Translational and Clinical Pharmacology最新文献

Focal epilepsy is the most common type of epilepsy in Korea, and anti-epileptic drugs (AEDs) are the main treatment option for patients. This study aimed to compare the efficacy and safety of AEDs for focal epilepsy through a meta-analysis. The AEDs prescribed in Korea as monotherapy and adjunctive treatment for patients with focal epilepsy were included for analysis. Relevant articles were searched for randomized clinical trials of AEDs and treatment outcomes were analyzed on the basis of the 50% responder rate, seizure-free rate, treatment withdrawal rate, and emergence rates of adverse events (AEs). The odds ratios (ORs) and their 95% confidence intervals (CI) of study outcome were calculated using combined data from multiple studies. A total of 47 studies were included in the meta-analysis. The seizure-free rate, treatment withdrawal rate, and AE rate were not significantly different among the AEDs recommended for monotherapy. Among the AEDs recommended for adjunctive treatment, topiramate and oxcarbazepine yielded the highest OR in comparison with placebo for each efficacy parameter: the 50% responder rate for topiramate = 6.42 (3.76-11.6) and the seizure-free rate for oxcarbazepine = 32.7 (6.05-899). The third-generation AEDs (brivaracetam and perampanel) yielded relatively better safety outcomes than other AEDs. In general, the 50% responder rate and treatment withdrawal rate tended to increase as the dose of the AEDs increased. The results from the current meta-analysis of the efficacy and safety data of various AEDs may provide insight into optimal pharmacotherapy for the treatment of focal epilepsy.

Along with the multiple neuroprotective effect, recent studies suggest that gintonin might increase the blood brain barrier permeability. We evaluated the effect of gintonin on the vascular permeability changes in different brain segments, using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). In this 8-week, randomized, open label pilot study, ten participants with subjective memory impairment but preserved cognitive function assigned to gintonin-enriched fraction (GEF) 300 mg/day or placebo groups. Korean versions of the Alzheimer's disease assessment scale (ADAS-K) and DCE-MRI parameters including K^trans and V_p in different brain segments were evaluated at baseline and at 8 weeks after treatment. Nine participants completed the study protocol. No adverse events occurred during the observation period for 8 weeks in both groups. Following gintonin administration, increment trends of the brain permeability that did not reach a statistical significance were observed in the left hippocampus (K^trans and V_p, both, p = 0.062), left thalamus and in left putamen (K^trans, p = 0.062), and left insula and right amygdala (V_p, p = 0.062), but not in the control placebo group. The increment of the K^trans value in the left thalamus from the baseline was highly correlated with the change of the ADAS scores (r = -0.900, p = 0.037). Gintonin might enhance the blood-brain barrier (BBB) permeability in the brain structures involved in cognitive functions. Further efficacy exploration for the synergistic effect of gintonin's BBB permeability enhancement to its other cognitive enhancing mechanisms are warranted.

Trial registration: Clinical Research Information Service Identifier: KCT0003418.

Clozapine has been used as a treatment of schizophrenia. Despite its large interindividual variability, few reports addressed the physiologically-based pharmacokinetic modeling and simulation (PBPK M&S) of clozapine in patients. This study aimed to develop a PBPK M&S of clozapine in Korean patients with schizophrenia. PBPK modeling for clozapine was constructed using a population-based PBPK platform, the SimCYP^® Simulator (V19; Certara, Sheffield, UK). The PBPK model was developed by optimizing the physiological parameters of the built-in population and compound libraries in the SimCYP^® Simulator. The model verification was performed with the predicted/observed ratio for pharmacokinetic parameters and visual predictive checks (VPCs) plot. Simulations were performed to predict toxicities according to dosing regimens. From published data, 230 virtual trials were simulated for each dosing regimen. The predicted/observed ratio for the area under the curve and peak plasma concentration was calculated to be from 0.78 to 1.34. The observation profiles were within the 5th and 95th percentile range with no serious model misspecification through the VPC plot. A significant impact on age and gender was found for clozapine clearance. The simulation results suggested that 150 mg twice a day and 150 mg three times a day of clozapine have toxicity concerns. In conclusion, a PBPK model was developed and reasonable parameters were made from the data of Korean patients with schizophrenia. The provided model might be used to predict the pharmacokinetics of clozapine and assist dose adjustment in clinical settings.

