Takenori Niioka

Limited sampling strategy for simultaneous estimation of the area under the concentration-time curve of tacrolimus and mycophenolic acid in adult renal transplant recipients.

The aim of this study was to develop a limited sampling strategy to allow the simultaneous estimation of the area under the concentration-time curves (AUCs) of tacrolimus and mycophenolic acid (MPA), the active metabolite of the prodrug mycophenolate mofetil, using a small number of samples from patients undergoing renal transplantation. Fifty Japanese patients were enrolled. On day 28 after transplantation, samples were collected just before and 1, 2, 3, 4, 6, 9, and 12 hours after tacrolimus and mycophenolate mofetil administration at 9:00 am and 9:00 pm. The full pharmacokinetic profiles obtained from these timed concentration data were used to choose the best sampling times. Three error indices (percent mean error, percent mean absolute error, and percent relative mean square error) were used to evaluate the predictive bias, accuracy, and precision. The predicted AUC0-12 of MPA calculated at the three time points of C2h-C4h-C9h best approximated the actual AUC0-12 of MPA (r2 = 0.877), and the AUC0-12 of tacrolimus calculated at the same time points predicted a good correlation with the actual AUC (r2 = 0.928). When the three sampling times of trough level (C0h) and two other points within 4 hours after administration were used, the three points of C0h-C2h-C4h were the best points for estimation of the AUC0-12 tacrolimus and MPA (AUC0-12 = 7.04·C0 + 1.71·C2 + 3.23·C4 + 15.19, r2 = 0.799, P < 0.001 and AUC0-12 = 0.26·C0 + 2.06·C2 + 3.82·C4 + 20.38, r2 = 0.693, P < 0.001, respectively). The percent mean error, percent mean absolute error, and percent relative mean square error of the prediction formula using the three time points of C0h-C2h-C4h were -0.3%, 8.8%, and 13.5% for tacrolimus and 2.9%, 17.1%, and 21.5% for MPA, respectively. A limited sampling strategy using C2h-C4h-C9h provides the most reliable and accurate simultaneous estimation of the AUC0-12 of tacrolimus and MPA in patients undergoing renal transplantation. In addition, a limited sampling strategy using C0h-C2h-C4h is recommended for the simultaneous estimation of the AUC0-12 of tacrolimus and MPA when focused on samples collected within 4 hours after administration for clinical expediency.

Comparison of pharmacokinetics and pharmacogenetics of once- and twice-daily tacrolimus in the early stage after renal transplantation.

Background This study investigated pharmacokinetic and pharmacogenetic differences between a modified-release once-daily formulation of tacrolimus (Tac-QD) and the original formulation requiring twice-daily intake (Tac-BID) in de novo renal transplant recipients. Methods Forty-seven and 25 patients who received Tac-BID and Tac-QD, respectively, were enrolled. The pharmacokinetics and CYP3A5 6986A>G and ABCB1 3435C>T pharmacogenetics of each formulation were analyzed on day 28 posttransplantation. Results The dose-adjusted trough level (C0) and area under the concentration-time curve (AUC0-24) of tacrolimus were approximately 25% lower for Tac-QD than Tac-BID. However, there was a good correlation between the AUC0-24 and C0 in the Tac-BID and Tac-QD groups (r2=0.575, P<0.001; and r2=0.638, P<0.001, respectively) and a similar coefficient in each regression equation. The dose-adjusted AUC0-24 was approximately 25% lower in carriers of the CYP3A*1 allele (CYP3A5 expressers), but not individuals with the CYP3A*3/*3 genotype (nonexpressers), for TAC-QD than Tac-BID. In the Tac-QD group, the interpatient variability for dose-adjusted parameters was small, and the interquatile ranges of dose-adjusted parameters differed between CYP3A5 expressers and nonexpressers and did not overlap. The ABCB1 polymorphism was not associated with any pharmacokinetic parameters of Tac-QD. Conclusions C0-guided monitoring may lead to similar AUC0-24 values for both formulations. However, to maintain the same AUC0-24 value, a higher dose of Tac-QD than Tac-BID may be needed, especially for CYP3A5 expressers, in the early stage posttransplantation. The narrow interindividual variability of Tac-QD pharmacokinetics and its difference between CYP3A5 expressers and nonexpressers might contribute to a dosing strategy based on CYP3A5 genotype.

Simultaneous determination of warfarin enantiomers and its metabolite in human plasma by column-switching high-performance liquid chromatography with chiral separation.

