Chunze Li

Physiologically Based Pharmacokinetic Modeling as a Tool to Predict Drug Interactions for Antibody-Drug Conjugates

Background and ObjectivesMonomethyl auristatin E (MMAE, a cytotoxic agent), upon releasing from valine-citrulline-MMAE (vc-MMAE) antibody-drug conjugates (ADCs), is expected to behave like small molecules. Therefore, evaluating the drug–drug interaction (DDI) potential associated with MMAE is important in the clinical development of ADCs. The objective of this work was to build a physiologically based pharmacokinetic (PBPK) model to assess MMAE–drug interactions for vc-MMAE ADCs.MethodsA PBPK model linking antibody-conjugated MMAE (acMMAE) to its catabolite unconjugated MMAE associated with vc-MMAE ADCs was developed using a mixed ‘bottom-up’ and ‘top-down’ approach. The model was developed using in silico and in vitro data and in vivo pharmacokinetic data from anti-CD22-vc-MMAE ADC. Subsequently, the model was validated using clinical pharmacokinetic data from another vc-MMAE ADC, brentuximab vedotin. Finally, the verified model was used to simulate the results of clinical DDI studies between brentuximab vedotin and midazolam, ketoconazole, and rifampicin.ResultsThe pharmacokinetic profile of acMMAE and unconjugated MMAE following administration of anti-CD22-vc-MMAE was well described by simulations using the developed PBPK model. The model’s performance in predicting unconjugated MMAE pharmacokinetics was verified by successful simulation of the pharmacokinetic profile following brentuximab vedotin administration. The model simulated DDIs, expressed as area under the concentration-time curve (AUC) and maximum concentration (Cmax) ratios, were well within the two-fold of the observed data from clinical DDI studies.ConclusionsThis work is the first demonstration of the use of PBPK modelling to predict MMAE-based DDI potential. The described model can be extended to assess the DDI potential of other vc-MMAE ADCs.

A Pharmacometric Analysis of Patient-Reported Outcomes in Breast Cancer Patients Through Item Response Theory

PurposeAn item response theory (IRT) pharmacometric framework is presented to characterize Functional Assessment of Cancer Therapy-Breast (FACT-B) data in locally-advanced or metastatic breast cancer patients treated with ado-trastuzumab emtansine (T-DM1) or capecitabine-plus-lapatinib.MethodsIn the IRT model, four latent well-being variables, based on FACT-B general subscales, were used to describe the physical, social/family, emotional and functional well-being. Each breast cancer subscale item was reassigned to one of the other subscales. Longitudinal changes in FACT-B responses and covariate effects were investigated.ResultsThe IRT model could describe both item-level and subscale-level FACT-B data. Non-Asian patients showed better baseline social/family and functional well-being than Asian patients. Moreover, patients with Eastern Cooperative Oncology Group performance status of 0 had better baseline physical and functional well-being. Well-being was described as initially increasing or decreasing before reaching a steady-state, which varied substantially between patients and subscales. T-DM1 exposure was not related to any of the latent variables. Physical well-being worsening was identified in capecitabine-plus-lapatinib-treated patients, whereas T-DM1-treated patients typically stayed stable.ConclusionThe developed framework provides a thorough description of FACT-B longitudinal data. It acknowledges the multi-dimensional nature of the questionnaire and allows covariate and exposure effects to be evaluated on responses.

Platform model describing pharmacokinetic properties of vc-MMAE antibody–drug conjugates

