Masato Fukae

Pharmacogenomic/pharmacokinetic assessment of a four-probe cocktail for CYPs and OATPs following oral microdosing.

OBJECTIVES To test whether the multiple phenotype and genotype relationships established using therapeutic dose, can be reproduced following oral microdosing using substrates of CYP2C9 (warfarin and glibenclamide), CYP2C19 (lansoprazole), CYP2D6 (dextromethorphan), and OATPs (glibenclamide). METHODS A cocktail of test drugs was administered orally under the microdose in liquid or capsule form, and then a therapeutic dose of dextromethorphan was administered to 17 healthy subjects whose genotypes for CYPs and OATPs had been prescreened. Concentrations of the drugs and their metabolites were measured by LC-MS/MS. RESULTS The AUC and t1/2 of glibenclamide following the microdosing tended to be higher and longer, respectively, in CYP2C9*1/*3 than CYP2C9*1/*1 subjects. In contrast, there were no significant differences in any of the pharmacokinetic parameters for warfarin between the two genotypes. For CYP2D6 following the therapeutic dose, there was good concordance between genotype and phenotype; however, such relationships disappeared after microdosing. For CYP2C19 following the microdosing, there were significant differences between EMs and PMs in the pharmacokinetic parameters of lansoprazole. The relative AUC0-12 ratio of lansoprazole in EMs and PMs was 1:3.3 - 4.3. Among test drugs, phenotypic measurements of lansoprazole accorded well with the CYP2C19 genotype at the microdose as well as therapeutic dose. CONCLUSIONS The present study suggests that 1) the sampling strategy should be optimized according to pharmacokinetic profiles of the test drugs following oral microdosing, and 2) microdosing can be applied to the pharmacogenomic study of CYP-specific drugs.

Clinical impact of genetic variants of drug transporters in different ethnic groups within and across regions

Drug transporters, together with drug metabolic enzymes, are major determinants of drug disposition and are known to alter the response to many commonly used drugs. Substantial frequency differences for known variants exist across geographic regions for certain drug transporters. To deliver efficacious medicine with the right dose for each patient, it is important to understand the contribution of genetic variants for drug transporters. Recently, mutual pharmacokinetic data usage among Asian regions, which are thought to be relatively similar in their own genetic background, is expected to accelerate new drug applications and reduce developmental costs. Polymorphisms of drug transporters could be key factors to be considered in implementing multiethnic global clinical trials. This review addresses the current knowledge on genetic variations of major drug transporters affecting drug disposition, efficacy and toxicity, focusing on the east Asian populations, and provides insights into future directions for precision medicine and drug development in east Asia.

Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

Background Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. Methods The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. Results On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson’s correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Conclusion Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

Sulfasalazine disposition in a subject with 376C>T (nonsense mutation) and 421C>A variants in the ABCG2 gene

Breast cancer resistance protein (BCRP), the ABCG2 gene product, is a half-molecule ATP-binding cassette transporter that acts as an efflux transporter. BCRP substrates include not only drugs such as methotrexate, topotecan, irinotecan, its active metabolite SN-38, gefitinib, statins and sulfasalazine (SASP) but also endogenous substrates such as haemoglobin metabolites and uric acid. SASP is a candidate in vivo probe for BCRP function. SASP is not metabolized in the liver of humans 1. Zaher et al. reported that BCRP is a major determinant of the oral bioavailability as well as elimination of SASP using Bcrp-/- knockout mice 2. Some single nucleotide polymorphisms (SNPs) of the ABCG2 gene have been associated with changes in the pharmacokinetics and pharmacodynamics of clinically important drugs 3. A non-synonymous 421C>A (rs2231142, 141Q>K) is a well-known SNP causing the increased oral bioavailability of BCRP substrates, such as SASP 4.

Population pharmacodynamic analysis of LDL-cholesterol lowering effects by statins and co-medications based on electronic medical records.

