4.6 Article

Limited Sampling Strategy for Determination of Ibrutinib Plasma Exposure: Joint Analyses with Metabolite Data

Journal

PHARMACEUTICALS
Volume 14, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/ph14020162

Keywords

ibrutinib; metabolite; therapeutic drug monitoring; Bayesian analysis; pharmacokinetics

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The study found that a limited sampling strategy using the T0-1-2-4 design can accurately estimate ibrutinib exposure, with good accuracy even when removing the 1-hour or 2-hour sampling points. The correlation between actual AUC(IBRU) and C-min, C-ss was poor, and joint analysis of dihydrodiol-ibrutinib metabolite concentrations did not improve predictive performance. At least three samples within the pre-dose and 4-hour post-dose period are necessary for accurate estimation of ibrutinib exposure.
Therapeutic drug monitoring of ibrutinib is based on the area under the curve of concentration vs. time (AUC(IBRU)) instead of trough concentration (C-min,C-ss) because of a limited accumulation in plasma. Our objective was to identify a limited sampling strategy (LSS) to estimate AUC(IBRU) associated with Bayesian estimation. The actual AUC(IBRU) of 85 patients was determined by the Bayesian analysis of the full pharmacokinetic profile of ibrutinib concentrations (pre-dose T0 and 0.5, 1, 2, 4 and 6 h post-dose) and experimental AUC(IBRU) were derived considering combinations of one to four sampling times. The T0-1-2-4 design was the most accurate LSS (root-mean-square error RMSE = 11.0%), and three-point strategies removing the 1 h or 2 h points (RMSE = 22.7% and 14.5%, respectively) also showed good accuracy. The correlation between the actual AUC(IBRU) and C-min,C-ss was poor (r(2) = 0.25). The joint analysis of dihydrodiol-ibrutinib metabolite concentrations did not improve the predictive performance of AUC(IBRU). These results were confirmed in a prospective validation cohort (n = 27 patients). At least three samples, within the pre-dose and 4 h post-dose period, are necessary to estimate ibrutinib exposure accurately.

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