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Combination therapy with rosuvastatin and ezetimibe is generally administered to patients with high cardiovascular risk. The objective of this study was to develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the interaction between rosuvastatin and ezetimibe that incorporates enterohepatic recirculation (EHC). Concentration-time data were obtained from a two-part, open-label, multiple-dose crossover, drug interaction study. In total, 50 healthy male subjects received both monotherapy and co-therapy (Part A: rosuvastatin and co-therapy; Part B: ezetimibe and co-therapy). Rosuvastatin (20 mg) or ezetimibe (10 mg) were administered once daily for 7 days as monotherapy or co-therapy. Plasma concentrations were measured for PK analysis until 72 h post-dose at steady state. The changes in low-density lipoprotein cholesterol (LDL-C) levels from baseline to steady state at 24 h after the last administration were measured. A population PK/PD model incorporating EHC was developed using Monolix 2024R1. Covariate effects were explored, and the final model was evaluated through goodness-of-fit diagnostics and visual predictive checks. Model-based simulations were conducted to compare the LDL-C lowering effects of monotherapy and co-therapy. A population PK/PD model was established using a two-compartment model for rosuvastatin and a four-compartment model for ezetimibe incorporating EHC via intermittent gallbladder emptying. No significant PK interaction was observed. An indirect response PD model reflected the independent LDL-C lowering effects of both drugs. Simulations showed LDL-C reductions of -51.0% (rosuvastatin), -25.3% (ezetimibe), and -60.7% (co-therapy), supporting the additive efficacy of co-therapy. EHC increased the exposure of total ezetimibe with limited LDL-C lowering effects. The overall PK interaction between rosuvastatin and total ezetimibe was not significant. The developed PK/PD model incorporating EHC successfully described the independent LDL-C lowering effects. These findings support the additive benefit of co-therapy of rosuvastatin and ezetimibe and may guide future research toward personalized lipid-lowering strategies.

Covariate selection is a fundamental step when building sparse prediction models in order to avoid overfitting and to gain a better interpretation of the classifier without losing its predictive accuracy. In practice the LASSO regression of Tibshirani, which penalizes the likelihood of the model by the L1 norm of the regression coefficients, has become the gold-standard to reach these objectives. Recently Lee and Oh developed a novel random-effect covariate selection method called the modified unbounded penalty (MUB) regression, whose penalization function can equal minus infinity at 0 in order to produce very sparse models. We sought to compare the predictive accuracy and the number of covariates selected by these two methods in several high-dimensional datasets, consisting in genes expressions measured to predict response to chemotherapy in breast cancer patients. These comparisons were performed by building the Receiver Operating Characteristics (ROC) curves of the classifiers obtained with the selected genes and by comparing their area under the ROC curve (AUC) corrected for optimism using several variants of bootstrap internal validation and cross-validation. We found consistently in all datasets that the MUB penalization selected a remarkably smaller number of covariates than the LASSO while offering a similar-and encouraging-predictive accuracy. The models selected by the MUB were actually nested in the ones obtained with the LASSO. Similar findings were observed when comparing these results to those obtained in their first publication by other authors or when using the area under the Precision-Recall curve (AUCPR) as another measure of predictive performance. In conclusion, the MUB penalization seems therefore to be one of the best options when sparsity is required in high-dimension. Further investigation in other datasets is however required to validate these findings.

Bioequivalence tests are fundamental step in assessing the equivalence in bioavailability between a test and reference product. In practice, two separate linear mixed models (LMMs) with random subject effects, which have an area under the concentration-time curve (AUC) and the peak concentration (C ) as the responses, have become the gold standard for evaluating bioequivalence. Recently, Lee et al developed a multivariate hierarchical generalized linear model (HGLM) for several responses that modeled correlations among multivariate responses via correlated random effects. The objective of this study was to apply this multivariate analysis to the bioequivalence test in practice and to compare the performance of multivariate HGLM and separate LMMs. Three pharmacokinetic datasets, fixed-dose combination (naproxen and esomeprazole), tramadol and fimasartan data were analyzed. We compared the 90% confidence interval (CI) for the geometric mean ratio (GMR) of a test product to a reference product using the multivariate HGLM and two conventional separate LMMs. We found that the 90% CIs for the GMRs of both AUC and C from the multivariate HGLM were narrower than those from the separate LMMs: (0.843, 1.152) vs (0.825, 1.177) for C of esomeprazole in fixed-dose combination data; (0.805, 0.931) vs (0.797, 0.941) for C in tramadol data; (0.801, 1.501) vs (0.762, 1.578) for C and (1.163, 1.332) vs (1.009, 1.341) for AUC in fimasartan data, consistent with the random subject effects from two separate LMMs being highly correlated in the three datasets (correlation coefficient r = 0.883; r = 0.966; r = 0.832). This multivariate HGLM had good performance in the bioequivalence test with multiple endpoints. This method would provide a more reasonable option to reduce the 90% CI by adding correlation parameters and thus an advantage especially in evaluating the bioequivalence of highly variable drugs with broad 90% CIs.

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. 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. Rosuvastatin and ezetimibe presented multiple peaks. The 90% confidence intervals (CIs) of the geometric mean ratios for the peak plasma concentration at steady state (C ) and area under the plasma concentration-time curve during the dosing interval at steady state (AUC ) 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. 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.

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. 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. 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. 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(®).

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. 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. 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. 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.

