Semimechanistic Population PK/PD Modeling of Axatilimab in Healthy Participants and Patients With Solid Tumors or Chronic Graft-Versus-Host Disease.

Abstract

Axatilimab, a high-affinity humanized immunoglobulin G4 monoclonal antibody against colony-stimulating factor 1 receptor (CSF-1R), is approved for the treatment of chronic graft-versus-host disease (cGVHD), and under investigation for idiopathic pulmonary fibrosis and solid tumors. The population pharmacokinetics (PK) and pharmacodynamics (PD) of axatilimab were characterized in healthy participants and patients with solid tumors or cGVHD using data from four clinical studies with 325 participants, including 278 patients with cGVHD. The model structure reflected the mechanism of action of axatilimab: blocking CSF-1R signaling with axatilimab reduces the circulating levels of cells in the mononuclear phagocytic cell lineage (including nonclassical monocytic cells (NCMCs) and Kupffer cells), resulting in increases in circulating enzymes owing to reduced clearance by Kupffer cells. The structural model consisted of a two-compartment axatilimab PK model and turnover PD models for CSF-1, NCMCs, aspartate transaminase (AST), and creatine phosphokinase (CPK). Axatilimab PK and CSF-1 equations also included saturable clearance components to reflect the competitive binding of axatilimab and CSF-1 to CSF-1R. Covariate search was conducted with the conditional sampling use for the stepwise approach based on correlation tests (COSSAC) approach. Covariate effects on model parameters, steady-state axatilimab exposure, and NCMC concentrations were assessed. The final population PK/PD model was mathematically described with 6 ordinary differential equations and 39 model parameters. Among the 11 statistically significant covariates, one (body weight) and two (participant population type and baseline CPK) covariates affected axatilimab steady-state exposure and steady-state NCMC levels by > 20%, respectively. These results informed the axatilimab dosing strategy in patients with cGVHD.