Simulation-based evaluation of personalized dosing approaches for anti-FGFR/KLB bispecific antibody fazpilodemab

Abstract

Personalized dosing approaches play important roles in clinical practices to improve benefit: risk profiles. Whereas this is also important for drug development, especially in the context of drugs with narrow therapeutic windows, such approaches have not been fully evaluated during clinical development. Fazpilodemab (BFKB8488A) is an agonistic bispecific antibody which was being developed for the treatment of nonalcoholic steatohepatitis. The objective of this study was to characterize the exposure-response relationships of fazpilodemab with the purpose of guiding dose selection for a phase II study, as well as to evaluate various personalized dosing strategies to optimize the treatment benefit. Fazpilodemab exhibited clear exposure-response relationships for a pharmacodynamic (PD) biomarker and gastrointestinal adverse events (GIAEs), such as nausea and vomiting. Static exposure-response analysis, as well as longitudinal adverse event (AE) analysis using discrete-time Markov model, were performed to characterize the observations. Clinical trial simulations were performed based on the developed exposure-response models to evaluate probability of achieving target PD response and the frequency of GIAEs to inform phase II dose selection. Dynamic simulation of personalized dosing strategies demonstrated that the AE-based personalized dosing is the most effective approach for optimizing the benefit-risk profiles. The approach presented here can be a useful framework for quantifying the benefit of personalized dosing for drugs with narrow therapeutic windows.