Miyuki Kimura

Polymorphisms of OATP-C (SLC21A6) and OAT3 (SLC22A8) genes: Consequences for pravastatin pharmacokinetics

Objective: Our objective was to quantitate the contribution of the genetic polymorphisms of the genes for 2 human organic anion transporters—organic anion transporting polypeptide C (OATP‐C) and organic anion transporter 3 (OAT3)—to the pharmacokinetics of pravastatin.

Role of human MDR1 gene polymorphism in bioavailability and interaction of digoxin, a substrate of P-glycoprotein

Our objective was to quantitate the contribution of the genetic polymorphism of the human MDR1 gene to the bioavailability and interaction profiles of digoxin, a substrate of P‐glycoprotein.

SLCO1B1 (OATP1B1, an Uptake Transporter) and ABCG2 (BCRP, an Efflux Transporter) Variant Alleles and Pharmacokinetics of Pitavastatin in Healthy Volunteers

To investigate the contribution of genetic polymorphisms of SLCO1B1 and ABCG2 to the pharmacokinetics of a dual substrate, pitavastatin, 2 mg of pitavastatin was administered to 38 healthy volunteers and pharmacokinetic parameters were compared among the following groups: 421C/C*1b/*1b (group 1), 421C/C*1b/*15 (group 2), 421C/C*15/*15 and 421C/A*15/*15 (group 3), 421C/A*1b/*1b (group 4), 421A/A*1b/*1b (group 5), and 421C/A*1b/*15 (group 6). In SLCO1B1, pitavastatin area under plasma concentration–time curve from 0 to 24 h (AUC0–24) for groups 1, 2, and 3 was 81.1±18.1, 144±32, and 250±57 ng h/ml, respectively, with significant differences among all three groups. In contrast to SLCO1B1, AUC0–24 in groups 1, 4, and 5 was 81.1±18.1, 96.7±35.4, and 78.2±8.2 ng h/ml, respectively. Although the SLCO1B1 polymorphism was found to have a significant effect on the pharmacokinetics of pitavastatin, a nonsynonymous ABCG2 variant, 421C>A, did not appear to be associated with the altered pharmacokinetics of pitavastatin.

Pharmacogenetic Characterization of Sulfasalazine Disposition Based on NAT2 and ABCG2 (BCRP) Gene Polymorphisms in Humans

The role of breast cancer resistance protein (BCRP), an efflux ABC transporter, in the pharmacokinetics of substrate drugs in humans is unknown. We investigated the impact of genetic polymorphisms of ABCG2 (421C>A) and NAT2 on the pharmacokinetics of sulfasalazine (SASP), a dual substrate, in 37 healthy volunteers, taking 2,000 mg of conventional SASP tablets. In ABCG2, SASP AUC0–48 of C/C, C/A, and A/A subjects was 171 ± 85, 330 ± 194, and 592 ± 275 μg h/ml, respectively, with significant differences among groups. In contrast, AUC0–48 of sulfapyridine (SP) tended to be lower in subjects with the ABCG2‐A allele as homozygosity. In NAT2, AUCAcSP/AUCSP was significantly higher in rapid than in intermediate and slow acetylator (SA) genotypes. We successfully described the pharmacokinetics of SASP, SP, and N ‐acetylsulfapyridine (AcSP) simultaneously by nonlinear mixed‐effects modeling (NONMEM) analysis with regard to both gene polymorphisms. The data indicate that SASP is a candidate probe of BCRP, particularly in its role in intestinal absorption.

Pharmacokinetics of omeprazole (a substrate of CYP2C19) and comparison with two mutant alleles, CYP2C19m1 in exon 5 and CYP2C19m2 in exon 4, in Japanese subjects

