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Aims: We compared the CYP3A4 metrics weight-corrected midazolam apparent oral clearance (MDZ Cl/F/W) and plasma 4β-hydroxycholesterol/cholesterol (4β-OHC/C) as they relate to tacrolimus (TAC) Cl/F/W in renal transplant recipients., Methods: For a cohort of 147 patients, 8 h area under the curve (AUC) values for TAC and oral MDZ were calculated besides measurement of 4β-OHC/C. A subgroup of 70 patients additionally underwent intravenous erythromycin breath test (EBT) and were administered the intravenous MDZ probe. All patients were genotyped for common polymorphisms in CYP3A4, CYP3A5 and P450 oxidoreductase, among others., Results: MDZ Cl/F/W, 4β-OHC/C/W, EBT and TAC Cl/F/W were all moderately correlated (r = 0.262-0.505). Neither MDZ Cl/F/W nor 4β-OHC/C/W explained variability in TAC Cl/F/W in CYP3A5 expressors (n = 29). For CYP3A5 non-expressors (n = 118), factors explaining variability in TAC Cl/F/W in a MDZ-based model were MDZ Cl/F/W (R 2  = 0.201), haematocrit (R 2  = 0.139), TAC formulation (R 2  = 0.107) and age (R 2  = 0.032; total R 2  = 0.479). In the 4β-OHC/C/W-based model, predictors were 4β-OHC/C/W (R 2  = 0.196), haematocrit (R 2  = 0.059) and age (R 2  = 0.057; total R 2  = 0.312). When genotype information was ignored, predictors of TAC Cl/F/W in the whole cohort were 4β-OHC/C/W (R 2  = 0.167), MDZ Cl/F/W (R 2  = 0.045); Tac QD formulation (R 2  = 0.036), and haematocrit (R 2  = 0.032; total R 2  = 0.315). 4β-OHC/C/W, but not MDZ Cl/F/W, was higher in CYP3A5 expressors because it was higher in CYP3A4*1b carriers, which were almost all CYP3A5 expressors., Conclusions: A MDZ-based model explained more variability in TAC clearance in CYP3A5 non-expressors. However, 4β-OHC/C/W was superior in a model in which no genotype information was available, likely because 4β-OHC/C/W was influenced by the CYP3A4*1b polymorphism., (© 2016 The British Pharmacological Society.)

What Is Already Known About This Subject: SLCO1B3 is an influx transporter located at the hepatocyte basolateral membrane and it is involved in the uptake of a broad range of drug substrates including docetaxel. The pharmacogenetics of SLCO1B3 is not well characterized and previous in vivo and in vitro studies reported conflicting results with regards to the functional effects of the limited number of SLCO1B3 polymorphisms that were studied. Docetaxel displays a wide interindividual variability in its pharmacokinetics and pharmacodynamics and an understanding of SLCO1B3 pharmacogenetics might provide clinical benefits in guiding docetaxel dosing., What This Study Adds: The SLCO1B3 gene was comprehensively screened in the local healthy Asian populations (n= 168). A strong linkage disequilibrium pattern was detected across a total of 88 polymorphisms and 15 haplotype-tag SNPs (htSNPs) were identified. These htSNPs were profiled in a cohort of Chinese nasopharyngeal cancer (NPC) patients (n= 50). Genotypic-phenotypic analysis showed that a haplotypic construct comprising of four variants [IVS4+76G>A, 699G>A(Met233Ile), IVS12-5676A>G, and *347_*348insA] was the critical determinant of docetaxel disposition. This study suggests that the comprehensive screening and haplotypic linkage analysis of SLCO1B3 can better elucidate its pharmacogenetic effects on interpatient variability of docetaxel and other putative drug substrates. Further studies are warranted in cancer patients belonging to other ethnic groups. AIMS To completely screen the SLCO1B3 gene in three distinct healthy Asian populations (Chinese, Malay and Indian, n= 168) and investigate the influence of haplotype-tag SNPs (htSNPs) on docetaxel disposition in 50 nasopharyngeal carcinoma patients., Methods: Genomic DNA of individuals was screened for SLCO1B3 polymorphisms by direct sequencing. htSNPs were derived based on the sequence clustering algorithm and profiled in the patients. Population based genetic association analysis was performed using Haplostats package implemented in R and PLINK., Results: A strong linkage disequilibrium pattern was detected across a total of 88 polymorphisms and 15-htSNPs were identified. The SLCO1B3 haplotypic region comprising seven htSNPs was found to be significantly associated with docetaxel clearance (P= 0.003). Conditional haplotype analyses revealed that the haplotypic constructs comprising the IVS4+76G>A, 699G>A(Met233Ile), IVS12-5676A>G, and *347_*348insA polymorphisms were critical determinants of variability in docetaxel disposition [clearance and area under the plasma concentration-time curve (AUC(0,∞)): r(2) = 29% and 22%, respectively]. Patients harbouring the GAG*347insA haplotype were significantly associated with a 30% decrease in clearance and a 40% increase in AUC(0,∞) of docetaxel compared with patients harbouring the reference haplotype, GGA*347wt (P= 0.025 and 0.018, respectively). In contrast, a 50% higher clearance was observed in patients carrying the GAG*347wt haplotype compared with those with the reference haplotype (P= 0.002). The functional SLCO1B3 haplotypic constructs included the widely studied Met233Ile variant and *347_*348insA located in the putative miR-890 binding site in the 3'-untranslated region which may influence the transport characteristics of SLCO1B3., Conclusions: This study highlights the importance of SLCO1B3 polymorphic variations in influencing docetaxel disposition in nasopharyngeal carcinoma patients., (© 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.)