AIMS HMG-CoA reductase inhibitors are available for use in low density lipoprotein-cholesterol (LDL-C) lowering therapy. The purposes of this study were to develop a population pharmacodynamic (PPD) model to describe the time course for the LDL-C lowering effects of statins and assess the efficacy of combination therapy based on electronic medical records. METHODS Patient backgrounds, laboratory tests and prescribed drugs were collected retrospectively from electronic medical records. Patients who received atorvastatin, pitavastatin or rosuvastatin were enrolled. A physiological indirect response model was used to describe the changes observed in LDL-C concentrations. The PPD analysis was performed using nonmem 7.2.0 with the first order conditional estimation method with interaction (FOCE-INTER). RESULTS An indirect response Imax model, based on the 2863 LDL-C concentrations of 378 patients, successfully and quantitatively described the time course for the LDL-C lowering effects of three statins. The combination of ezetimibe, a cholesterol absorption inhibitor, decreased the LDL synthesis rate (Kin ) by 10.9%. A simulation indicated that the combined treatment of ezetimibe with rosuvastatin (2.5 mg day(-1) ) led to superior clinical responses than those with high doses of rosuvastatin (5.0 mg day(-1) ) monotherapy, even in patients with higher baseline LDL-C concentrations prior to the treatment. CONCLUSIONS A newly constructed PPD model supported previous evidence for the beneficial effects of ezetimibe combined with rosuvastatin. In addition, the established framework is expected to be applicable to other drugs without pharmacokinetic data in clinical practice.

Small-Dosing Clinical Study: Pharmacokinetic, Pharmacogenomic (SLCO2B1 and ABCG2), and Interaction (Atorvastatin and Grapefruit Juice) Profiles of 5 Probes for OATP2B1 and BCRP

The aims of this study were (1) to investigate the effects of atorvastatin (10 mg, therapeutic dose) and grapefruit juice (GFJ), inhibitors of OATP2B1, on the pharmacokinetics of substrates for OATP2B1 and BCRP under oral small-dosing conditions (300 μg sulfasalazine, 250 μg rosuvastatin, 300 μg glibenclamide, 1200 μg celiprolol, and 600 μg sumatriptan), and (2) to evaluate the contribution of SLCO2B1*3 and ABCG2 c.421C>A polymorphisms to the pharmacokinetics of the 5 test drugs in 23 healthy volunteers. In the 3 phases, the test drugs were administered to volunteers with either water (control phase), atorvastatin, or GFJ. GFJ but not atorvastatin reduced the exposure of the test drugs significantly more than the control phase, suggesting that all 5 test drugs are substrates for OATP2B1. The SLCO2B1*3 genotype had no effect on the pharmacokinetics of the test drugs. In contrast, the exposure of sulfasalazine and rosuvastatin was significantly higher in ABCG2 421C/A than in ABCG2 421C/C individuals at all 3 phases, even under small-dosing conditions.

Effect of Curcumin on Sulfasalazine Pharmacokinetics in HealthyVolunteers

Curcumin, a commonly used spice, is a naturally occurring polyphenol. It has been reported that curcumin inhibited the transport activity of breast cancer resistance protein (BCRP/ABCG2) in animal studies, and curcumin caused significantly increased plasma concentrations of sulfasalazine (SASP), an in vivo probe for BCRP function in human. In this study, we assessed the influence of prior administration of curcumin on the pharmacokinetics of SASP. An open-label, single-arm and two-phase study was conducted in 34 healthy participants. A single dose of SASP (2,000 mg) was administered orally after overnight fast (phase 1). After seven days washout period, a single oral dose of curcumin (2,000 mg) was administered, and then, 4 days to 5 days after administration of curcumin, 2,000 mg of SASP was administered orally again (phase 2). Plasma concentrations of SASP were assayed by highperformance liquid chromatography. Orally 4 days to 5 days’ time lag between SASP and curcumin intake disappeared the interaction. The disappeared interaction may be responsible for the extremely low bioavailability of curcumin and the disappearance of curcumin in the gastro-intestinal tracts before the administration of SASP. Our findings suggested that 4 days to 5 days’ time lag is necessary to avoid the drug interaction between BCRP substrates and curcumin.

