Hyungmi An

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.

Trough concentration over 12.1 mg/L is a major risk factor of vancomycin-related nephrotoxicity in patients with therapeutic drug monitoring.

Background: High doses of vancomycin increase the risk of nephrotoxicity, but the quantitative relationship between vancomycin exposure and nephrotoxicity is still controversial. This study evaluated the relationship between vancomycin trough concentration and nephrotoxicity, and risk factors for nephrotoxicity in patients undergoing therapeutic drug monitoring. Methods: A total of 1269 cases from patients who underwent therapeutic drug monitoring were collected from 2006 to 2010. Receiver operating characteristic curve analysis was used to evaluate the relationship between trough concentration and the incidence of nephrotoxicity. Logistic regression using the generalized Least Absolute Shrinkage and Selection Operator (lasso) method was used to evaluate possible risk factors for nephrotoxicity. The data were divided into high/low-concentration groups by the cutoff value obtained from the receiver operating characteristic curve, and additional logistic regression using the generalized lasso method was performed for each group. Results: The cutoff value of the vancomycin trough concentration was 12.1 mg/L. Patients with high concentrations (>12.1 mg/L) were more likely to develop nephrotoxicity (odds ratio = 16.0, 95% confidence interval, 8.2–31.1). The vancomycin trough concentration was the only significant risk factor for nephrotoxicity identified using the generalized lasso (P < 0.001). In contrast, no factor was associated with nephrotoxicity in the low-concentration group. Conclusions: Vancomycin trough concentrations over 12.1 mg/L were associated with an increased risk of nephrotoxicity. This is lower than the known threshold. Trough vancomycin concentration over the threshold was the only risk factor of nephrotoxicity among demographic factors, dosing regimen, and other clinical conditions in this study. It is suggested that vancomycin trough concentrations greater than 12.1 mg/L require close monitoring for nephrotoxicity.

a pharmacokinetic comparison of two voriconazole formulations and the effect of cYP2c19 polymorphism on their pharmacokinetic profiles

Purpose SYP-1018 is a lyophilized polymeric nanoparticle formulation of voriconazole that is under development for intravenous dosing. This study compared the pharmacokinetic and tolerability profiles of SYP-1018 with those of Vfend®, the marketed formulation of voriconazole. The effect of CYP2C19 polymorphism on the voriconazole pharmacokinetics was also evaluated. Methods An open-label, two-treatment, two-period, two-sequence crossover study was conducted in 52 healthy male volunteers, who randomly received a single intravenous infusion of either of the two voriconazole formulations at 200 mg. Blood samples were collected up to 24 hours after drug administration for pharmacokinetic analysis. The plasma concentrations of voriconazole were determined using liquid chromatography with tandem mass spectrometry, and the pharmacokinetic parameters were estimated using a noncompartmental method. CYP2C19 genotype was identified in 51 subjects. Results The geometric mean ratio (90% confidence interval) of SYP-1018 to Vfend® was 0.99 (0.93–1.04) for the maximum plasma concentrations (Cmax) and 0.97 (0.92–1.01) for the area under the concentration–time curve (AUC) from dosing to the last quantifiable concentration (AUClast). Nineteen homozygous extensive metabolizers (EMs, *1/*1), 19 intermediate metabolizers (IMs, *1/*2 or *1/*3), and ten poor metabolizers (PMs, *2/*2, *2/*3, or *3/*3) were identified, and the pharmacokinetic comparability between SYP-1018 and Vfend® was also noted when analyzed separately by genotype. The systemic exposure to voriconazole was greatest in the PM group, followed by the IM, and then the EM groups. Furthermore, the intrasubject variability for Cmax and AUClast was greater in IMs and PMs than in EMs. No serious adverse event occurred, and both treatments were well tolerated. Conclusion SYP-1018 had comparable pharmacokinetic and tolerability profiles to Vfend® after a single intravenous infusion. CYP2C19 genotype affected not only the pharmacokinetics of voriconazole, but its intrasubject variability. SYP-1018 can be further developed as a clinically effective alternative to Vfend®.

Pharmacokinetic and pharmacodynamic interaction between ezetimibe and rosuvastatin in healthy male subjects

