (eg, conjugate, total antibody, and unconjugated payload) in different tissues. Quantitative clinical pharmacology using mathematical modeling and simulation provides an excellent approach to overcome these challenges, as it can simultaneously integrate the disposition, PK, and PD of antibody‐drug conjugates and their components in a quantitative manner. In this review, we highlight diverse quantitative clinical pharmacology approaches, ranging from system models (eg, physiologically based pharmacokinetic [PBPK] modeling) to mechanistic and empirical models (eg, population PK/PD modeling for single or multiple analytes, exposure‐response modeling, platform modeling by pooling data across multiple antibody‐drug conjugates). The impact of these PBPK and PK/PD models to provide insights into clinical dosing justification and inform drug development decisions is also highlighted.

Capturing the Magic Bullet: Pharmacokinetic Principles and Modeling of Antibody-Drug Conjugates

Over the past two decades, antibody-drug conjugates (ADCs) have emerged as a promising class of drugs for cancer therapy and have expanded to nononcology fields such as inflammatory diseases, atherosclerosis, and bacteremia. Eight ADCs are currently approved by FDA for clinical applications, with more novel ADCs under clinical development. Compared with traditional chemotherapy, ADCs combine the target specificity of antibodies with chemotherapeutic capabilities of cytotoxic drugs. The benefits include reduced systemic toxicity and enhanced therapeutic index for patients. However, the heterogeneous structures of ADCs and their dynamic changes following administration create challenges in their development. The understanding of ADC pharmacokinetics (PK) is crucial for the optimization of clinical dosing regimens when translating from animal to human. In addition, it contributes to the optimization of dose selection and clinical monitoring with regard to safety and efficacy. This manuscript reviews the PK characteristics of ADCs and summarizes the diverse approaches for PK modeling that can be used to evaluate an ADC at the preclinical and clinical stages to support their successful development. Despite the numerous available options, fit-for-purpose modeling approaches for the PK and PD of ADCs should be critically planned and well-thought-out to adequately support the development of an ADC.

Antibody Conjugates-Recent Advances and Future Innovations

Monoclonal antibodies have evolved from research tools to powerful therapeutics in the past 30 years. Clinical success rates of antibodies have exceeded expectations, resulting in heavy investment in biologics discovery and development in addition to traditional small molecules across the industry. However, protein therapeutics cannot drug targets intracellularly and are limited to soluble and cell-surface antigens. Tremendous strides have been made in antibody discovery, protein engineering, formulation, and delivery devices. These advances continue to push the boundaries of biologics to enable antibody conjugates to take advantage of the target specificity and long half-life from an antibody, while delivering highly potent small molecule drugs. While the "magic bullet" concept produced the first wave of antibody conjugates, these entities were met with limited clinical success. This review summarizes the advances and challenges in the field to date with emphasis on antibody conjugation, linker-payload chemistry, novel payload classes, absorption, distribution, metabolism, and excretion (ADME), and product developability. We discuss lessons learned in the development of oncology antibody conjugates and look towards future innovations enabling other therapeutic indications.

An Integrated Population Pharmacokinetic Model Versus Individual Models of Depatuxizumab Mafodotin, an Anti-EGFR Antibody Drug Conjugate, in Patients With Solid Tumors Likely to Overexpress EGFR

Depatuxizumab mafodotin (depatux-m) is an antibody-drug conjugate (ADC) designed for the treatment of tumors expressing epidermal growth factor receptor (EGFR), consisting of a veneered "humanized" recombinant IgG1κ antibody that has binding properties specific to a unique epitope of human EGFR with noncleavable maleimido-caproyl linkers each attached to a potent antimitotic cytotoxin, monomethyl auristatin F. We aimed to describe the development and comparison of 2 population pharmacokinetic modeling approaches. Data from 2 phase 1 studies enrolling patients with glioblastoma multiforme or advanced solid tumors were included in the analysis. Patients in these studies received doses of depatux-m ranging from 0.5 to 4.0 mg/kg as monotherapy, in combination with temozolomide, or radiation plus temozolomide depending on the study and/or arm. First, an integrated ADC model to simultaneously describe the concentration-time data for ADC, total antibody, and cys-mafodotin was built using a 2-compartment model for ADC for each drug-to-antibody ratio. Then, 3 individual models were developed for ADC, total antibody, and cys-mafodotin separately using 2-compartment models for ADC and total antibody and a 1-compartment model for cys-mafodotin. Visual predictive checks suggested accurate model fitting across a range of concentrations. The analysis showed that both an integrated complex ADC model and the individual models that have shorter computational time would result in similar outcomes.

