| Literature DB >> 29549540 |
Chuanpu Hu1, Zhenling Yao2, Yang Chen2, Bruce Randazzo3, Liping Zhang2, Zhenhua Xu2, Amarnath Sharma2, Honghui Zhou2.
Abstract
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.Entities:
Keywords: Clinical drug development; Exposure–response modeling; Joint modeling; Latent variable IDR modeling; NONMEM; Ordered categorical endpoints
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Year: 2018 PMID: 29549540 DOI: 10.1007/s10928-018-9581-1
Source DB: PubMed Journal: J Pharmacokinet Pharmacodyn ISSN: 1567-567X Impact factor: 2.745