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Bottom‐up modeling and simulation of tacrolimus clearance: prospective investigation of blood cell distribution, sex and CYP3A5 expression as covariates and assessment of study power
Author(s) -
Ohtani Hisakazu,
Barter Zoe,
Minematsu Tsuyoshi,
Makuuchi Masatoshi,
Sawada Yasufumi,
RostamiHodjegan Amin
Publication year - 2011
Publication title -
biopharmaceutics and drug disposition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.419
H-Index - 58
eISSN - 1099-081X
pISSN - 0142-2782
DOI - 10.1002/bdd.777
Subject(s) - tacrolimus , population , covariate , pharmacokinetics , cyp3a5 , medicine , pharmacology , physiologically based pharmacokinetic modelling , transplantation , biology , statistics , genotype , mathematics , biochemistry , environmental health , gene
The objectives were to investigate the ability of population‐based in vitro–in vivo extrapolation (IVIVE) to reproduce the influence of haematocrit on the clearance of tacrolimus, observed previously, and to assess the power of clinical studies to detect the effects of covariates on the clearance of tacrolimus. A population‐based pharmacokinetic simulator (Simcyp) was used to simulate tacrolimus clearance from in vitro metabolism data and demographic characteristics of Japanese liver transplant patients (JLTs). The relationship between haematocrit and dose‐to‐concentration (D/C) ratio was validated using seven JLTs, whose highly variable haematocrit and D/C ratio were previously analysed. This validation was used as a surrogate for establishing ‘interindividual’ variability and to assess the power of clinical studies to discern the effect of haematocrit, sex and CYP3A5 genotype on tacrolimus clearance in a virtual JLT population. The relationship between haematocrit and D/C ratio was reproducible by Simcyp and corresponded well to those observed in seven JLTs. The number of JLTs required to detect the influence of CYP3A5 genotype and sex were estimated to be about 50 and > 600, respectively, which was consistent with the results of previous population pharmacokinetic studies for tacrolimus. In conclusion, population ‐ based IVIVE is considered to be a useful approach to assess the influence of covariates a priori before conducting clinical studies. This is also helpful with study design and assessment of the statistical power of clinical studies involving population‐based pharmacokinetics to detect the effects of covariates. Copyright © 2011 John Wiley & Sons, Ltd.