Circulating intestine-derived exosomal miR-328 in plasma, a possible biomarker for estimating BCRP function in the human intestines

A variant in the breast cancer resistance protein (BCRP) gene, 421C> A is a useful biomarker for describing large inter-individual differences in the pharmacokinetics of sulfasalazine (SASP), a BCRP substrate. However, large intra-genotypic variability still exists in spite of the incorporation of this variant into the pharmacokinetics of SASP. Since miR-328 negatively regulates BCRP expression in human tissues, we hypothesized that exosomal miR-328 in plasma, which leaks from the intestines, is a possible biomarker for estimating BCRP activity in the human intestines. We established an immunoprecipitation-based quantitative method for circulating intestine-derived miR-328 in plasma using an anti-glycoprotein A33 antibody. A clinical study was conducted with an open-label, non-randomized, and single-arm design involving 33 healthy participants. Intestine-derived exosomal miR-328 levels positively correlated (P < 0.05) with SASP AUC0-48, suggesting that subjects with high miR-328 levels have low intestinal BCRP activity, resulting in the high AUC of SASP. Circulating intestine-derived exosomal miR-328 in plasma has potential as a possible biomarker for estimating BCRP function in the human intestines.

Population pharmacodynamic analysis of hemoglobin A1c-lowering effects by adding treatment of DPP-4 inhibitors (sitagliptin) in type 2 diabetes mellitus patients based on electronic medical records

AIM To develop a population pharmacodynamic (PPD) model describing the time course for the hemoglobin A1c (HbA1c)-lowering effects of adding treatment of DPP-4 inhibitors and to assess the efficacy of combination therapy in type 2 diabetes mellitus patients based on electronic medical records. METHODS Information on patients was collected retrospectively from electronic medical records. Of the 4 DPP-4 inhibitors used, we focused on sitagliptin as it had the best time-response relationships. A physiological indirect response model was developed to describe changes in HbA1c levels. RESULTS An indirect response model, based on the 1300 HbA1c levels of 160 patients, described the time course for the HbA1c-lowering effects of adding sitagliptin. The combination with pioglitazone decreased the HbA1c synthesis rate by 7.74% relative to without pioglitazone. Bayesian forecasting based on the final PDD model using the first two HbA1c observations, before and within 30days after the addition of sitagliptin, gave a precise prediction of HbA1c-lowering effects individually. CONCLUSIONS Our PPD model quantitatively described the beneficial effects of combination therapy with pioglitazone and sitagliptin. The proposal methodology is also expected to be applicable to other medicines based on electronic medical records in clinical practice.

Population Pharmacodynamic Analysis of Uric Acid–Lowering Effects of Febuxostat Based on Electronic Medical Records in Two Hospitals

The aim of this study was to develop a population pharmacodynamic (PPD) model to describe uric acid (UA)–lowering effects in patients treated with febuxostat based on electronic medical records in 2 independent hospitals (university and city hospitals). Interhospital differences in the PPD model were also evaluated. We conducted the following 2 approaches to build the PPD models. A PPD model was developed separately using individual hospital data, and structural models and covariates between the two hospitals were compared (approach A). Another PPD model was developed using all available data from both hospitals, and differences between the 2 hospitals were evaluated by performing a covariate analysis on all PPD parameters (approach B). PPD analyses were performed by NONMEM using data from 358 patients. In both approaches, one indirect response model was established. In approach A, 2 diuretics (loops and thiazides) and renal function tests (Scr or BUN) were selected as covariates for the UA baseline level (serum UA levels just before the febuxostat treatment), whereas 2 diuretics and BUN were selected in approach B. A covariate analysis indicated that loops and thiazides increased UA baseline levels by 7%–14% and 6%–11%, respectively. In approach B, “hospital” was identified as a significant covariate for the UA baseline level; the baseline level was 7% higher in the city hospital. A PPD analysis may provide a precise description of the time course of the UA‐lowering effects of febuxostat and quantitatively detect an interhospital difference in the UA baseline level.