Semimechanistic model to characterize nonlinear pharmacokinetics of nimotuzumab in patients with advanced breast cancer

Confounding mitigation for the exposure-response relationship of bevacizumab in colorectal cancer patients

AIMS

The exposure-response relationship of bevacizumab may be confounded by various factors, including baseline characteristics, time-dependent target engagement and recursive relationships between exposure and response, requiring effective mitigation. This study aimed to investigate the exposure-response relationships of bevacizumab in metastatic colorectal cancer (mCRC) patients while mitigating potential biases.

METHODS

Bevacizumab pharmacokinetics was described using target-mediated drug disposition modelling. Relationships between target kinetics, progression-free (PFS) and overall (OS) survivals were assessed using joint pharmacokinetic and parametric hazard function models. Both prognostic-driven and response-driven potential biases were mitigated. These models evaluated the impact of increased antigen target levels, clearance and intensified dosing regimen on survival.

RESULTS

Estimated target-mediated pharmacokinetic parameters in 130 assessed patients were baseline target levels (R0  = 8.4 nM), steady-state dissociation constant (KSS  = 10 nM) and antibody-target complexes elimination constant (kint  = 0.52 day-1 ). The distribution of R0 was significantly associated with increased baseline concentrations of carcinoembryonic antigen, circulating vascular endothelial growth factor and the presence of extrahepatic metastases. Unbound target levels (R) significantly influenced both progression and death hazard functions. Increasing baseline target levels and/or clearance values led to decreased bevacizumab unbound concentrations, increased R levels and shortened PFS and OS, while increasing bevacizumab dose led to decreased R and longer survival.

CONCLUSION

This study is the first to demonstrate the relationship between bevacizumab concentrations, target involvement and clinical efficacy by effectively mitigating potential sources of bias. Most of the target amount may be tumoural in mCRC. Future studies should provide a more in-depth description of this relationship.

Relationship Between Cetuximab Target-Mediated Pharmacokinetics and Progression-Free Survival in Metastatic Colorectal Cancer Patients

BACKGROUND AND OBJECTIVE

Cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal immunoglobulin (Ig)G1 antibody, has been approved for the treatment of metastatic colorectal cancer (mCRC). The influence of target-antigen on cetuximab pharmacokinetics has never been investigated using target-mediated drug disposition (TMDD) modelling. This study aimed to investigate the relationship between cetuximab concentrations, target kinetics and progression-free survival (PFS).

METHODS

In this ancillary study (NCT00559741), 91 patients with mCRC treated with cetuximab were assessed. Influence of target levels on cetuximab pharmacokinetics was described using TMDD modelling. The relationship between cetuximab concentrations, target kinetics and time-to-progression (TTP) was described using a joint pharmacokinetic-TTP model, where unbound target levels were assumed to influence hazard of progression by an Emax model. Mitigation strategies of concentration-response relationship, i.e., time-varying endogenous clearance and mutual influences of clearance and time-to-progression were investigated.

RESULTS

Cetuximab concentration-time data were satisfactorily described using the TMDD model with quasi-steady-state approximation and time-varying endogenous clearance. Estimated target parameters were baseline target levels (R0 = 43 nM), and complex elimination rate constant (kint = 0.95 day-1). Estimated time-varying clearance parameters were time-invariant component of CL (CL0= 0.38 L/day-1), time-variant component of CL (CL1= 0.058 L/day-1) and first-order rate of CL1 decreasing over time (kdes = 0.049 day-1). Part of concentration-TTP was TTP-driven, where clearance and TTP were inversely correlated. In addition, increased target occupancy was associated with increased TTP.

CONCLUSION

This is the first study describing the complex relationship between cetuximab target-mediated pharmacokinetics and PFS in mCRC patients using a joint PK-time-to-progression model. Further studies are needed to provide a more in-depth description of this relationship.

Semi-Mechanistic Pharmacokinetic Model to Guide the Dose Selection of Nimotuzumab in Patients with Autosomal Dominant Polycystic Kidney Disease

Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disease characterized by an overexpression of epidermal growth factor receptor (EGFR). Nimotuzumab is a recombinant humanized monoclonal antibody against human EGFR. The aim of this study was to develop a population pharmacokinetic model for nimotuzumab and to identify demographic and clinical predictive factors of the pharmacokinetic variability. The population pharmacokinetics (PopPK) of nimotuzumab was characterized using a nonlinear mixed-effect modeling approach with NONMEM^®. A total of 422 log-transformed concentration-versus-time datapoints from 20 patients enrolled in a single-center phase I clinical trial were used. Quasi steady state approximation of the full TMDD (target-mediated drug disposition) model with constant target concentration best described the concentration-time profiles. A turnover mediator was included which stimulates the non-specific clearance of mAb in the central compartment in order to explain the reduced levels at higher doses. Covariates had no influence on the PK (pharmacokinetics) parameters. The model was able to detect that the maximum effective dose in ADPKD subjects is 100 mg. The developed PopPK model may be used to guide the dose selection for nimotuzumab during routine clinical practice in patients with polycystic kidney disease. The model will further support the ongoing investigations of the PK/PD relationships of nimotuzumab to improve its therapeutic use in other disease areas.

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).