What Is Already Known About This Subject: * Pharmacokinetic variability of voriconazole is largely caused by CYP3A4- and CYP2C19-mediated metabolism. * Oral bioavailability of voriconazole has been claimed to be almost 100%, thus facilitating a change from intravenous to oral application without dose adjustment., What This Study Adds: * For the first time voriconazole exposure after intravenous and oral administration in relation to CYP2C19 activity is reported. * In addition, the predominant metabolic pathway is the hydroxylation that seems to be influenced by the CYP2C19 genotype. * Enterohepatic circulation of both hydroxylated metabolites must be anticipated., Aims: The aim was to determine the pharmacokinetics of voriconazole after a single oral dose in comparison with intravenous (i.v.) administration in healthy individuals stratified according to the cytochrome P450 (CYP) 2C19 genotype. In addition, the possible metabolic pathways and their modulation according to CYP2C19 genotype were investigated after oral and i.v. administration of voriconazole., Methods: In a single-centre, open-label, two-period crossover study 20 participants received single doses of 400 mg voriconazole orally and 400 mg voriconazole intravenously in randomized order. Blood and urine samples were collected up to 96 h post dose and the voriconazole and three major metabolites were quantified by high-performance liquid chromatography coupled to mass spectroscopy., Results: Absolute oral bioavailability of voriconazole was 82.6% (74.1, 91.0). It ranged from 94.4% (78.8, 109.9) in CYP2C19 poor metabolizers to 75.2% (62.9, 87.4) in extensive metabolizers. In contrast to voriconazole and its N-oxide, the plasma concentrations of both hydroxylated metabolites showed a large second peak after 24 h. Independent of the route of administration, voriconazole partial metabolic hydroxylation after i.v. administration was eightfold higher compared with N-oxidation [48.8 ml min(-1) (30.5, 67.1) vs. 6.1 ml min(-1) (4.1, 8.0)]. The formation of the metabolites was related to CYP2C19 activity., Conclusions: Independent of the route of administration, voriconazole exposure was three times higher in CYP2C19 poor metabolizers compared with extensive metabolizers. Voriconazole has a high bioavailability with no large differences between the CYP2C19 genotypes. The hydroxylation pathway of voriconazole elimination exceeded the N-oxidation, both influenced by the CYP2C19 genotype.

Aims: This study reports the pharmacokinetics of nelfinavir, its active metabolite, M8, and active moiety (nelfinavir + M8) in volunteers genotyped for CYP2C19 as extensive metabolizer (*1*1; n = 38), heterozygous poor metabolizer (PM) (*1*2; n = 22) and homozygous PM (*2*2; n = 6)., Methods: Subjects received nelfinavir at normal dose (3.5 days of 1250 mg q12h) or high dose (1250 mg q12h for 3 days and single dose of 3125 mg on day 4). Steady-state plasma samples were analysed by high-performance liquid chromatography/ultraviolet assay to determine pharmacokinetics., Results: At steady state, the mean C(max) was 42% [95% confidence interval (CI) 19, 69] and 63% (95% CI 20, 122) higher, and mean AUC was 51% (95% CI 24, 83) and 85% (95% CI 32, 159) higher for *1*2 and *2*2 compared with *1*1 subjects, respectively. For M8, the mean C(max) and AUC were 35% (95% CI 6, 55) and 33% (95% CI -3, 56), respectively, lower for *1*2 compared with *1*1 subjects. M8 was not detectable in *2*2 subjects. The mean C(max) and AUC values for the active moiety were higher by 30-35% for the *1*2 and *2*2 compared with *1*1 subjects., Conclusions: Mutation in CYP2C19 increased the systemic exposure of nelfinavir and reduced the exposure of M8. No significant differences were noted among the heterozygous (*1*2) and homozygous (*2*2) PMs. These changes are not considered to be clinically relevant and hence the use of nelfinavir does not require prior assessment of CYP2C19 genotype.

