The BCR-ABL T315I kinase domain mutation is insensitive to dasatinib therapy for Philadelphia-positive acute lymphoid leukemia (Ph + ALL) patients. Resistant T315I clone may be present prior to initiating dasatinib, which could expand under selective pressures during treatment. However, it is also possible that Ph + ALL patients newly acquire the T315I mutation during dasatinib therapy. Despite the potent inhibition of BCR-ABL kinase by dasatinib, little is known about the relationship between dasatinib pharmacokinetics and the emergence of kinase domain mutations in vivo.

To investigate the exposure-toxicity relationship of bosutinib and to identify the target trough plasma concentration (C0). The toxicity and C0 of bosutinib in Japanese chronic myeloid leukemia (CML) patients were monitored every 2 weeks for the first 3 months of treatment, and subsequently once a month during the 6 months after beginning 500 mg/day of standard dose (SD group, n = 10) or beginning 100 mg/day and increased by 100 mg every 2 weeks of dose escalation (DE group, n = 15). Nine of 10 patients (90%) in the SD group were not able to continue bosutinib therapy without interruption due to adverse events, compared to 2 patients (13.5%) in the DE group. The total duration of treatment interruption was 35 and 14 days in the SD and DE groups, respectively. The median time until liver dysfunction or diarrhea was day 28 and day 1 in the SD group, and day 53.5 and day 19 in the DE group, respectively. The cumulative dose of bosutinib was comparable between the SD and DE groups (51,700 vs. 53,550 mg, respectively). At 6 months, the median C0 was 63.7 ng/mL and 63.0 ng/mL in the SD and DE groups, respectively. Liver dysfunction (all grades) and diarrhea (> grade 2) were prevalent in quartile 4 of C0 (> 91.0 ng/mL), as calculated by the total C0 distribution. The DE regimen was better suited to avoid treatment interruption. The daily dose of bosutinib might be adjusted based on target C0 to avoid adverse events by therapeutic drug monitoring in general practice.

Nilotinib is a second-generation tyrosine kinase inhibitor that exhibits significant efficacy as first- or second-line treatment in patients with chronic myeloid leukemia (CML). We conducted a multicenter Phase II Clinical Trial to evaluate the safety and efficacy of nilotinib among Japanese patients with imatinib-resistant or -intolerant CML-chronic phase (CP) or accelerated phase (AP). We analyzed 49 patients (33 imatinib-resistant and 16 imatinib-intolerant) treated with nilotinib 400 mg twice daily. The major molecular response (MMR) rate was 47.8% at 12 months among 35 patients who did not demonstrate an MMR at study entry. Somatic BCR-ABL1 mutations (Y253H, I418V, and exon 8/9 35-bp insertion [35INS]) were detected in 3 patients at 12 months or upon discontinuation of nilotinib. Although 75.5% of patients were still being treated at 12 months, nilotinib treatment was discontinued because of progressing disease in 1 patient, insufficient effect in 2, and adverse events in 9. There was no statistically significant correlation between MMR and trough concentrations of nilotinib. Similarly, no correlation was observed between trough concentrations and adverse events, except for pruritus and hypokalemia. Hyperbilirubinemia was frequently observed (all grades, 51.0%; grades 2–4, 29%; grades 3–4, 4.1%). Hyperbilirubinemia higher than grade 2 was significantly associated with the uridine diphosphate glucuronosyltransferase (UGT)1A9 I399C/C genotype (P = 0.0086; Odds Ratio, 21.2; 95% Confidence Interval 2.2–208.0). Nilotinib was efficacious and well tolerated by patients with imatinib-resistant or -intolerant CML-CP/AP. Hyperbilirubinemia may be predicted before nilotinib treatment, and may be controlled by reducing the daily dose of nilotinib in patients with UGT1A9 polymorphisms. clinicaltrials.gov: UMIN000002201

While CYP3A5 polymorphisms are used to predict the initial dosage of tacrolimus therapy, the predictive capability of genetic information for dosing at early stage post-renal transplantation is unknown. We investigated the influence of polymorphisms over time. An initial oral dose of modified-release once-daily tacrolimus formulation (0.20 mg/kg) was administered to 50 Japanese renal transplant patients every 24 h. Stepwise multiple linear regression analysis for tacrolimus dosing was performed each week to determine the effect of patient clinical characteristics. The dose-adjusted trough concentration was approximately 70% higher for patients with the CYP3A5*3/*3 than patients with the CYP3A5*1 allele before the second pre-transplantation tacrolimus dose (0.97 (0.78–1.17) vs. 0.59 (0.45–0.87) ng/mL/mg; p < 0.001). The contribution of genetic factors (CYP3A5*1 or *3) for tacrolimus dosing showed increased variation from Day 14 to Day 28 after transplantation: 7.2%, 18.4% and 19.5% on Days 14, 21 and 28, respectively. The influence of CYP3A5 polymorphisms on the tacrolimus maintenance dosage became evident after Day 14 post-transplantation, although the tacrolimus dosage was determined based only on patient body weight for the first three days after surgery. Tacrolimus dosage starting with the initial administration should be individualized using the CYP3A5 genotype information.

Cytochrome P450 (CYP) 2C19 (CYP2C19) genotype is regarded as a useful tool to predict area under the blood concentration-time curve (AUC) of proton pump inhibitors (PPIs). In our results, however, CYP2C19 genotypes had no influence on AUC of all PPIs during fluvoxamine treatment. These findings suggest that CYP2C19 genotyping is not always a good indicator for estimating AUC of PPIs. Limited sampling strategies (LSS) were developed to estimate AUC simply and accurately. It is important to minimize the number of blood samples because of patient's acceptance. This article reviewed the usefulness of LSS for estimating AUC of three PPIs (omeprazole: OPZ, lansoprazole: LPZ and rabeprazole: RPZ). The best prediction formulas in each PPI were AUCOPZ=9.24×C6h+2638.03, AUCLPZ=12.32×C6h+3276.09 and AUCRPZ=1.39×C3h+7.17×C6h+344.14, respectively. In order to optimize the sampling strategy of LPZ, we tried to establish LSS for LPZ using a time point within 3 hours through the property of pharmacokinetics of its enantiomers. The best prediction formula using the fewest sampling points (one point) was AUCracemic LPZ=6.5×C3h of (R)-LPZ+13.7×C3h of (S)-LPZ−9917.3×G1−14387.2×G2+7103.6 (G1: homozygous extensive metabolizer is 1 and the other genotypes are 0; G2: heterozygous extensive metabolizer is 1 and the other genotypes are 0). Those strategies, plasma concentration monitoring at one or two time-points, might be more suitable for AUC estimation than reference to CYP2C19 genotypes, particularly in the case of coadministration of CYP mediators.