A simple and sensitive column-switching high-performance liquid chromatographic method for the simultaneous determination of warfarin enantiomers and their metabolites, 7-hydroxywarfarin enantiomers, in human plasma is described. Warfarin enantiomers, 7-hydroxywarfarin enantiomers, and an internal standard, diclofenac sodium, were extracted from 1 mL of a plasma sample using diethyl ether-chloroform (80:20, v/v). The extract was injected onto column I (TSK precolumn BSA-C8, 5 μm, 10 mm × 4.6 mm inside diameter) for cleanup and column II (Chiralcel OD-RH analytical column, 150 mm × 4.6 mm inside diameter) coupled with a guard column (Chiralcel OD-RH guard column, 10 mm ×4.6 mm inside diameter) for separation. The mobile phase consisted of phosphate buffer-acetonitrile (84:16 v/v, pH 2.0) for clean-up and phosphate buffer-acetonitrile (45:55 v/v, pH 2.0) for separation. The peaks were monitored with an ultraviolet detector set at a wavelength of 312 nm, and total time for chromatographic separation was approximately 25 minutes. The validated concentration ranges of this method were 3 to 1000 ng/mL for (R)- and (S)-warfarin and 3 to 200 ng/mL for (R)- and (S)-7-hydroxywarfarin. Intra- and interday coefficients of variation were less than 4.4% and 4.9% for (R)-warfarin and 4.8% and 4.0% for (S)-warfarin, and 5.1% and 4.2% for (R)-7-hydroxywarfarin and 5.8% and 5.0% for (S)-7-hydroxywarfarin at the different concentrations. The limit of quantification was 3 ng/mL for both warfarin and 7-hydroxywarfarin enantiomers. This method was suitable for therapeutic drug monitoring of warfarin enantiomers and was applied in a pharmacokinetic study requiring the simultaneous determination of warfarin enantiomers and its metabolite, 7-hydroxywarfarin enantiomers, in human volunteers.

A multicenter clinical study evaluating the confirmed complete molecular response rate in imatinib-treated patients with chronic phase chronic myeloid leukemia by using the international scale of real-time quantitative polymerase chain reaction

Achievement of complete molecular response in patients with chronic phase chronic myeloid leukemia has been recognized as an important milestone in therapy cessation and treatment-free remission; the identification of predictors of complete molecular response in these patients is, therefore, important. This study evaluated complete molecular response rates in imatinib-treated chronic phase chronic myeloid leukemia patients with major molecular response by using the international standardization for quantitative polymerase chain reaction analysis of the breakpoint cluster region-Abelson1 gene. The correlation of complete molecular response with various clinical, pharmacokinetic, and immunological parameters was determined. Complete molecular response was observed in 75/152 patients (49.3%). In the univariate analysis, Sokal score, median time to major molecular response, ABCG2 421C>A, and regulatory T cells were significantly lower in chronic phase chronic myeloid leukemia patients with complete molecular response than in those without complete molecular response. In the multivariate analysis, duration of imatinib treatment (odds ratio: 1.0287, P=0.0003), time to major molecular response from imatinib therapy (odds ratio: 0.9652, P=0.0020), and ABCG2 421C/C genotype (odds ratio: 0.3953, P=0.0284) were independent predictors of complete molecular response. In contrast, number of natural killer cells, BIM deletion polymorphisms, and plasma trough imatinib concentration were not significantly associated with achieving a complete molecular response. Several predictive markers for achieving complete molecular response were identified in this study. According to our findings, some chronic myeloid leukemia patients treated with imatinib may benefit from a switch to second-generation tyrosine kinase inhibitors (ClinicalTrials.gov, UMIN000004935).

Effect of itraconazole on pharmacokinetics of paroxetine: the role of gut transporters.

A recent in vitro study has shown that paroxetine is a substrate of P-glycoprotein. However, there was no in vivo information indicating the involvement of P-glycoprotein on the pharmacokinetics of paroxetine. The aim of this study was to examine the effects of itraconazole, a P-glycoprotein inhibitor, on the pharmacokinetics of paroxetine. Two 6 day courses of either 200 mg itraconazole daily or placebo with at least a 4 week washout period were conducted. Thirteen volunteers took a single oral 20 mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 hours after the dosing. Compared with placebo, itraconazole treatment significantly increased the peak plasma concentration (Cmax) of paroxetine by 1.3 fold (6.7 ± 2.5 versus 9.0 ± 3.3 ng/mL, P < 0.05) and the area under the plasma concentration-time curve from zero to 48 hours [AUC (0-48)] of paroxetine by 1.5 fold (137 ± 73 versus 199 ± 91 ng*h/mL, P < 0.01). Although elimination half-life differed significantly (16.1 ± 3.4 versus 18.8 ± 5.9 hours, P < 0.05), the alteration was small (1.1 fold). The present study demonstrated that the bioavailability of paroxetine was increased by itraconazole, suggesting a possible involvement of P-glycoprotein in the pharmacokinetics of paroxetine.