Antibody-Drug Conjugates as Cancer Therapeutics: Past, Present, and Future

Antibody-drug conjugates (ADCs) represent an innovative therapeutic approach that provides novel treatment options and hope for patients with cancer. By coupling monoclonal antibodies (mAbs) to cytotoxic small-molecule payloads with a plasma-stable linker, ADCs offer the potential for increased drug specificity and fewer off-target effects than systemic chemotherapy. As evidence for the potential of these therapies, many new ADCs are in various stages of clinical development. Because their structure poses unique challenges to pharmacokinetic and pharmacodynamic characterization, it is critical to recognize the differences between ADCs and conventional chemotherapy in the design of ADC clinical development strategies. Although some properties may be determined mainly by either the mAb or the small-molecule portion, the behavior of these agents is not always predictable. Furthermore, because the absorption, distribution, metabolism, and excretion (ADME) of ADCs are influenced by all 3 of its components (mAb, linker, and payload), it is important to characterize the intact molecule, any target-mediated catabolic clearance of the mAb, and the ADME properties of the small-molecule payload. Here we describe key issues in the clinical development of ADCs, including considerations for designing first-in-human studies for ADCs. We discuss some difficulties of ADC pharmacokinetic characterization and current approaches to overcoming these challenges. Finally, we consider all aspects of clinical pharmacology assessment required during drug development, using examples from the literature to illustrate the discussion.

Development of a Translational Physiologically Based Pharmacokinetic Model for Antibody-Drug Conjugates: a Case Study with T-DM1

Systems pharmacokinetic (PK) models that can characterize and predict whole body disposition of antibody-drug conjugates (ADCs) are needed to support (i) development of reliable exposure-response relationships for ADCs and (ii) selection of ADC targets with optimal tumor and tissue expression profiles. Towards this goal, we have developed a translational physiologically based PK (PBPK) model for ADCs, using T-DM1 as a tool compound. The preclinical PBPK model was developed using rat data. Biodistribution of DM1 in rats was used to develop the small molecule PBPK model, and the PK of conjugated trastuzumab (i.e., T-DM1) in rats was characterized using platform PBPK model for antibody. Both the PBPK models were combined via degradation and deconjugation processes. The degradation of conjugated antibody was assumed to be similar to a normal antibody, and the deconjugation of DM1 from T-DM1 in rats was estimated using plasma PK data. The rat PBPK model was translated to humans to predict clinical PK of T-DM1. The translation involved the use of human antibody PBPK model to characterize the PK of conjugated trastuzumab, use of allometric scaling to predict human clearance of DM1 catabolites, and use of monkey PK data to predict deconjugation of DM1 in the clinic. PBPK model-predicted clinical PK profiles were compared with clinically observed data. The PK of total trastuzumab and T-DM1 were predicted reasonably well, and slight systemic deviations were observed for the PK of DM1-containing catabolites. The ADC PBPK model presented here can serve as a platform to develop models for other ADCs.

What is the role for population pharmacokinetics in hemophilia?

Prevention of bleeding in hemophilia requires that plasma levels of the deficient factor exceed the desired minimum target level. Large interindividual variability suggests that knowledge of individual pharmacokinetic (PK) would help to achieve this goal, simultaneously minimizing infusion frequency and the amount of concentrate used. Population PK (PopPK) allows for the incorporation of determinants of interpatient variability and eliminates the need for extensive postinfusion plasma sampling. Barriers to implementation of PopPK are the need for concentrate specific models, Bayesian calculation power, specific expertise for validation and appraisal of forecasted estimates. The Web Accessible Population Pharmacokinetic Service – Hemophilia ( www.wapps-hemo.org ), developed by an international research network of hemophilia centers will test if PK-guided dose individualization can improve patient important outcomes in hemophilia.

