Time-dependent clearance can confound exposure-response analysis of therapeutic antibodies: A comprehensive review of the current literature.

Exposure-response (ER) analysis is used to optimize dose and dose regimens during clinical development. Characterization of relationships between drug exposure and efficacy or safety outcomes can be utilized to make dose adjustments that improve patient response. Therapeutic antibodies typically show predictable pharmacokinetics (PK) but can exhibit clearance that decreases over time due to treatment. Moreover, time-dependent changes in clearance are frequently associated with drug response, with larger decreases in clearance and increased exposure seen in patients who respond to treatment. This often confounds traditional ER analysis, as drug response influences exposure rather than the reverse. In this review, we survey published population PK analyses for reported time-dependent drug clearance effects across 158 therapeutic antibodies approved or in regulatory review. We describe the mechanisms by which time-dependent clearance can arise, and evaluate trends in frequency, magnitude, and time scale of changes in clearance with respect to indication, mechanistic interpretation of time-dependence, and PK modeling techniques employed. We discuss the modeling and simulation strategies commonly used to characterize time-dependent clearance, and examples where time-dependent clearance has impeded ER analysis. A case study using population model simulation was explored to interrogate the impact of time-dependent clearance on ER analysis and how it can lead to spurious conclusions. Overall, time-dependent clearance arises frequently among therapeutic antibodies and has spurred erroneous conclusions in ER analysis. Appropriate PK modeling techniques aid in identifying and characterizing temporal shifts in exposure that may impede accurate ER assessment and successful dose optimization.

Population pharmacokinetics of zanidatamab, an anti-HER2 biparatopic antibody, in patients with advanced or metastatic cancer.

PURPOSE: To characterize the pharmacokinetics (PK) of zanidatamab including evaluation of the impact of intrinsic and extrinsic patient factors. To investigate alternative dosing regimens to improve caregiver convenience and reduce zanidatamab wastage. METHODS: Serum zanidatamab concentrations were obtained from 305 patients with advanced or metastatic breast cancer, gastroesophageal adenocarcinoma (GEA), biliary tract cancer, and other HER2-expressing cancers from four ongoing phase I and II clinical trials. Zanidatamab PK were described using population methods. The exposure of alternative dosing regimens and the impact of dose delay was estimated by model simulation. RESULTS: A two-compartment model with parallel linear and nonlinear clearance from the central compartment adequately described zanidatamab PK. At the recommended dose regimens of 20 mg/kg Q2W and 30 mg/kg Q3W, zanidatamab clearance was primarily linear at steady state. At steady state, 30 mg/kg Q3W zanidatamab returns within 10% of the steady state trough after 2 subsequent doses following either a 1-week or 2-week dose delay. Statistically significant covariates included in the final model were body weight, sex, albumin, GEA cancer type, baseline tumor size, and presence of post-baseline anti-drug antibodies, all of which resulted in less than 30% impact on exposure. Model simulation predicts weight-based and two-tiered flat dosing will result in similar exposure and variability. CONCLUSION: The identified significant covariates were not considered clinically meaningful. Both weight-based (30 mg/kg Q3W) and two-tiered flat dosing (1800/2400 mg Q3W, 70 kg threshold) strategies are expected to provide similar exposures of zanidatamab.