Early Phase Limited Sampling Strategy Characterizing Tacrolimus and Mycophenolic Acid Pharmacokinetics Adapted to the Maintenance Phase of Renal Transplant Patients

The aim of this study was to examine whether a limited sampling strategy (LSS) to allow the simultaneous estimation of the area under the concentration-time curves (AUCs) of tacrolimus and mycophenolic acid (MPA) calculated in the early stage after renal transplantation could be applied to maintenance phase pharmacokinetics. Seventy Japanese patients were enrolled. One year after transplantation, samples were collected just before and 1, 2, 3, 4, 6, 9, and 12 hours after tacrolimus and mycophenolate mofetil administration at 9:00 am and at 9:00 pm. The prediction formulas on day 28 (tacrolimus AUC0-12 = 7.04·C0h + 1.71·C2h + 3.23·C4h + 15.19 and 2.25·C2h + 1.92·C4h + 7.27·C9h + 6.61, and MPA AUC0-12 = 0.26·C0h + 2.06·C2h + 3.82·C4h + 20.38 and 1.77·C2h + 2.34·C4h + 4.76·C9h + 15.94) were applied to pharmacokinetic data obtained at 1 year. Three error indices [percent mean prediction error (ME), % mean absolute error, and percent root mean squared prediction error (RMSE)] were used to evaluate the predictive bias, accuracy, and precision. The predicted AUC0-12 of tacrolimus and MPA at 3 time points, C2h-C4h-C9h, showed higher correlation with the measured AUC0-12 of tacrolimus and MPA (r2 = 0.817 and 0.789, respectively) in comparison with those at C0h-C2h-C4h. The values for the prediction formulas for tacrolimus AUC at 1 year using the C2h-C4h-C9h combination yielded less than 5% for %ME and 15% for %RMSE. The %ME and %RMSE values of the prediction formulas for tacrolimus AUC using the C0h-C2h-C4h combination were 6.3% and 15.9%, respectively. The %ME and %RMSE values of the prediction formulas for MPA AUC at 1 year using the C0h-C2h-C4h combination were 5.9% and 25.8%, respectively, and those for the C2h-C4h-C9h combination were 4.9% and 21.2%, respectively. AUC6-12/AUC0-12 of MPA 1 year after transplantation was significantly lower than 28 days after transplantation. An LSS using C2h-C4h-C9h seems to be applicable for predicting the AUC of tacrolimus and MPA at either posttransplantation stage. The enterohepatic circulation of MPA was significantly reduced 1 year after transplantation. Therefore, 1 year after transplantation, the estimation of the AUC0-12 of MPA for the C0h-C2h-C4h equations was imprecise. It is important that the LSS includes C9h because it contains information on the secondary plasma peak of MPA.

Different effects of the selective serotonin reuptake inhibitors fluvoxamine, paroxetine, and sertraline on the pharmacokinetics of fexofenadine in healthy volunteers.

Abstract Although the interaction between selective serotonin reuptake inhibitors (SSRIs) and other drugs is important in the treatment of depression, there have been few studies of SSRIs concerning transporter-mediated interactions in humans. The objective of this study was to evaluate the in vivo effects of commonly used SSRIs on the pharmacokinetics of fexofenadine, a P-glycoprotein substrate. Twelve healthy volunteers (3 females and 9 males) were enrolled in this study. Each subject received a 60-mg dose of fexofenadine orally at baseline. Afterward, they were randomly assigned to receive 3 treatments with a 60-mg dose of fexofenadine after a 7-day treatment with fluvoxamine (50 mg/d), paroxetine (20 mg/d), or sertraline (50 mg/d), with 2-week intervals between the agents. Fluvoxamine pretreatment significantly increased the maximum plasma concentration, the area under the concentration time curves, and the 24-hour urinary fexofenadine excretion by 66% (P = 0.004), 78% (P = 0.029), and 78% (P < 0.001), respectively, without prolonging its elimination half-life. Paroxetine extended the elimination half-life of fexofenadine by 45% (P = 0.042), and it increased the 24-hour urinary fexofenadine excretion by 55% (P = 0.002). Sertraline did not alter any of the pharmacokinetic parameters of fexofenadine. This is the first report of the different effects of 3 commonly used SSRIs on fexofenadine pharmacokinetics in humans. Our 7-day, repeated-dose clinical study in healthy volunteers indicates that fluvoxamine and paroxetine, but not sertraline, may impact the patient exposure to fexofenadine, which is likely the result of P-glycoprotein inhibition in the small intestine and/or the liver.