Metabolic abnormalities, such as preexisting diabetes or hyperglycemia or hypoglycemia during hospitalization aggravated the severity of COVID-19. We evaluated whether diabetes history, hyperglycemia before and during extracorporeal membrane oxygenation (ECMO) support, and hypoglycemia were risk factors for mortality in patients with COVID-19. This study included data on 195 patients with COVID-19, who were aged ≥19 years and were treated with ECMO. The proportion of patients with diabetes history among nonsurvivors was higher than that among survivors. Univariate Cox regression analysis showed that in-hospital mortality after ECMO support was associated with diabetes history, renal replacement therapy (RRT), and body mass index (BMI) < 18.5 kg/m2. Glucose at admission >200 mg/dL and glucose levels before ventilator >200 mg/dL were not associated with in-hospital mortality. However, glucose levels before ECMO >200 mg/dL and minimal glucose levels during hospitalization <70 mg/dL were associated with in-hospital mortality. Multivariable Cox regression analysis showed that glucose >200 mg/dL before ECMO and minimal glucose <70 mg/dL during hospitalization remained risk factors for in-hospital mortality after adjustment for age, BMI, and RRT. In conclusion, glucose >200 mg/dL before ECMO and minimal glucose level <70 mg/dL during hospitalization were risk factors for in-hospital mortality among COVID-19 patients who underwent ECMO.

Background and objective Moxifloxacin 400 mg is a widely used positive control in thorough QT (TQT) studies, but its QT-prolonging effects in Korean subjects have not been studied. The present study was conducted to collect pilot data in Korean subjects after moxifloxacin administration to evaluate the adequacy of moxifloxacin as a positive control. Methods Thirty-eight, healthy, Korean, male subjects were recruited for pharmacokinetic (PK) blood sampling and electrocardiography (ECG) recordings at three different study sites. On day 1, a baseline 12-lead ECG was recorded, and on day 2, ECG recordings were conducted after placebo, or moxifloxacin 400- or 800-mg administration. Baseline-corrected, placebo-adjusted, corrected QT (ΔΔQTc) values were calculated. Blood samples were collected after moxifloxacin administration and PK parameters were assessed. Results A total of 33 subjects completed the study. The largest time-matched ΔΔQTc occurred approximately 4 h after dosing, with ΔΔQTcI (QT interval corrected by individual QT-RR regression model) values of 11.66 ms (moxifloxacin 400 mg) and 20.96 ms (800 mg). The mean and 90 % confidence intervals of ΔΔQTcI did not include zero at any of the measurement time points. There was a positive correlation between plasma moxifloxacin concentration and ΔΔQTcI ( r  = 0.422). Dose-proportional PK profiles were observed. Conclusion Moxifloxacin 400 mg is an adequate positive control in Korean TQT studies. Our results indicate that moxifloxacin 400 mg can be used to evaluate the cardiac safety of a drug in Korean subjects.

Background and Objectives: In adolescents, adequate nutrition education is essential for making decisions regarding healthy eating habits. We aimed to investigate differences in dietary habits and body image misperception according to nutrition education status. Methods and Study Design: We analyzed 60,389 adolescents aged 12-18 years old, using the 2017 Korea Youth Risk Behavior Web-based Survey data. Participants were divided into nutrition-educated (EDU) and uneducated (non-EDU) groups, according to nutrition education status within the past year. Skipping breakfast was defined as skipping breakfast >=5 times/week. Desirable dietary behaviors were divided into the frequency of consumption of 3 items: vegetables >=1 time/day, milk >=1 time/day, and fruits >=1 time/day. Participants with normal weight who reported being slightly fat or very fat were defined as having body image misperception. Results: Compared to the non-EDU group, the odds ratio (OR) and 95% confidence interval (CI) for desirable dietary behaviors in the EDU group were 1.08 (1.04-1.13), 1.14 (1.09-1.19), and 1.16 (1.12-1.20) for the intake of fruits, milk, and vegetables, respectively. The EDU group was less associated with skipping breakfast than the non-EDU group (OR=0.91, 95% CI: 0.87-0.95, p<0.001). The OR and 95% CI of body image misperception in the EDU group were lower than in the non-EDU group (OR=0.92, 95% CI: 0.87- 0.97, p<0.001). Conclusions: Nutrition education have positive effects on healthy dietary behaviors. It also shows a negative association with body image misperception, confirming the importance of nutrition education at school.

Purpose Sarcopenia is an involuntary loss of muscle mass, strength, and physical performance associated with aging. Sarcopenia contributes to adverse health outcomes. Milk contains essential amino acids important for maintaining muscle. We investigated the relationships among milk consumption frequency (MCF), muscle mass, and strength in Korean adults. Methods We analyzed the data from 16,173 adults in the 2008–2011 Korean National Health and Nutrition Examination Survey (KNHANES), 13,537 adults in the 2014–2016 KNHANES, and 8254 adults in the Korean Genome and Epidemiology Study (KoGES). MCF was divided into two groups: (1) MCF less than once per day (MCF < 1 group) and (2) MCF greater than or equal to once per day (MCF ≥ 1 group). Low skeletal muscle mass index (LSMI) was defined using the Foundation for the National Institutes of Health sarcopenia project criteria for low muscle mass. Muscle strength was measured using the hand-grip strength test. Results The odds ratio (95% confidence interval) for LSMI in the MCF < 1 group was 1.250 (1.013–1.543) after adjusting for confounding factors, compared with the MCF ≥ 1 group (2008–2011 KNHANES). The adjusted mean for hand-grip strength was higher in the MCF ≥ 1 group (2014–2016 KNHANES). After a mean follow-up of 9 years, fat-free mass/body mass index was higher in the MCF ≥ 1 group than the MCF < 1 group (KoGES). Conclusion We found that MCF ≥ 1 was significantly associated with higher skeletal muscle index and muscle strength than lower MCF. Milk consumption could help prevent sarcopenia in adults.