Antibody–drug conjugates (ADCs) developed using the valine-citrulline-MMAE (vc-MMAE) platform, consist of a monoclonal antibody (mAb) covalently bound with a potent anti-mitotic toxin (MMAE) through a protease-labile vc linker. Recently, clinical data for a variety of vc-MMAE ADCs has become available. The goal of this analysis was to develop a platform model that simultaneously described antibody-conjugated MMAE (acMMAE) pharmacokinetic (PK) data from eight vc-MMAE ADCs, against different targets and tumor indications; and to assess differences and similarities of model parameters and model predictions, between different compounds. Clinical PK data of eight vc-MMAE ADCs from eight Phase I studies were pooled. A population PK platform model for the eight ADCs was developed, where the inter-compound variability (ICV) was described explicitly, using the third random effect level (ICV), and implemented using LEVEL option of NONMEM 7.3. The PK was described by a two-compartment model with time dependent clearance. Clearance and volume of distribution increased with body weight; volume was higher for males, and clearance mildly decreased with the nominal dose. Michaelis–Menten elimination had only minor effect on PK and was not included in the model. Time-dependence of clearance had no effect beyond the first dosing cycle. Clearance and central volume were similar among ADCs, with ICV of 15 and 5%, respectively. Thus, PK of acMMAE was largely comparable across different vc-MMAE ADCs. The model may be applied to predict PK-profiles of vc-MMAE ADCs under development, estimate individual exposure for the subsequent PK–pharmacodynamics (PD) analysis, and project optimal dose regimens and PK sampling times.

Population pharmacokinetics and exposure-response of trastuzumab emtansine in advanced breast cancer previously treated with ≥2 HER2-targeted regimens

AIMS We conducted population pharmacokinetic (PopPK) and exposure-response analyses for trastuzumab emtansine (T-DM1), to assess the need for T-DM1 dose optimization in patients with low exposure by using TH3RESA [A Study of Trastuzumab Emtansine in Comparison With Treatment of Physicians Choice in Patients With human epidermal growth factor receptor 2 (HER2)-positive Breast Cancer Who Have Received at Least Two Prior Regimens of HER2-directed Therapy] study data (NCT01419197). The randomized phase III TH3RESA study investigated T-DM1 vs. treatment of physicians choice (TPC) in patients with heavily pretreated HER2-positive advanced breast cancer. METHODS We compared a historical T-DM1 PopPK model with T-DM1 pharmacokinetics in TH3RESA and performed exposure-response analyses using model-predicted cycle 1 maximum concentration (Cmax ), cycle 1 minimum concentration (Cmin ) and area under the concentration-time curve at steady state (AUCss ). Kaplan-Meier analyses [overall survival (OS), progression-free survival (PFS)] and logistic regression [overall response rate (ORR), safety] were stratified by T-DM1 exposure metrics. Survival hazard ratios (HRs) in the lowest exposure quartile (Q1) of cycle 1 Cmin were compared with matched TPC-treated patients. RESULTS T-DM1 concentrations in TH3RESA were described well by the historical PopPK model. Patients with higher cycle 1 Cmin and AUCss exhibited numerically longer median OS and PFS and higher ORR than patients with lower exposure. Exposure-response relationships were less evident for cycle 1 Cmax . No relationship between exposure and safety was identified. HRs for the comparison of T-DM1-treated patients in the Q1 subgroup with matched TPC-treated patients were 0.96 [95% confidence interval (CI) 0.63, 1.47] for OS and 0.92 (95% CI 0.64, 1.32) for PFS. CONCLUSIONS Exposure-response relationships for efficacy were inconsistent across exposure metrics. HRs for survival in patients in the lowest T-DM1 exposure quartile vs. matched TPC-treated patients suggest that, compared with TCP, the approved T-DM1 dose is unlikely to be detrimental to patients with low exposure.

Impact of Shed/Soluble targets on the PK/PD of approved therapeutic monoclonal antibodies.

ABSTRACT Introduction: Suboptimal treatment for monoclonal antibodies (mAbs) directed against endogenous circulating soluble targets and the shed extracellular domains (ECD) of the membrane-bound targets is an important clinical concern due to the potential impact of mAbs on the in vivo efficacy and safety. Consequently, there are considerable challenges in the determination of an optimal dose and/or dosing regimen. Areas covered: This review outlines the impact of shed antigen targets from membrane-bound proteins and soluble targets on the PK and/or PD of therapeutic mAbs that have been approved in the last decade. We discuss various bioanalytical techniques that have facilitated the interpretation of the PK/PD properties of therapeutic mAbs and also considered the factors that may impact such measurements. Quantitative approaches include target-mediated PK models and bi- or tri-molecular interaction PK/PD models that describe the relationships between the antibody PK and the ensuing effects on PD biomarkers, to facilitate the mAb PK/PD characterization. Expert commentary: The proper interpretation of PK/PD relationships through the integrated PK/PD modeling and bioanalytical strategy facilitates a mechanistic understanding of the disease processes and dosing regimen optimization, thereby offering insights into developing effective therapeutic regimens. This review provides an overview of the impact of soluble targets or shed ECD on mAb PK/PD properties. We provide examples of quantitative approaches that facilitate the characterization of mAb PK/PD characteristics and their corresponding bioanalytical strategies.