Background and objective Rosuvastatin and ezetimibe are commonly applied in lipid-lowering pharmacotherapy. However, the pharmacokinetic (PK) interaction was not clear by the coadministration of rosuvastatin and ezetimibe. This study investigated the pharmacodynamic (PD) and PK interactions between rosuvastatin and ezetimibe through a crossover clinical trial. Subjects and methods A randomized, open-label, multiple-dose, two-treatment, two-period, two-sequence crossover study with two treatment parts was conducted in healthy male subjects. Study part A involved rosuvastatin, and study part B involved ezetimibe. A total of 25 subjects in both parts completed the PK and PD evaluations. Rosuvastatin (20 mg) or ezetimibe (10 mg) was administered once daily for 7 days as monotherapy or co-therapy. The plasma concentrations of rosuvastatin, total ezetimibe and free ezetimibe were measured for 72 h after day 7. Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and total cholesterol (TC) were investigated for the PD assessments on day 1 (pretreatment) and day 8. Results Rosuvastatin and ezetimibe presented multiple peaks. The 90% confidence intervals (CIs) of the geometric mean ratios for the peak plasma concentration at steady state (Cmax,ss) and area under the plasma concentration–time curve during the dosing interval at steady state (AUCτ,ss) of rosuvastatin and total ezetimibe were within the range 0.8–1.25. However, the coadministration increased the systemic exposure of free ezetimibe. In the PD assessments, rosuvastatin and ezetimibe monotherapy reduced the LDL-C and TC levels effectively. In addition, the lipid-lowering effects of the coadministration corresponded to an approximate summation of the effects of rosuvastatin and ezetimibe monotherapy. However, no significant changes in HDL-C were observed with rosuvastatin or ezetimibe treatment. No significant safety issue was noted. Conclusion The coadministration of rosuvastatin and ezetimibe revealed a bioequivalent PK interaction. Additional lipid-lowering effects, including decreased LDL-C and TC, were observed as expected in combination therapy without significant safety concern.

An analysis of QTc prolongation with atypical antipsychotic medications and selective serotonin reuptake inhibitors using a large ECG record database

ABSTRACT Background: This study evaluated the effects of atypical antipsychotic drugs and selective serotonin reuptake inhibitors (SSRIs) on the corrected QT (QTc) interval using a large database obtained from clinical settings. Additionally, the effects of factors including age on QTc intervals were estimated. Methods: Using an open-access QT database (ECG-ViEW), QTc-lengthening effects of 14 selected atypical antipsychotics and SSRIs were compared to those of a positive control drug, cilostazol, and a negative control drug, diazepam. We also evaluated effects of age, sexgender, and select electrolyte levels on observed QTc intervals. Results: The frequency of QTc prolongation with the pooled data of the 14 study drugs was lower than that with cilostazol (age-adjusted odds ratio (OR) = 0.43, 95% confidence interval (CI) = 0.27-0.69), but no significant difference was found relative to when compared with that with diazepam (age-adjusted OR = 0.89, 95% CI = 0.55-1.47). Furthermore, administration of the 14 study drugs significantly increased the QTc interval by 2.89 ms after each 10-year age increment (p-value < 0.0001). Conclusions: This study suggests that atypical antipsychotic drugs and SSRIs are less likely to be associated with QTc prolongation in clinical settings. In addition, age showed a significant association with the QTc interval. Further studies with well-characterized cohorts are warranted.

Predictive performance of gentamicin dosing nomograms.

Background Several nomograms have been proposed to facilitate the determination of initial gentamicin dosing regimens in clinical settings. This study aimed to assess the predictive performance of these nomograms in Korean patients. Methods Gentamicin concentrations were determined in 84 patients with infective endocarditis (IE) and in 95 patients with other infections. All patients underwent therapeutic drug monitoring in Seoul National University Hospital from 2006 to 2012. Individual pharmacokinetic parameters were estimated using a Bayesian method, which predicted steady state peak and trough serum concentrations. Six nomograms were evaluated in patients with “other” infections: the Thomson guidelines, Hull-Sarubbi table, and Rule of Eights, for multiple daily dosing; and the Hartford nomogram, Barnes-Jewish Hospital nomogram, and Sanford Guide, for extended-interval dosing. In IE patients, synergistic combination dosing nomograms, based on the American Heart Association dosing interval guidelines, were evaluated. Results Gentamicin dosing nomograms performed poorly in attaining the target peak serum concentrations. Multiple-daily dosing nomograms predicted peak serum gentamicin concentrations better than did the extended-interval dosing nomograms (31.9%–72.3% vs 4.3%–45.7%, respectively). Similarly, in patients with IE, the once-daily dosing nomogram resulted in a significantly lower percentage of patients achieving target peak gentamicin concentrations than that associated with the thrice-daily dosing nomogram (P=0.0015). All of the multiple-daily dosing, extended-interval dosing, and synergistic combination dosing nomograms predicted the nontoxic target trough concentrations in >80% of patients. Conclusion Gentamicin dosing nomograms performed poorly in achieving the target peak serum concentrations. New gentamicin nomograms may be required in patients with IE, particularly for once-daily dosing. Therapeutic drug monitoring is highly recommended for gentamicin to ensure that the target concentrations are achieved.

Bio-Equivalence Analysis using Linear Mixed Model

Linear mixed models are commonly used in the clinical pharmaceutical studies to analyze repeated measures such as the crossover study data of bioequivalence studies. In these models, random effects describe the correlation between repeated outcomes and variance-covariance matrix explain within-subject variabilities. Bioequivalence analysis verifies whether a 90% confidence interval for geometric mean ratio of Cmax and AUC between reference drug and test drug is included in the bioequivalence margin [0.8, 1.25] performed using linear mixed models with period, sequence and treatment effects as fixed and sequence nested subject effects as random. A Levofloxacin study is referred to for an example of real data analysis.