The pharmacokinetic profile of omeprazole was examined in 27 healthy Japanese volunteers, and the results were analyzed in relation to genotype for the two mutations, CYP2C19m1 in exon 5 and CYP2C19m2 in exon 4, associated with the poor metabolizer phenotype. Of the 27 individuals analyzed, 10 were homozygous for the wild‐type (wt) allele in both exon 5 and exon 4 (wt/wt; 37.0%, pattern G1), five were heterozygous for the CYP2C19m1 (wt/m1; 18.5%, G2), five were heterozygous for the CYP2C19m2 (wt/m2; 18.5%, G3), two were heterozygous for the two defects (m1/m2; 7.4%, G4), and five were homozygous for the CYP2C19m1 (m1/m1; 18.5%, G5). The allele frequencies of the m1 and m2 mutation were 0.31 and 0.13, respectively. A correlation between the rate of metabolism of omeprazole and genotype was observed. The mean clearance values of omeprazole in patterns G1, G2, G3, G4, and G5 were 1369.0, 332.7, 359.0, 70.8, and 89.5 ml/hr/kg, respectively. The relative area under the serum concentration‐time curve (AUC) ratio of omeprazole to 5‐hydroxyomeprazole in patterns G1, G2, G3, G4, and G5 was 1:2.8:3.4:16:17.2. A similar relation was observed in the omeprazole/5‐hydroxyomeprazole serum concentration ratio, determined 3 hours after drug intake (1:3:4:18.8:20.3). There were significant (p < 0.05 to 0.01) differences in the disposition kinetics of omeprazole between the subjects with patterns G1, G2, and G3 and the subjects with patterns G4 and G5. The results indicate that the 5‐hydroxylation pathway of omeprazole is clearly impaired in subjects with m1/m2 and m1/m1.

Microdosing clinical study: Pharmacokinetic, pharmacogenomic (SLCO2B1), and interaction (grapefruit juice) profiles of celiprolol following the oral microdose and therapeutic dose

The authors evaluated the contribution of the SLCO2B1 polymorphism to the pharmacokinetics of celiprolol at a microdose (MD) and therapeutic dose (TD) and compared pharmacokinetic proportionality between the 2 dose forms in 30 SLCO2B1 genotype‐matched healthy volunteers. Three drugs (celiprolol, fexofenadine, and atenolol) were orally administered as a cassette dosing following the MD (totally 97.5 μg) and then a TD (100 mg) of celiprolol, with and without grapefruit juice. The mean AUC0–24 of celiprolol was lower in SLCO2B1*3/*3 individuals (775 ng·h/mL) than in *1/*3 (1097 ng·h/mL) and *1/*1 (1547 ng·h/mL) individuals following the TD, and this was confirmed in population pharmacokinetic analysis with statistical significances; however, SLCO2B1 genotype‐dependent differences disappeared following the MD. Dose‐normalized AUC of celiprolol at the MD was much lower than that at the TD, explained by the saturation of the efflux transporter. Thus, the effect of SLCO2B1 polymorphism on the AUC of celiprolol clearly observed only at the TD may be due to the saturation of the efflux transport systems.

Pharmacokinetic and pharmacogenomic profiles of telmisartan after the oral microdose and therapeutic dose.

Objectives In this study, we evaluated (a) the contribution of SLCO1B3 and UGT1A polymorphisms to the pharmacokinetics of telmisartan in two forms, a microdose (MD) and a therapeutic dose (TD); (b) linkage disequilibrium (LD) between UGT1A1 and UGT1A3; and (c) linearity in the pharmacokinetics of telmisartan between the two forms. Methods Telmisartan was orally administered at MD condition (100 &mgr;g), and then at TD condition (80 mg) to 33 healthy volunteers whose genotypes were prescreened by DMET Plus. Plasma concentrations of telmisartan and its glucuronide were measured by LC-MS/MS, and population pharmacokinetic analysis was performed. Results No obvious effect of SLCO1B3 polymorphisms (334T>G, 699G>A, and rs11045585) on the pharmacokinetics of telmisartan was observed. The strong LD between UGT1A1*6 and UGT1A3*4a, and between UGT1A1*28 and UGT1A3*2a were observed. After both MD and TD administration, the mean area under the curve0–24 (±standard deviation) of telmisartan was significantly lower and higher in individuals with the UGT1A3*2a (TD, 1701±970 ng hr/ml; MD, 978±537 pg hr/ml) and *4a variants (TD, 5340±1168; MD, 3145±1093), respectively, compared with those in individuals with UGT1A3*1/*1 (TD, 2969±1456; MD, 1669±726). These results were quantitatively confirmed by population pharmacokinetic analysis. Nonlinearity of the dose–exposure relationship was observed between the MD and TD. Conclusion The haplotypes of UGT1A3 significantly influenced pharmacokinetics of telmisartan and a strong LD between UGT1A1 genotype and UGT1A3 haplotype was observed. These findings are potentially of pharmacological and toxicological importance to the development and clinical use of drugs.

Pharmacokinetic interaction between pravastatin and olmesartan in relation to SLCO1B1 polymorphism.