Integrated Two-Analyte Population Pharmacokinetic Model for Antibody-Drug Conjugates in Patients: Implications for Reducing Pharmacokinetic Sampling

An integrated pharmacokinetics (PK) model that simultaneously describes concentrations of total antibody (Tab) and antibody‐conjugated monomethyl auristatin E (acMMAE) following administration of monomethyl auristatin E (MMAE)‐containing antibody–drug conjugates (ADCs) was developed based on phase I PK data with extensive sampling for two ADCs. Two linear two‐compartment models that shared all parameters were used to describe the PK of Tab and acMMAE, except that the deconjugation rate was an additional clearance pathway included in the acMMAE PK model compared to Tab. Further, the model demonstrated its ability to predict Tab concentrations and PK parameters based on observed acMMAE PK and various reduced or eliminated Tab PK sampling schemes of phase II data. Thus, this integrated model allows for the reduction of Tab PK sampling in late‐phase clinical development without compromising Tab PK characterization.

Development and Translational Application of an Integrated, Mechanistic Model of Antibody-Drug Conjugate Pharmacokinetics

Antibody drug conjugates (ADC), in which small molecule cytotoxic agents are non-specifically linked to antibodies, can enable targeted delivery of chemotherapeutics to tumor cells. ADCs are often produced and administered as a mixture of conjugated antibodies with different drug to antibody ratios (DAR) resulting in complex and heterogeneous disposition kinetics. We developed a mechanism-based platform model that can describe and predict the complex pharmacokinetic (PK) behavior of ADCs with protease-cleavable valine-citrulline (VC) linker linked to Monomethylmonomethyl auristatin F/E by incorporating known mechanisms of ADC disposition. The model includes explicit representation of all DAR species; DAR-dependent sequential deconjugation of the drug, resulting in the conversion of higher DAR to lower DAR species; and DAR-dependent antibody/ADC clearance. PK profiles of multiple analytes (total antibody, drug-conjugated antibody, and/or antibody-conjugated drug) for different ADC molecules and targets in rodents and cynomolgus monkeys were used for model development. The integrated cross-species model was successful in capturing the multi-analyte PK profiles after administration of purified ADCs with defined DAR species and ADCs with mixtures of DAR. Human PK predictions for DSTP3086S (anti-STEAP1-vc-MMAE) with the platform model agreed well with PK (total antibody and antibody-conjugated drug concentrations) measurements in the dose-ranging phase I clinical study. The integrated model is applicable to various other ADCs with different formats, conjugated drugs, and linkers, and provides a valuable tool for the exploration of mechanisms governing disposition of ADCs and enables translational predictions.

Determination of Cellular Processing Rates for a Trastuzumab-Maytansinoid Antibody-Drug Conjugate (ADC) Highlights Key Parameters for ADC Design

Antibody-drug conjugates (ADCs) are a promising class of cancer therapeutics that combine the specificity of antibodies with the cytotoxic effects of payload drugs. A quantitative understanding of how ADCs are processed intracellularly can illustrate which processing steps most influence payload delivery, thus aiding the design of more effective ADCs. In this work, we develop a kinetic model for ADC cellular processing as well as generalizable methods based on flow cytometry and fluorescence imaging to parameterize this model. A number of key processing steps are included in the model: ADC binding to its target antigen, internalization via receptor-mediated endocytosis, proteolytic degradation of the ADC, efflux of the payload out of the cell, and payload binding to its intracellular target. The model was developed with a trastuzumab-maytansinoid ADC (TM-ADC) similar to trastuzumab-emtansine (T-DM1), which is used in the clinical treatment of HER2+ breast cancer. In three high-HER2-expressing cell lines (BT-474, NCI-N87, and SK-BR-3), we report for TM-ADC half-lives for internalization of 6-14 h, degradation of 18-25 h, and efflux rate of 44-73 h. Sensitivity analysis indicates that the internalization rate and efflux rate are key parameters for determining how much payload is delivered to a cell with TM-ADC. In addition, this model describing the cellular processing of ADCs can be incorporated into larger pharmacokinetics/pharmacodynamics models, as demonstrated in the associated companion paper.

Integration of bioanalytical measurements using PK-PD modeling and simulation: implications for antibody-drug conjugate development

Recent technological advances have enabled precise quantitation of various bioanalytical measurements pertaining to antibody-drug conjugates (ADCs). However, availability of bioanalytical data alone cannot guarantee the provision of correct go/no-go decisions at different stages of ADC development. Integration and comprehension of all the available data at each stage of ADC development is necessary to make a well informed and objective decision about moving the ADC forward to the clinic. In this manuscript, we have reviewed the application of PK-PD modeling and simulation for quantitative integration of diverse bioanalytical data available from different stages of ADC development. We have also elaborated on how similar bioanalytical data can be characterized using different models to gain distinct insights into ADC development.