Aims: The aims of this study were to develop a combined population pharmacokinetic model for both aripiprazole and its active metabolite, dehydroaripiprazole, in psychiatric patients and to identify to what extent the genetic polymorphisms of cytochrome P450 (CYP) enzymes contribute to the variability in pharmacokinetics (PK)., Methods: A population pharmacokinetic analysis was performed using NONMEM software based on 141 plasma concentrations at steady state from 80 patients receiving multiple oral doses of aripiprazole (10-30 mg day(-1))., Results: A one-compartment model with first-order kinetics for aripiprazole and dehydroaripiprazole each was developed to describe simultaneously the concentration data. The absorption rate constant was fixed to 1.06 h(-1). The typical value of apparent distribution volume of aripiprazole was estimated to be 192 l. Covariate analysis showed that CYP2D6 genetic polymorphisms significantly influenced the apparent clearance of aripiprazole (CL/F), reducing the interindividual variability on CL/F from 37.8% CV (coefficient of variation) to 30.5%. The CL/F in the CYP2D6 IMs was approximately 60% of that in CYP2D6 EMs having two functional alleles. Based on the CYP2D6 genotype, the metabolic ratios were calculated at 0.20-0.34. However, the plasma concentration : dose ratios of dehydroaripiprazole were not different across the CYP2D6 genotype., Conclusions: This population pharmacokinetic model provided an adequate fit to the data for both aripiprazole and dehydroaripiprazole in psychiatric patients. The usefulness of CYP genotyping as an aid to select the starting dose should be further investigated.

Aims: To investigate the population pharmacokinetics of 6-mercaptopurine (6-MP) active metabolites in paediatric patients with acute lymphoblastic leukaemia (ALL) and examine the effects of various genetic polymorphisms on the disposition of these metabolites., Methods: Data were collected prospectively from 19 paediatric patients with ALL (n = 75 samples, 150 concentrations) who received 6-MP maintenance chemotherapy (titrated to a target dose of 75 mg m(-2) day(-1)). All patients were genotyped for polymorphisms in three enzymes involved in 6-MP metabolism. Population pharmacokinetic analysis was performed with the nonlinear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance for the active metabolites., Results: The developed model revealed considerable interindividual variability (IIV) in the clearance of 6-MP active metabolites [6-thioguanine nucleotides (6-TGNs) and 6-methylmercaptopurine nucleotides (6-mMPNs)]. Body surface area explained a significant part of 6-TGNs clearance IIV when incorporated in the model (IIV reduced from 69.9 to 29.3%). The most influential covariate examined, however, was thiopurine methyltransferase (TPMT) genotype, which resulted in the greatest reduction in the model's objective function (P < 0.005) when incorporated as a covariate affecting the fractional metabolic transformation of 6-MP into 6-TGNs. The other genetic covariates tested were not statistically significant and therefore were not included in the final model., Conclusions: The developed pharmacokinetic model (if successful at external validation) would offer a more rational dosing approach for 6-MP than the traditional empirical method since it combines the current practice of using body surface area in 6-MP dosing with a pharmacogenetically guided dosing based on TPMT genotype.

Aims: To characterize pharmacokinetic (PK) variability of risperidone and 9-OH risperidone using sparse sampling and to evaluate the effect of covariates on PK parameters., Methods: PK analysis used plasma samples collected from the Clinical Antipsychotic Trials of Intervention Effectiveness. A nonlinear mixed-effects model was developed using NONMEM to describe simultaneously the risperidone and 9-OH risperidone concentration-time profile. Covariate effects on risperidone and 9-OH risperidone PK parameters were assessed, including age, weight, sex, smoking status, race and concomitant medications., Results: PK samples comprised 1236 risperidone and 1236 9-OH risperidone concentrations from 490 subjects that were available for analysis. Ages ranged from 18 to 93 years. Population PK submodels for both risperidone and 9-OH risperidone with first-order absorption were selected to describe the concentration-time profile of risperidone and 9-OH risperidone. A mixture model was incorporated with risperidone clearance (CL) separately estimated for three subpopulations [poor metabolizer (PM), extensive metabolizer (EM) and intermediate metabolizer (IM)]. Age significantly affected 9-OH risperidone clearance. Population parameter estimates for CL in PM, IM and EM were 12.9, 36 and 65.4 l h(-1) and parameter estimates for risperidone half-life in PM, IM and EM were 25, 8.5 and 4.7 h, respectively., Conclusions: A one-compartment mixture model with first-order absorption adequately described the risperidone and 9-OH risperidone concentrations. Age was identified as a significant covariate on 9-OH risperidone clearance in this study.