Influence of NAT2 Polymorphisms on Sulfamethoxazole Pharmacokinetics in Renal Transplant Recipients

ABSTRACT The sulfamethoxazole (SMX)-trimethoprim drug combination is routinely used as prophylaxis against Pneumocystis pneumonia during the first 3 to 6 months after renal transplantation. The objective of this study was to examine the impact of N-acetyltransferase 2 (NAT2) and CYP2C9 polymorphisms on the pharmacokinetics of SMX in 118 renal transplant recipients. Starting on day 14 after renal transplantation, patients were administered 400 mg/day-80 mg/day of SMX-trimethoprim orally once daily. On day 14 after the beginning of SMX therapy, plasma SMX concentrations were determined by a high-performance liquid chromatography method. The SMX area under the concentration-time curve from 0 to 24 h (AUC0-24) for 15 recipients with the NAT2 slow acetylator genotype (NAT2*5/*6, -*6/*6, -*6/*7, and -*7/*7) was significantly greater than that for 56 recipients with the NAT2 rapid acetylator genotype (homozygous for NAT2*4) (766.4 ± 432.3 versus 537.2 ± 257.5 μg-h/ml, respectively; P = 0.0430), whereas there were no significant differences in the SMX AUC0-24 between the CYP2C9*1/*1 and -*1/*3 groups. In a multiple regression analysis, the SMX AUC0-24 was associated with NAT2 slow acetylator polymorphisms (P = 0.0095) and with creatinine clearance (P = 0.0499). Hepatic dysfunction in NAT2 slow acetylator recipient patients during the 6-month period after SMX administration was not observed. SMX plasma concentrations were affected by NAT2 polymorphisms and renal dysfunction. Although standard SMX administration to patients with NAT2 slow acetylator polymorphisms should be accompanied by monitoring for side effects and drug interaction effects from the inhibition of CYP2C9, SMX administration at a low dose (400 mg) as prophylaxis may not provide drug concentrations that reach the level necessary for the expression of side effects. Further studies with a larger sample size should be able to clarify the relationship between SMX plasma concentration and side effects.

Influence of UGT1A1 *6, *27, and *28 Polymorphisms on Nilotinib-induced Hyperbilirubinemia in Japanese Patients with Chronic Myeloid Leukemia

Nilotinib potently inhibits human uridine diphosphate-glucuronosyltransferase (UGT1A1) activity, causing hyperbilirubinemia. We investigated the influence of UGT1A1 polymorphisms and nilotinib plasma trough concentrations (C0) on nilotinib-induced hyperbilirubinemia in 34 Japanese patients with chronic myeloid leukemia (CML). The proportion of patients with hyperbilirubinemia was significantly higher among patients with the UGT1A1*6/*6 and *6/*28 genotypes (poor metabolizers) than among those with other genotypes (p = 0.004). The median time to elevation of bilirubin levels in UGT1A1 poor metabolizers was 2.0 weeks (hazard ratio, 6.11). The median time to reduction in nilotinib dose in UGT1A1 poor metabolizers was 4.0 weeks (hazard ratio, 7.52; p = 0.002). Consequently, in the maintenance phase 3 months following the initiation of nilotinib therapy, the median daily dose and C0 of nilotinib were 350 mg/day and 372 ng/mL, respectively, in UGT1A1 poor metabolizers, and 600 mg/day and 804 ng/mL, respectively, in the other patients. Patients at increased hyperbilirubinemia risk could be identified by prospective UGT1A1 genotyping prior to nilotinib therapy. To avoid an interruption of CML treatment due to nilotinib-induced hyperbilirubinemia, it may be beneficial to reduce the initial nilotinib dose to 300-400 mg/day for UGT1A1 poor metabolizers.

Pharmacokinetic and CYP3A5 pharmacogenetic differences between once- and twice-daily tacrolimus from the first dosing day to 1 year after renal transplantation

UNLABELLED Aim & patients & methods: This study investigated 24-h pharmacokinetic and CYP3A5 pharmacogenetic differences between once-daily tacrolimus (Tac-q.d.) versus twice-daily tacrolimus (Tac-b.i.d.) pretransplantation and at 1 month and 1 year post-transplantaion. RESULTS The dose-adjusted trough level (Cmin) and area under the blood concentration-time curve from 0 to 24 h (AUC₀₋₂₄) increased twofold within 1 year post-transplantation with both formulations and the two genotypes. Good correlations were observed between the AUC₀₋₂₄ and Cmin for both formulations. However, the dose-adjusted Cmin, but not dose-adjusted AUC₀₋₂₄, was approximately 30% lower for Tac-q.d. than for Tac-b.i.d. Although the dose-adjusted Cmin was lower for Tac-q.d. than for Tac-b.i.d. in both genotypes, the dose-adjusted AUC₀₋₂₄ was approximately 25% lower for Tac-q.d. than for Tac-b.i.d. in CYP3A5 expressers, but not in nonexpressers during the study period. CONCLUSION These results suggested that the approximately 30% lower Cmin for Tac-q.d. than for Tac-b.i.d. may have achieved the same AUC₀₋₂₄ with both formulations and may be associated with CYP3A5 pharmacogenomic differences, especially in CYP3A5 expressers, between Tac-b.i.d. and Tac-q.d.