Pharmacokinetics of Selected Anticancer Drugs in Elderly Cancer Patients: Focus on Breast Cancer

Background: Elderly patients receiving anticancer drugs may have an increased risk to develop treatment-related toxicities compared to their younger peers. However, a potential pharmacokinetic (PK) basis for this increased risk has not consistently been established yet. Therefore, the objective of this study was to systematically review the influence of age on the PK of anticancer agents frequently administered to elderly breast cancer patients. Methods: A literature search was performed using the PubMed electronic database, Summary of Product Characteristics (SmPC) and available drug approval reviews, as published by EMA and FDA. Publications that describe age-related PK profiles of selected anticancer drugs against breast cancer, excluding endocrine compounds, were selected and included. Results: This review presents an overview of the available data that describe the influence of increasing age on the PK of selected anticancer drugs used for the treatment of breast cancer. Conclusions: Selected published data revealed differences in the effect and magnitude of increasing age on the PK of several anticancer drugs. There may be clinically-relevant, age-related PK differences for anthracyclines and platina agents. In the majority of cases, age is not a good surrogate marker for anticancer drug PK, and the physiological state of the individual patient may better be approached by looking at organ function, Charlson Comorbidity Score or geriatric functional assessment.

Trastuzumab emtansine in advanced human epidermal growth factor receptor 2-positive breast cancer

INTRODUCTION

Ado- trastuzumab emtansine (T-DM1) is a human epidermal growth factor receptor 2 (HER2)-targeted antibody-drug conjugate composed of trastuzumab, a stable linker (MCC), and the cytotoxic agent DM1 (derivative of maytansine; mertansine). T-DM1 retains the mechanisms of action of trastuzumab, but also acts as a, selectively delivered, tubulin inhibitor. Following antigen-mediated binding to the tumor cell, T-DM1 is endocytosed and intracellularly catabolized resulting in the release of its cytotoxic moiety.

AREAS COVERED

T-DM1 has completed Phase III development and compared favorably with the lapatinib/capecitabine combination with a superior response rate (objective response rate [ORR]) and duration of response, longer duration of disease control (progression-free survival [PFS]), prolonged overall survival and improved tolerability and quality of life in patients with prior treatment with trastuzumab and a taxane. In a separate Phase III, T-DM1 was compared with any other chosen regimen in patients who had at least received two prior HER2-directed therapies. T-DM1 nearly doubled PFS.

EXPERT OPINION

T-DM1 (Kadcyla) has become the treatment of choice in second-line and beyond for patients with advanced HER2-expressing breast cancer.

Trastuzumab emtansine: a review of its use in patients with HER2-positive advanced breast cancer previously treated with trastuzumab-based therapy

Trastuzumab emtansine (Kadcyla™) is an antibody-drug conjugate consisting of the humanized anti-human epidermal growth factor receptor (HER) 2 antibody trastuzumab covalently linked to the highly potent microtubule inhibitory drug DM1 (a cytotoxic derivative of maytansine) via a stable thioether linker. Intravenous trastuzumab emtansine was recently approved for use in patients with HER2-positive, unresectable, locally advanced (in the EU) or metastatic (in the USA and EU) breast cancer who had previously received trastuzumab and a taxane (separately or in combination), making it the first antibody-drug conjugate approved in this indication. This article reviews the efficacy and tolerability of trastuzumab emtansine in these patients and summarizes its pharmacology. In the well-designed EMILIA study, trastuzumab emtansine significantly prolonged progression-free survival and overall survival, relative to treatment with lapatinib plus capecitabine, in patients with HER2-positive, unresectable, locally advanced or metastatic breast cancer who were previously treated with trastuzumab and a taxane. Trastuzumab emtansine was generally well tolerated in this study, with <6% of patients discontinuing treatment because of adverse events. Based on its efficacy and favourable tolerability, the US National Comprehensive Cancer Network guidelines recommend trastuzumab emtansine as the preferred option in patients with HER2-positive metastatic breast cancer who have received previous trastuzumab-based therapy.

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.

