Imatinib mesylate (IM) trough concentration varies among IM-treated chronic myeloid leukemia (CML) patients. Although IM pharmacokinetics is influenced by several enzymes and transporters, little is known about the role of pharmacogenetic variation in IM metabolism. In this study, associations between IM trough concentration, clinical response and 11 single-nucleotide polymorphisms in genes involved in IM pharmacokinetics (ABCB1, ABCC2, ABCG2 CYP3A5, SLC22A1 and SLCO1B3) were investigated among 67 Japanese chronic phase CML patients. IM trough concentration was significantly higher in patients with a major molecular response than in those without one (P¼0.010). No significant correlations between IM trough concentration and age, weight, body mass index or biochemical data were observed. However, the dose-adjusted IM trough concentration was significantly higher in patients with ABCG2 421A than in those with 421C/C (P=0.015). By multivariate regression analysis, only ABCG2 421A was independently predictive of a higher dose-adjusted IM trough concentration (P¼0.015). Moreover, previous studies have shown that the ABCG2 421C4A (p.Q141K) variant is prevalent among Japanese and Han Chinese individuals and less common among Africans and Caucasians. Together, these data indicate that plasma IM concentration monitoring and prospective ABCG2 421C4A genotyping may improve the efficacy of IM therapy, particularly among Asian CML patients.

MPA excretion into bile in patients with SLCO1B3 T334G GG (or G699A AA) was higher than in those with T334G TT (or G699A GG), probably resulting in a higher AUC(6-12) value of MPA. MPA uptake into hepatocytes and excretion into bile at first pass may be greater in SLCO1B3 T334G GG carriers than in TT carriers. In addition, the ABCC2 C-24T polymorphism also seems to be associated with enhanced enterohepatic circulation of MPA. The SLCO1B3 and ABCC2 transporters rather than uridine diphosphate-glucuronosyltransferase (UGT) may partly affect interindividual variety in plasma MPA concentration.

The CYP3A4*1/*1G polymorphism was associated with the pharmacokinetics of tacrolimus, however, its contribution to dose-adjusted pharmacokinetics was approximately twofold less than that of the CYP3A5*1/*3 polymorphism. Although its effect on CYP3A4 activity is not clear, CYP3A4*1/*1G may be a candidate for a polymorphism affecting the interindividual variability in tacrolimus pharmacokinetics among CYP3A5 expressers.

No abstract

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 (r = 0.877), and the AUC0-12 of tacrolimus calculated at the same time points predicted a good correlation with the actual AUC (r = 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, r = 0.799, P < 0.001 and AUC0-12 = 0.26.C0 + 2.06.C2 + 3.82.C4 + 20.38, r = 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.