A comprehensive evaluation of exposure-response relationships in clinical trials: application to support guselkumab dose selection for patients with psoriasis

摘要

Guselkumab, a human IgG1 monoclonal antibody that blocks interleukin-23, has been evaluated in one Phase 2 and two Phase 3 trials in patients with moderate-to-severe psoriasis, in which disease severity was assessed using Psoriasis Area and Severity Index (PASI) and Investigator's Global Assessment (IGA) scores. Through the application of landmark and longitudinal exposure-response (E-R) modeling analyses, we sought to predict the guselkumab dose-response (D-R) relationship using data from 1459 patients who participated in these trials. A recently developed novel latent-variable Type I Indirect Response joint model was applied to PASI75/90/100 and IGA response thresholds, with placebo effect empirically modeled. An effect of body weight on E-R, independent of pharmacokinetics, was identified. Thorough landmark analyses also were implemented using the same dataset. The E-R models were combined with a population pharmacokinetic model to generate D-R predictions. The relative merits of longitudinal and landmark analysis also are discussed. The results provide a comprehensive and robust evaluation of the D-R relationship.