Beyond peptides and mAbs--current status and future perspectives for biotherapeutics with novel constructs

Biotherapeutics are attractive anti-cancer agents due to their high specificity and limited toxicity compared to conventional small molecules. Antibodies are widely used in cancer therapy, either directly or conjugated to a cytotoxic payload. Peptide therapies, though not as prevalent, have been utilized in hormonal therapy and imaging. The limitations associated with unmodified forms of both types of biotherapeutics have led to the design and development of novel structures, which incorporate key features and structures that have improved the molecules' abilities to bind to tumor targets, avoid degradation, and exhibit favorable pharmacokinetics. In this review, we highlight the current status of monoclonal antibodies and peptides, and provide a perspective on the future of biotherapeutics using novel constructs.

Application of Pharmacokinetic-Pharmacodynamic Modeling and Simulation for Antibody-Drug Conjugate Development

Characterization and prediction of the pharmacokinetics (PK) and pharmacodynamics (PD) of Antibody-Drug Conjugates (ADCs) is challenging, since it requires simultaneous quantitative understanding about the PK-PD properties of three different molecular species i.e., the monoclonal antibody, the drug, and the conjugate. Mathematical modeling and simulation provides an excellent tool to overcome these challenges, as it can simultaneously integrate the PK-PD of ADCs and their components in a quantitative manner. Additionally, the computational PK-PD models can also serve as a cornerstone for the model-based drug development and preclinical-to-clinical translation of ADCs. To provide an overview of this subject matter, this manuscript reviews the PK-PD models applicable to ADCs. Additionally, the usage of these models during different drug development stages (i.e., discovery, preclinical development, and clinical development) is also emphasized. The importance of PK-PD modeling and simulation in making rationale go/no-go decisions throughout the drug development process is also highlighted. There is an array of PK-PD models available, ranging from the systems models specifically developed for ADCs to the empirical models applicable to all chemotherapeutic agents, which one can employ for ADCs. The decision about which model to choose depends on the questions to be answered, time at hand, and resources available.

Semi-mechanistic Multiple-Analyte Pharmacokinetic Model for an Antibody-Drug-Conjugate in Cynomolgus Monkeys

Purpose

A semi-mechanistic multiple-analyte population pharmacokinetics (PK) model was developed to describe the complex relationship between the different analytes of monomethyl auristatin E (MMAE) containing antibody-drug conjugates (ADCs) and to provide insight regarding the major pathways of conjugate elimination and unconjugated MMAE release in vivo.

Methods

For an anti-CD79b-MMAE ADC the PK of total antibody (Tab), conjugate (evaluated as antibody conjugated MMAE or acMMAE), and unconjugated MMAE were quantified in cynomolgus monkeys for single (0.3, 1, or 3 mg/kg), and multiple doses (3 or 5 mg/kg, every-three-weeks for 4 doses). The PK data of MMAE in cynomolgus monkeys, after intravenous administration of MMAE at single doses (0.03 or 0.063 mg/kg), was included in the analysis. A semi-mechanistic model was developed and parameter estimates were obtained by simultaneously fitting the model to all PK data using a hybrid ITS-MCPEM method.

Results

The final model well described the observed Tab, acMMAE and unconjugated MMAE concentration-time profiles. Analysis suggested that conjugate is lost via both proteolytic degradation and deconjugation, while unconjugated MMAE in systemic circulation appears to be mainly released via proteolytic degradation of the conjugate.

Conclusions

Our model improves the understanding of ADC catabolism, which may provide useful insights when designing future ADCs.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-014-1585-y) contains supplementary material, which is available to authorized users.

Ado-trastuzumab emtansine: a HER2-positive targeted antibody-drug conjugate

OBJECTIVE

To review the pharmacology, pharmacokinetics, efficacy, adverse effects, drug-drug interactions, dosage and administration, and formulary considerations for ado-trastuzumab emtansine.

DATA SOURCES

Sources of information were identified through a PubMed search (1966 to June 2014) using the key terms ado-trastuzumab emtansine, trastuzumab-DM1, trastuzumab-MCC-DM1, and T-DM1. Other information was obtained from clinicaltrials.gov, product labeling, and press releases.

STUDY SELECTION AND DATA EXTRACTION

All English-language clinical trials and abstracts evaluating ado-trastuzumab emtansine in humans were reviewed for inclusion.

