Open AccessModel‐Based Optimal Design and Execution of the First‐Inpatient Trial of the Anti‐IL‐6, Olokizumab
Author(s) -
Kretsos K,
Jullion A,
Zamacona M,
Harari O,
Shaw S,
Boulanger B,
Oliver R
Publication year - 2014
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1038/psp.2014.17
Subject(s) - interim , interim analysis , computer science , sample size determination , optimal design , statistics , medicine , machine learning , mathematics , randomized controlled trial , archaeology , history
The first‐in‐patient study for olokizumab (OKZ) employed model‐based, optimal design and adaptive execution to define the concentration–C‐reactive protein (CRP) suppression response. Modeling and exploratory statistics activities involved: reverse engineering of first‐in‐class (tocilizumab) pharmacokinetic/pharmacodynamic (PK/PD) models, adaptation of models to OKZ with a priori knowledge and preclinical data translation, application of multidimensional Desirability Index for optimal study design, sample size reestimation based on new information, optimization of second study part via Bayesian analysis of interim data, and interim and final analysis for PK/PD objective attainment. Design work defined a dose window (0.1–3 mg/kg) for CRP suppression exploration and suggested 72 patients in five single‐dose levels would suffice. During execution, new information resulted in reestimating the study size to half. Halting the first part and conducting interim analysis for second part optimization followed. Second interim and final analyses confirmed attainment of study objective, illustrating efficiency and optimality of the study. CPT Pharmacometrics Syst. Pharmacol . (2014) 3, e119; doi: 10.1038/psp.2014.17 ; published online 18 June 2014