For the treatment of hypertension, fixed-dose combinations (FDCs) of antihypertensive drugs can provide complementary benefits from improved compliance and cost-effectiveness compared with loose combinations of corresponding drugs. A new FDC of fimasartan/amlodipine/hydrochlorothiazide 60/10/25 mg is undergoing clinical development. A randomized, open-label, single-dose, 3-period, 3-sequence, partially replicated crossover phase 1 study was conducted to compare the pharmacokinetics (PKs) between the FDC of fimasartan/amlodipine/hydrochlorothiazide 60/10/25 mg and a loose combination of a dual-combination FDC (fimasartan/amlodipine 60/10 mg) and hydrochlorothiazide 25 mg. Sixty healthy subjects were randomized, and 55 subjects completed the study. Serial blood samples were collected, and plasma concentrations of fimasartan, amlodipine and hydrochlorothiazide were measured to analyze PK parameters. The PK profiles of the FDC were similar to those of the loose combinations. The geometric mean ratios (GMRs) and 90% confidence intervals (CIs) of the FDC to loose combinations for the maximum plasma concentration (C_max) and area under the curve until the last measurable time point (AUC_last) were within the conventional bioequivalent range of 0.80 to 1.25. The GMRs and 90% CIs of fimasartan, amlodipine and hydrochlorothiazide were 1.0163 (0.8681-1.1898), 0.9595 (0.9256-0.9946), and 1.1294 (1.0791-1.1821) for C_max and 1.0167 (0.9347-1.1059), 0.9575 (0.9317-0.9841), and 1.0561 (1.0170-1.0967) for AUC_last, respectively. Both the FDC and loose combinations were well tolerated. In conclusion, the FDC of fimasartan/amlodipine/hydrochlorothiazide 60/10/25 mg showed similar PK profiles to those of the corresponding loose combination, and both treatments were well tolerated.

This tutorial explains the basic concept of parametric time to event (TTE) models, focusing on commonly used exponential, Weibull, and log-logistic model. TTE data is commonly used as endpoint for treatment effect of a drug or prognosis of diseases. Although non-parametric Kaplan-Meier analysis has been widely used for TTE data analysis, parametric modeling analysis has its own advantages such as ease of simulation, and evaluation of continuous covariate. Accelerated failure time model is introduced as a covariate model for TTE data together with proportional hazard model. Compared to proportional hazard model, accelerated failure time model provides more intuitive results on covariate effect since it states that covariates change TTE whereas in proportional hazard model covariates affect hazard.

Tenofovir is the representative treatment for human immunodeficiency virus and hepatitis B virus infection. This study was conducted to assess the pharmacokinetics (PKs) and safety characteristics after a single administration of tenofovir disoproxil phosphate compared to tenofovir disoproxil fumarate in healthy male subjects. An open-label, randomized, single administration, two-treatment, two-sequence crossover study was conducted in 37 healthy volunteers. Serial blood samples were collected up to 72 hours. Non-compartmental analysis was used to calculate the PK parameters. The 90% confidence intervals (90% CIs) of the geometric mean ratio (GMR) were calculated for comparing tenofovir disoproxil phosphate to tenofovir disoproxil fumarate. Safety assessments were performed including clinical laboratory tests, adverse events, etc. during the study. The GMR and 90% CIs were 1.0514 (0.9527-1.1603) for C_max and 1.0375 (0.9516-1.1311) for AUC_last, respectively, and both fell within the conventional bioequivalence range of 0.8-1.25. Both tenofovir salt forms were tolerable. This study demonstrated that tenofovir disoproxil phosphate (292 mg) was bioequivalent to tenofovir disoproxil fumarate (300 mg).

