A reduction in between subject variability is not mandatory for selecting a new covariate

Population pharmacokinetics of brexpiprazole in Japanese healthy subjects and patients with schizophrenia

Brexpiprazole, widely approved for the treatment of schizophrenia, is an atypical antipsychotic that modulates serotonin-dopamine activity. To better understand the pharmacokinetics (PK) of brexpiprazole in Japanese patients, a population PK model was constructed and used to estimate steady state PK profiles and parameters as well as dopamine D2/D3 receptor occupancy profiles after repeated oral administrations of brexpiprazole at 1 and 2 mg/day. Nonlinear mixed effects modelling was used to analyse data from a total of 398 healthy subjects and patients with schizophrenia who received brexpiprazole in three Japanese clinical trials. The PK of brexpiprazole were well described by a two-compartment disposition model with transit absorption compartments. Estimated glomerular filtration rate, age and cytochrome P450 2D6 phenotype were identified as significant covariates on CL/F only. The model predicted that, at a dose of 2 mg/day, trough plasma concentration (90 % prediction interval) of brexpiprazole is 77.1 (22.4-173) ng/mL and that dopamine D2/D3 receptor occupancy is >80 % over one day for most patients at steady state. This suggests the recommended maintenance dose of 2 mg/day of brexpiprazole leads to clinically useful dopamine D2/D3 receptor occupancy at steady state in Japanese patients.

Why we should sample sparsely and aim for a higher target: Lessons from model-based therapeutic drug monitoring of vancomycin in intensive care patients

Aims

To explore the optimal data sampling scheme and the pharmacokinetic (PK) target exposure on which dose computation is based in the model‐based therapeutic drug monitoring (TDM) practice of vancomycin in intensive care (ICU) patients.

Methods

We simulated concentration data for 1 day following four sampling schemes, C_min, C_max + C_min, C_max + C_{mid‐interval} + C_min, and rich sampling where a sample was drawn every hour within a dose interval. The datasets were used for Bayesian estimation to obtain PK parameters, which were used to compute the doses for the next day based on five PK target exposures: AUC₂₄ = 400, 500, and 600 mg·h/L and C_min = 15 and 20 mg/L. We then simulated data for the next day, adopting the computed doses, and repeated the above procedure for 7 days. Thereafter, we calculated the percentage error and the normalized root mean square error (NRMSE) of estimated against “true” PK parameters, and the percentage of optimal treatment (POT), defined as the percentage of patients who met 400 ≤ AUC₂₄ ≤ 600 mg·h/L and C_min ≤ 20 mg/L.

Results

PK parameters were unbiasedly estimated in all investigated scenarios and the 6‐day average NRMSE were 32.5%/38.5% (CL/V, where CL is clearance and V is volume of distribution) in the trough sampling scheme and 27.3%/26.5% (CL/V) in the rich sampling scheme. Regarding POT, the sampling scheme had marginal influence, while target exposure showed clear impacts that the maximum POT of 71.5% was reached when doses were computed based on AUC₂₄ = 500 mg·h/L.

Conclusions

For model‐based TDM of vancomycin in ICU patients, sampling more frequently than taking only trough samples adds no value and dosing based on AUC₂₄ = 500 mg·h/L lead to the best POT.