AbstractThe impact of SLCO1B1 polymorphism on the pharmacokinetics of olmesartan and on the pharmacokinetic interaction between pravastatin and olmesartan was investigated. On day 1, ten healthy volunteers took an oral dose (10 mg) of pravastatin. After a 3-day washout period, each subject received olmesartan medoxomil (10 mg) for 3 days. On day 8, they received olmesartan medoxomil (10 mg) and pravastatin (10 mg) concurrently, and pharmacokinetic profiles were compared with those in each single-dose phase with regard to the SLCO1B1 genotypes (*1b/*1b, *1b/*15, and *15/*15). In the single-dose phase, the mean Cmax and AUC0-24 of olmesartan tended to be higher in *15/*15 subjects than in *1b/*1b subjects, while the mean CLt/F (±SD) in *15/*15 subjects was significantly lower than that in *1b/*1b subjects. No statistically significant differences were observed in any pharmacokinetic parameters between single-dose and co-administration phases for both pravastatin and RMS-416. These results suggest that OATP1B1 plays a role in the pharmacokinetics of olmesartan, and the co-administration of olmesartan does not affect the pharmacokinetics of pravastatin or its metabolite, RMS-416, although larger scale clinical studies are needed to confirm these observations due to the small sample size in the present study.

P-hydroxylation of phenobarbital: relationship to (S)-mephenytoin hydroxylation (CYP2C19) polymorphism.

The aim of the current study was to compare the pharmacokinetics of phenobarbital (PB) in extensive metabolizers (EMs) and poor metabolizers (PMs) of S-mephenytoin. Ten healthy volunteers (5 EMs and 5 PMs) were given 30 mg PB daily for 14 days. PB and p-hydroxyphenobarbital (p-OHPB) in serum and urine were measured by high-performance liquid chromatography (HPLC). Urinary excretion (12.5% versus 7.7%) and formation clearance (29.8 versus 21.1 mL/h) of p-OHPB, one of the main metabolites of PB, were significantly lower (p < .05) in PMs than in EMs. However, area under the serum concentration–time curve (153.3 in the EMs versus 122.9 &mgr;g · h/mL in the PMs) , total (210.8 versus 254.9 mL/h) and renal clearance (53.1 versus 66.1 mL/h) of PB were identical between the two groups. To compare the inducibility of CYP2C19, mephenytoin was also given prior to and on the last day of PB treatment. The urinary level of 4´-hydroxymephenytoin was analyzed by a validated gas chromatograpy/mass spectrometry (GC/MS) method. The mephenytoin hydroxylation index did not change in either EMs (1.42 versus 1.42) or PMs (341.4 versus 403.5), showing that CYP2C19 was not induced by treatment with PB. These results indicated that the p-hydroxylation pathway of PB co-segregates with the CYP2C19 metabolic polymorphism. However, the overall disposition kinetics of PB were not different between EMs and PMs, and therefore polymorphic CYP2C19 seems have no major clinical implications.

Interaction magnitude, pharmacokinetics and pharmacodynamics of ticlopidine in relation to CYP2C19 genotypic status

Objectives The aim of this study was to investigate the impact of CYP2C19 polymorphism on the extent of the interaction and on the pharmacokinetics and pharmacodynamics of ticlopidine. Methods Homozygous (hmEMs) and heterozygous extensive metabolizers (htEMs), and poor metabolizers (PMs, n=6 each) took an oral dose (20 mg) of omeprazole. After a 1-week washout period, each subject received ticlopidine (200 mg) for 8 days, and ticlopidine pharmacokinetics were studied on days 1 and 7. On day 8, omeprazole was given again and its kinetic disposition was compared with that in the first dose. ADP-induced platelet aggregation was measured as a pharmacodynamic index. Results In contrast to the PMs, whose mean kinetic parameters were not altered by the repeated dosings of ticlopidine, an eight- to 10-fold increase in the mean AUC ratio of omeprazole to 5-hydroxyomeprazole was observed in both the EM groups. No significant intergenotypic differences in the pharmacokinetic parameters of ticlopidine were observed, although the accumulation ratio tended to be greater in hmEMs than in PMs (2.4±0.2 versus 1.7±0.2). A significantly positive correlation (P=0.031) was observed between the individual percent inhibition of platelet aggregation and AUC0–24 of ticlopidine regardless of the CYP2C19 polymorphism. Conclusions Ticlopidine is a potent inhibitor for CYP2C19 and may be associated with the phenocopy when CYPC19 substrates are co-administered to EMs. Whether and to what extent CYP2C19 would be involved in the metabolism of ticlopidine remain unanswered from the present in-vivo study.