Histamine acts by binding to four histamine receptors (H1 to H4), of which the H1 is known to participate in dilate blood vessels, bronchoconstriction, and pruritus. Olopatadine hydrochloride blocks the release of histamine from mast cells and it inhibits H1 receptor activation. Olopatadine hydrochloride is anti-allergic agent that is effectively used. The object of this study had conducted to compare the pharmacokinetics (PKs) and safety characteristics between olopatadine hydrochloride 5 mg (test formulation) and olopatadine hydrochloride 5 mg (reference formulation; Alerac ^®) in Korean subjects. This study had conducted an open-label, randomized, fasting condition, single-dose, 2-treatment, 2-period, 2-way crossover. Subjects received single-dosing of reference formulation or test formulation in each period and blood samples were collected over 24 hours after administration for PK analysis. A wash-out period of 7 days was placed between the doses. Plasma concentration of olopatadine were determined using liquid chromatography-tandem spectrometry mass (LC-MS/MS). A total of 32 subjects were enrolled and 28 subjects completed. There were not clinical significantly different in the safety between two treatment groups for 32 subjects who administered the study drug more than once. The geometric mean ratio of test formulation to reference formulation and its 90% confidence intervals for The peak plasma concentration (C_max) and the areas under the plasma concentration-time curve from 0 to the last concentration (AUC_last) were 1.0845 (1.0107-1.1637) and 1.0220 (1.0005-1.0439), respectively. Therefore, the test formulation was bioequivalent in PK characteristics and was equally safe as the reference formulation.

Trial registration: Clinical Research Information Service Identifier: KCT0005943.

There are several hurdles to overcome before implementing pharmacogenomics (PGx) in precision medicine. One of the hurdles is unawareness of PGx by clinicians due to insufficient pharmacogenomic information on drug labels. Therefore, it might be important to implement PGx that reflects pharmacogenomic information on drug labels, standard of prescription for clinicians. This study aimed to evaluate the level at which PGx was being used in clinical practice by comparing the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines and drug labels of the US Food and Drug Administration (FDA) and the Korea Ministry of Food and Drug Safety (MFDS). Two PGx guidelines and drugs labels were scrutinized, and the concordance of the pharmacogenomic information between guidelines and drug labels was confirmed. The concordance of the label between FDA and MFDS was analyzed. In FDA labels, the number of concordant drug with guidelines was 24, while 13 drugs were concordant with MFDS labels. The number of drugs categorized as contraindication, change dose, and biomarker testing required was 7, 12 and 12 for the FDA and 8, 5 and 4 for the MFDS, respectively. The pharmacogenomic information of 9 drugs approved by both FDA and MFDS was identical. In conclusion, pharmacogenomic information on clinical implementation guidelines was limited on both FDA and MFDS labels because of various reasons including the characteristics of the guidelines and the drug labels. Therefore, more effort from pharmaceutical companies, academia and regulatory affairs needs to be made to implement pharmacogenomic information on drug labels.

This tutorial introduces background and methods to predict the human volume of distribution (V_d) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: V_d = V_p + ∑ _T (V_T × k_tp ). In this equation, V_p (plasma volume) and V_T (tissue volume) are known physiological values, and k_tp (tissue plasma partition coefficient) is experimentally measured. Here, the k_tp may be predicted by PBPK models because it is known to be correlated with the physicochemical property of drugs and tissue composition (fraction of lipid and water). Thus, PBPK models' evolution to predict human V_d has been the efforts to find a better function giving a more accurate k_tp. When animal PK parameters estimated using i.v. PK data in ≥ 3 species are available, allometric methods can also be used to predict human V_d. Unlike the PBPK method, many different models may be compared to find the best-fitting one in the allometry, a kind of empirical approach. Also, compartmental V_d parameters (e.g., V_c, V_p, and Q) can be predicted in the allometry. Although PBPK and allometric methods have long been used to predict V_d, there is no consensus on method choice. When the discrepancy between PBPK-predicted V_d and allometry-predicted V_d is huge, physiological plausibility of all input and output data (e.g., r²-value of the allometric curve) may be reviewed for careful decision making.