DATA SYNTHESIS

Overexpression or amplification of human epidermal growth factor receptor 2 (HER2) occurs in approximately 20% of breast cancers and is associated with more aggressive tumors and poorer prognosis in the absence of treatment. Although effective therapies for the initial management of HER2-positive metastatic breast cancer (MBC) exist, many patients will experience disease progression. Most second-line therapies are associated with either significant toxicities or limited improvements in overall survival (OS). Ado-trastuzumab emtansine is a HER2-positive directed antibody drug conjugate (ADC) approved in February 2013. In phase III clinical trials comparing the efficacy and safety of ado-trastuzumab emtansine with lapatinib-capecitabine or physician's choice, ado-trastuzumab emtansine had a better tolerability profile and improved progression-free survival compared with lapatinib-capecitabine or physician's choice and increased OS compared with lapatinib-capecitabine.

CONCLUSION

Ado-trastuzumab emtansine is a novel ADC effective for HER2-positive MBC in patients previously treated with trastuzumab, lapatinib, and a taxane. Further studies will determine its use in the adjuvant and neoadjuvant setting and in combination with pertuzumab.

Absorption, distribution, metabolism, and excretion considerations for the development of antibody-drug conjugates

Antibody-drug conjugates (ADCs) are a class of therapeutics that are designed to deliver potent small-molecule drugs selectively to cells that express a specific target antigen while limiting systemic exposure to the drug. This is accomplished by conjugating a potent drug onto an antibody-based therapeutic with a linker that is exquisitely stable in plasma. The development of an effective ADC requires optimizing a number of design elements and an extensive understanding of absorption, distribution, metabolism/catabolism, and elimination (ADME) processes for the ADC construct. Furthermore, as ADCs are a combination of an antibody and small-molecule drug, understanding key aspects of the ADME of each individual component is needed. This review aims to provide considerations for the development of ADCs from an ADME point of view.

Ado-trastuzumab Emtansine (T-DM1): an antibody-drug conjugate (ADC) for HER2-positive breast cancer

Ado-trastuzumab emtansine (T-DM1) is an antibody-drug conjugate that combines the antitumor properties of the humanized anti-human epidermal growth factor receptor 2 (HER2) antibody, trastuzumab, with the maytansinoid, DM1, a potent microtubule-disrupting agent, joined by a stable linker. Upon binding to HER2, the conjugate is internalized via receptor-mediated endocytosis, and an active derivative of DM1 is subsequently released by proteolytic degradation of the antibody moiety within the lysosome. Initial clinical evaluation led to a phase III trial in advanced HER2-positive breast cancer patients who had relapsed after prior treatment with trastuzumab and a taxane, which showed that T-DM1 significantly prolonged progression-free and overall survival with less toxicity than lapatinib plus capecitabine. In 2013, T-DM1 received FDA approval for the treatment of patients with HER2-positive metastatic breast cancer who had previously received trastuzumab and a taxane, separately or in combination, the first ADC to receive full approval based on a randomized study.

Methods to detect non-compliance and reduce its impact on population PK parameter estimates

This work proposes and evaluates two methods (CM1 and CM2) for detecting non-compliance using concentration-time data and for obtaining estimates of population pharmacokinetic model parameters in a population with prevalent non-compliance. CM1 estimates individual residual variability (RV) and identifies subjects with higher than average RV as non-compliant. Exclusion of subjects with high RV from the analysis dataset reduces the bias in the estimates of the model parameters. Various methods of identification and exclusion of non-compliant subjects were tested, compared, and shown to reduce or eliminate bias in parameter estimates associated with non-compliance. The tested methods were (i) a pre-defined cutoff value of the random effect on RV, (ii) sequential exclusion of subjects with the highest RV percentiles, and (iii) use of a mixture model for RV. CM2 is applicable for the data with a specific sampling pattern that includes a potentially non-compliant outpatient part with several trough samples followed by a dense profile after the inpatient (compliant) dose. It relies only on the doses known to be administered (e.g., inpatient doses). In this method, all concentration measurements during the outpatient part of the study (except the trough value immediately preceding the inpatient dose) are removed from the dataset and an additional parameter (individual relative bioavailability of the outpatient doses) is introduced. For a number of simulated datasets with various sampling schemes and non-compliance patterns the proposed methods allowed to identify subjects with compliance problems and to reduce or eliminate bias in the estimates of the model parameters.

