Exposure-response analysis using time-to-event data for bevacizumab biosimilar SB8 and the reference bevacizumab

Front Pharmacol. 2024 Jan 16:14:1288308. doi: 10.3389/fphar.2023.1288308. eCollection 2023.

Abstract

Purpose: This analysis aimed to characterize the exposure-response relationship of bevacizumab in non-small-cell lung cancer (NSCLC) and evaluate the efficacy of SB8, a bevacizumab biosimilar, and Avastin®, the reference bevacizumab sourced from the European Union (EU), based on the exposure reported in a comparative phase III efficacy and safety study (EudraCT, 2015-004026-34; NCT02754882). Materials and methods: The overall survival (OS) and progression-free survival (PFS) data from 224 patients with steady-state trough concentrations (Css,trough) were analyzed. A parametric time-to-event (TTE) model was developed using NONMEM®, and the effects of treatments (SB8 and bevacizumab-EU) and patient demographic and clinical covariates on OS and PFS were evaluated. Simulations of median OS and PFS by bevacizumab Css,trough were conducted, and concentrations required to achieve 50% and 90% of the maximum median TTE were computed. Results: A log-logistics model with Css,trough best described the OS and PFS data. Treatment was not a predictor of the hazard for OS or PFS. Simulations revealed steep exposure-response curves with a phase of rapid rise before saturating to a plateau. The median Css,trough values of SB8 and bevacizumab-EU reported from the clinical study were on the plateaus of the exposure-response curves. The concentrations required to achieve 50% and 90% of the maximum effect were 82.4 and 92.2 μg/mL, respectively, for OS and 79.7 and 89.1 μg/mL, respectively, for PFS. Conclusion: Simulations based on the constructed TTE models for OS and PFS have well described the exposure-response relationship of bevacizumab in advanced NSCLC. The analysis demonstrated comparable efficacy between SB8 and bevacizumab-EU in terms of OS and PFS based on their exposure levels.

Keywords: bevacizumab; biosimilar; exposure–response analysis; non-small-cell lung cancer; simulation; time-to-event modeling.

Grants and funding

The authors declare that no financial support was received for the research, authorship, and/or publication of this article.