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Objective

The objectives of the study were to develop a population pharmacokinetic model for 11C-flumazenil at tracer concentrations, to assess the effects of patient-related covariates and to derive an optimal sampling protocol for clinical use.

Methods

A population pharmacokinetic model was developed using nonlinear mixed effects modelling (NONMEM) with data obtained from 51 patients with either depression or epilepsy. Each patient received ∼370 MBq (1–4 µg) of 11C-flumazenil. The effects of selected covariates (gender, weight, type of disease and age) were investigated. The model was validated using a bootstrap method. Finally, an optimal sampling design was established.

Results

The population pharmacokinetics of tracer quantities of 11C-flumazenil were best described by a two compartment model. Type of disease and weight were identified as significant covariates (P < 0.002). Mean population pharmacokinetic parameters (percent coefficient of variation) were: CL 1530 mL min−1 (6.6%), V1 24.8 × 103 mL (3.8%), V2 27.3 × 103 mL (5.4%), and Q 2510 mL min−1 (6.5%). CL was 20% lower in patients with epilepsy, and the influence of weight on V1 was 0.55% kg−1. For the prediction of the AUC, a combination of two time points at t = 30 and 60 min post injection was considered optimal (bias −0.7% (95% CI −2.2 to 0.8%), precision 5.7% (95% CI 4.5–6.9%)). The optimal sampling strategy was cross-validated (observed AUC = 296 MBql−1 min−1 (95% CI 102–490), predicted AUC = 288 MBql−1 min−1 (95% CI 70–506)).

Conclusions

The population pharmacokinetics of tracer quantities of 11C-flumazenil are well described by a two-compartment model. Inclusion of weight and type of disease as covariates significantly improved the model. Furthermore, an optimal sampling procedure may increase the feasibility and applicability of 11C-flumazenil PET.