Population pharmacokinetics of trastuzumab emtansine (T-DM1), a HER2-targeted antibody-drug conjugate, in patients with HER2-positive metastatic breast cancer: clinical implications of the effect of covariates

Purpose

Trastuzumab emtansine (T-DM1) is an antibody–drug conjugate comprising the humanized monoclonal antibody trastuzumab linked to DM1, a highly potent cytotoxic agent. A population pharmacokinetic (PK) analysis was performed to estimate typical values and interindividual variability of T-DM1 PK parameters and the effects of clinically relevant covariates.

Methods

Serum samples were collected from 671 patients with human epidermal growth factor receptor 2-positive locally advanced or metastatic breast cancer (MBC) who received single-agent T-DM1 in five phase I to phase III studies. Nonlinear mixed-effects modeling with the first-order conditional estimation method was used.

Results

A linear two-compartment model with first-order elimination from the central compartment described T-DM1 PKs in the clinical dose range. T-DM1 elimination clearance was 0.676 L/day, volume of distribution in the central compartment (V_c) was 3.127 L, and terminal elimination half-life was 3.94 days. Age, race, region, and renal function did not influence T-DM1 PK. Given the low-to-moderate effect of all statistically significant covariates on T-DM1 exposure, none of these covariates is expected to result in a clinically meaningful change in T-DM1 exposure.

Conclusions

T-DM1 PK properties are consistent and predictable in patients. A further refinement of dose based on baseline covariates other than body weight for the current 3.6 mg/kg regimen would not yield clinically meaningful reductions in interindividual PK variability in patients with MBC.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-014-2500-2) contains supplementary material, which is available to authorized users.

A mechanistic pharmacokinetic model elucidating the disposition of trastuzumab emtansine (T-DM1), an antibody-drug conjugate (ADC) for treatment of metastatic breast cancer

Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate (ADC) therapeutic for treatment of human epidermal growth factor receptor 2 (HER2)-positive cancers. The T-DM1 dose product contains a mixture of drug-to-antibody ratio (DAR) moieties whereby the small molecule DM1 is chemically conjugated to trastuzumab antibody. The pharmacokinetics (PK) underlying this system and other ADCs are complex and have not been elucidated. Accordingly, we have developed two PK modeling approaches from preclinical data to conceptualize and understand T-DM1 PK, to quantify rates of DM1 deconjugation, and to elucidate the link between trastuzumab, T-DM1, and DAR measurements. Preclinical data included PK studies in rats (n = 34) and cynomolgus monkeys (n = 18) at doses ranging from 0.3 to 30 mg/kg and in vitro plasma stability. T-DM1 and total trastuzumab (TT) plasma concentrations were measured by enzyme-linked immunosorbent assay. Individual DAR moieties were measured by affinity capture liquid chromatography-mass spectrophotometry. Two PK modeling approaches were developed for T-DM1 using NONMEM 7.2 software: a mechanistic model fit simultaneously to TT and DAR concentrations and a reduced model fit simultaneously to TT and T-DM1 concentrations. DAR moieties were well described with a three-compartmental model and DM1 deconjugation in the central compartment. DM1 deconjugated fastest from the more highly loaded trastuzumab molecules (i.e., DAR moieties that are ≥3 DM1 per trastuzumab). T-DM1 clearance (CL) was 2-fold faster than TT CL due to deconjugation. The two modeling approaches provide flexibility based on available analytical measurements for T-DM1 and a framework for designing ADC studies and PK-pharmacodynamic modeling of ADC efficacy- and toxicity-related endpoints.

Comparative clinical pharmacokinetics of antibody-drug conjugates in first-in-human Phase 1 studies

Although there are currently more than 30 antibody-drug conjugates (ADC) in clinical development for the treatment of blood cancers and solid tumors, comparison of their clinical pharmacokinetics (PK) is challenging because of the large number of, and differences between, the targets, ADC constructs, dosing regimens, and patient populations. In this review, we standardized the evaluation, using non-compartmental PK data reported at Cycle 1, i.e., following the first drug administration of what is usually a repeated-dose treatment, in monotherapy. We report ADC clinical PK properties, dosing regimen, determination of doses ranges and associated maximum tolerated doses. We also evaluated the effect of structural characteristics and target types (hematological vs. solid tumors) on PK. In addition, we discuss how integration of PK/pharmacodynamics approaches on top of classical dose escalation in first-in-human studies may improve dosing regimen determination for subsequent phases of clinical development.

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.