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.

Abstract P4-15-09: Phase 1 study of trastuzumab emtansine in HER2-positive metastatic breast cancer patients with normal or reduced hepatic function

Introduction Trastuzumab emtansine (T-DM1) is an antibody–drug conjugate comprising trastuzumab, a stable linker, and the microtubule inhibitor DM1. In phase 3 studies of HER2-positive metastatic breast cancer (MBC), T-DM1 significantly increased progression-free survival (EMILIA and TH3RESA) and overall survival (EMILIA) vs. control regimens. Few patients (2–4%) treated with T-DM1 experience grade ≥3 increases in transaminases. Currently, there are no data on the pharmacokinetics (PK) of T-DM1 in patients with hepatic impairment. This international, multicenter, open-label, parallel group, phase 1 PK study (BO25499/NCT01513083) is designed to assess the PK of T-DM1 and relevant analytes in MBC patients with normal hepatic function and mild or moderate hepatic impairment; safety and efficacy will also be evaluated. Methods To obtain 8 evaluable patients, up to 10 patients each with HER2-positive MBC and ECOG performance status of 0–2 were enrolled in 1 of 3 independent cohorts based on hepatic function per Child-Pugh criteria: normal hepatic function, mild hepatic impairment (Child-Pugh A), and moderate hepatic impairment (Child-Pugh B). Patients with severe hepatic impairment (Child Pugh C) were ineligible. Patients received 3 cycles of T-DM1 3.6 mg/kg every 3 weeks. After 3 cycles, patients could continue to receive T-DM1 until disease progression, unmanageable toxicity, or study termination in the present study, or enroll in an extension study (BO25430/TDM4529g). PK samples were collected during cycle 1 (days 1 [predose, 30 m and 4 h postinfusion], 2, 3, 4, 8, 11, 15, and 18); cycle 2 (day 1 [predose, 30 m postinfusion]); and cycle 3 (days 1 [predose, 30 m postinfusion], 8, 15, and 22). T-DM1, total trastuzumab, DM1, MCC-DM1, and Lys-MCC-DM1 were measured using validated assays. Adverse events were graded per NCI CTCAE, v4.03. All analyses are descriptive. The clinical cutoff date for this interim analysis was January 30, 2014. Results PK data were fully evaluable for 10 out of 10 patients each in the normal and mild cohorts and for 6 out of 7 patients in the moderate cohort. Compared with the normal cohort, T-DM1 clearance at cycle 1 was ∼1.9- and 3.3-fold faster in the mild and moderate cohorts, respectively. The trend of faster clearance was less apparent for cycle 3 after repeated dosing, with similar T-DM1 exposures across the 3 cohorts. Plasma concentrations of DM1 and DM1-containing catabolites were largely comparable across the 3 cohorts. No new safety signals were seen relative to the known safety profile of T-DM1. Updated safety data will be presented. Conclusions There is a trend for faster clearance of T-DM1 at cycle 1 in patients with mild and moderate hepatic impairment vs. those with normal hepatic function, which can be partly explained by demographic and pathophysiological covariates such as tumor burden, albumin, and body weight. The study’s small sample size could also partly explain the variability. Work to better understand the mechanisms for the observed differences in clearance is ongoing. No increase in the systemic concentration of DM1 was observed in patients with mild or moderate hepatic impairment vs. those with normal hepatic function. No additional safety concerns were observed. Citation Format: Chunze Li, Priya Agarwal, Susan Dent, Anthony Goncalves, Joo-Hee Yi, Alexander Strasak, Marjorie Green, Sandhya Girish, Pat LoRusso. Phase 1 study of trastuzumab emtansine in HER2-positive metastatic breast cancer patients with normal or reduced hepatic function [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-15-09.