Systemic pharmacokinetics of indacaterol, an inhaled once-daily long-acting beta2-agonist, in different ethnic populations.

RATIONALE: To assess ethnic sensitivity of indacaterol systemic pharmacokinetics in Japanese vs. non-Japanese patients. METHODS: Analyses were in three parts: data from a single "all Asian" clinical study; and two on pooled data - one using a linear mixed effects (LME) model and the other a non-linear mixed effects (NLME) model. The NLME model analyzed pharmacokinetic data from nine indacaterol studies; the LME model analyzed peak (C(max)) and trough (C(min)) serum concentration using data from four of these studies. RESULTS: In the all-Asian study, indacaterol serum concentration-time pharmacokinetic profiles in Japanese patients (n = 102) were similar to those in the overall population (n = 229). In the LME model, C(max) (4,392 observations, 1,845 patients) and C(min) (4,664 observations, 1,796 patients) for Japanese patients (n = 94) were on average 25% and 18% higher, respectively, than non-Japanese patients. However, after adjusting for study differences, this apparent ethnicity effect was not significant (p = 0.25 and 0.39, respectively). In the NLME model (25,540 observations, 2,857 patients), there was no statistically significant effect of Japanese (n = 230) ethnicity on indacaterol serum pharmacokinetics. CONCLUSION: No ethnicity effect was observed on indacaterol systemic pharmacokinetic profile for Japanese patients when compared with the overall Asian patient population or with the Caucasian patient population.

The population pharmacokinetics of R- and S-warfarin: effect of genetic and clinical factors.

BACKGROUND: Warfarin is a drug with a narrow therapeutic index and large interindividual variability in daily dosing requirements. Patients commencing warfarin treatment are at risk of bleeding due to excessive anticoagulation caused by overdosing. The interindividual variability in dose requirements is influenced by a number of factors, including polymorphisms in genes mediating warfarin pharmacology, co-medication, age, sex, body size and diet. AIMS: To develop population pharmacokinetic models of both R- and S-warfarin using clinical and genetic factors and to identify the covariates which influence the interindividual variability in the pharmacokinetic parameters of clearance and volume of distribution in patients on long-term warfarin therapy. METHODS: Patients commencing warfarin therapy were followed up for 26 weeks. Plasma warfarin enantiomer concentrations were determined in 306 patients for S-warfarin and in 309 patients for R-warfarin at 1, 8 and 26 weeks. Patients were also genotyped for CYP2C9 variants (CYP2C9*1,*2 and *3), two single-nucleotide polymorphisms (SNPs) in CYP1A2, one SNP in CYP3A4 and six SNPs in CYP2C19. A base pharmacokinetic model was developed using NONMEM software to determine the warfarin clearance and volume of distribution. The model was extended to include covariates that influenced the between-subject variability. RESULTS: Bodyweight, age, sex and CYP2C9 genotype significantly influenced S-warfarin clearance. The S-warfarin clearance was estimated to be 0.144 l h⁻¹ (95% confidence interval 0.131, 0.157) in a 70 kg woman aged 69.8 years with the wild-type CYP2C9 genotype, and the volume of distribution was 16.6 l (95% confidence interval 13.5, 19.7). Bodyweight and age, along with the SNPs rs3814637 (in CYP2C19) and rs2242480 (in CYP3A4), significantly influenced R-warfarin clearance. The R-warfarin clearance was estimated to be 0.125 l h⁻¹ (95% confidence interval 0.115, 0.135) in a 70 kg individual aged 69.8 years with the wild-type CYP2C19 and CYP3A4 genotypes, and the volume of distribution was 10.9 l (95% confidence interval 8.63, 13.2). CONCLUSIONS: Our analysis, based on exposure rather than dose, provides quantitative estimates of the clinical and genetic factors impacting on the clearance of both the S- and R-enantiomers of warfarin, which can be used in developing improved dosing algorithms.

Population pharmacokinetics and optimal design of paediatric studies for famciclovir.

AIMS: To develop a population pharmacokinetic model for penciclovir (famciclovir is a prodrug of penciclovir) in adults and children and suggest an appropriate dose for children. Furthermore, to develop a limited sampling design based on sampling windows for three different paediatric age groups (1-2, 2-5 and 5-12 years) using an adequate number of subjects for future pharmacokinetic studies. METHODS: Penciclovir plasma data from six different adult and paediatric studies were supplied by Novartis. Population pharmacokinetic modelling was undertaken in NONMEM version VI. Simulations in MATLAB were used to select an oral paediatric dose that gives similar exposure to 500 mg in adults. Optimal sampling times and sampling windows were obtained in MATLAB and simulations in NONMEM were used to select adequate sample sizes for three paediatric age groups. RESULTS: A two-compartment, first-order absorption model with an absorption lag time, allometric weight models on V(1), V(2) and Q, and an allometric weight model, age and creatinine clearance as covariates on CL adequately describe the pharmacokinetics of penciclovir in adults and children. Estimated CL (l h(-1) 70 kg(-1)) and V(ss) (l.70 kg(-1)) were 31.2 and 83.1, respectively. An oral dose of 10 mg kg(-1) body weight in children was predicted to give similar exposure as 500 mg in adults. A single sampling windows design (0.25-0.4, 0.5-1, 1.25-1.75, 2.75-3.5 and 7.25-8 h) for five samples per subject and 10 subjects in each of the paediatric age groups is recommended for future studies. CONCLUSIONS: A population pharmacokinetic model of penciclovir in adults and children has been developed. A prospective study design, including dose adjustment, cohort size and blood sampling design has been recommended.

Pharmacokinetics of a single bolus of propofol in chinese children of different ages.

BACKGROUND: There is no information about the pharmacokinetic profile of propofol in Chinese children younger than 3 yr. This study was designed to determine a complete pharmacokinetic profile of a single dose of propofol in Chinese children of different ages. METHODS: Arterial blood samples were obtained from 35 children with an American Society of Anesthesiologist physical status of I or II at 2, 4, 6, 8, 10, 20, 30, 45, 60, 90, 120, and 180 min after a single bolus intravenous injection of propofol (3 mg/kg). The plasma concentrations of propofol were measured using high-performance liquid chromatography with an ultraviolet detector. A population model was used to estimate the pharmacokinetics of propofol. RESULTS: A three-compartment pharmacokinetic model best described the pharmacokinetics of propofol. Clearance was 0.185 l/min, the volume of distribution of the central compartment was 7.41 l, the peripheral volumes of distribution were 54.6 and 7.2 l, and the intercompartmental clearances were 0.614 and 0.692 l/min for a child of the average weight of 13.7 kg. The half-lives were 2.67, 14.89, and 310.60 min. Covariate models were applied, and weight was found to be significant covariate for the clearance and volume of distribution parameters. No significant age effect could be demonstrated on clearance or volume of distribution parameters after weight was taken into account. CONCLUSIONS: This study supports the case that the pharmacokinetic properties of propofol do not differ substantially across Chinese children of different ages after weight has been accounted for.

Quantitative justification for target concentration intervention--parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides.

AIMS: [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. METHODS: Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (> or =20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. RESULTS: A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V1), 19.5 l 70 kg(-1); volume of peripheral compartment (V2) 11.2 l 70 kg(-1). CONCLUSIONS: Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.