Evaluation of Drug Blood-Brain-Barrier Permeability Using a Microfluidic Chip.

The blood-brain-barrier (BBB) is made up of blood vessels whose permeability enables the passage of some compounds. A predictive model of BBB permeability is important in the early stages of drug development. The predicted BBB permeabilities of drugs have been confirmed using a variety of in vitro methods to reduce the quantities of drug candidates needed in preclinical and clinical trials. Most prior studies have relied on animal or cell-culture models, which do not fully recapitulate the human BBB. The development of microfluidic models of human-derived BBB cells could address this issue. We analyzed a model for predicting BBB permeability using the Emulate BBB-on-a-chip machine. Ten compounds were evaluated, and their permeabilities were estimated. Our study demonstrated that the permeability trends of ten compounds in our microfluidic-based system resembled those observed in previous animal and cell-based experiments. Furthermore, we established a general correlation between the partition coefficient (Kp) and the apparent permeability (Papp). In conclusion, we introduced a new paradigm for predicting BBB permeability using microfluidic-based systems.

Prediction of the Drug-Drug Interaction Potential between Tegoprazan and Amoxicillin/Clarithromycin Using the Physiologically Based Pharmacokinetic and Pharmacodynamic Model.

Tegoprazan is a novel potassium-competitive acid blocker. This study investigated the effect of drug-drug interaction on the pharmacokinetics and pharmacodynamics of tegoprazan co-administered with amoxicillin and clarithromycin, the first-line therapy for the eradication of Helicobacter pylori, using physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) modeling. The previously reported tegoprazan PBPK/PD model was modified and applied. The clarithromycin PBPK model was developed based on the model provided by the SimCYP® compound library. The amoxicillin model was constructed using the middle-out approach. All of the observed concentration-time profiles were covered well by the predicted profiles with the 5th and 95th percentiles. The mean ratios of predicted to observed PK parameters, including the area under the curve (AUC), maximum plasma drug concentration (Cmax), and clearance, were within the 30% intervals for the developed models. Two-fold ratios of predicted fold-changes of Cmax and AUC from time 0 to 24 h to observed data were satisfied. The predicted PD endpoints, including median intragastric pH and percentage holding rate at pH above 4 or 6 on day 1 and day 7, were close to the corresponding observed data. This investigation allows evaluation of the effects of CYP3A4 perpetrators on tegoprazan PK and PD changes, thus providing clinicians with the rationale for co-administration dosing adjustment.

Bioanalytical methods for the detection of duloxetine and thioctic acid in plasma using ultra performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS).

Duloxetine and thioctic acid (TA) are standard drugs for treating diabetic neuropathy, a primary complication associated with diabetes. In this study, ultra performance liquid chromatography coupled with tandem mass spectrometry methods was successfully developed and validated for quantifying duloxetine and TA in biological samples. The protein precipitation method was used to extract duloxetine, TA and their internal standards from beagle dog plasma. A Hypersil Gold C18 column (150 × 2.1 mm, 1.9 µm) was used for the experiment. Isocratic elution with 0.1% formic acid in acetonitrile (A) and 0.1% formic acid (B) was used for duloxetine, whereas a gradient elution with 0.03% acetic acid (A) and acetonitrile (B) was used for TA. The validated parameters included linearity, sensitivity, accuracy, precision, selectivity, matrix effect, stability, and recovery under different conditions. The linear ranges of the calibration curves for duloxetine and TA were 5-800 ng/mL and 5-1,000 ng/mL, respectively. An intra- and inter-run precision of ± 15% can be observed in all quality control samples. These methods were successfully used for pharmacokinetics (PKs) studies in beagle dogs to compare PK differences in a fixed-dose combination including duloxetine and TA and co-administration of the 2 drugs.

Integration of a Physiologically Based Pharmacokinetic and Pharmacodynamic Model for Tegoprazan and Its Metabolite: Application for Predicting Food Effect and Intragastric pH Alterations.

A physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model for tegoprazan and its major metabolite M1 was developed to predict PK and PD profiles under various scenarios. The PBPK model for tegoprazan and M1 was developed and predicted using the SimCYP® simulator and verified using clinical study data obtained after a single administration of tegoprazan. The established PBPK/PD model was used to predict PK profiles after repeated administrations of tegoprazan, postprandial PK profiles, and intragastric pH changes. The predicted tegoprazan and M1 concentration-time profiles fit the observed profiles well. The arithmetic mean ratios (95% confidence intervals) of the predicted to observed values for the area under the curve (AUC0-24 h), maximum plasma drug concentration (Cmax), and clearance (CL) for tegoprazan and M1 were within a 30% interval. Delayed time of maximum concentration (Tmax) and decreased Cmax were predicted in the postprandial PK profiles compared with the fasted state. This PBPK/PD model may be used to predict PK profiles after repeated tegoprazan administrations and to predict differences in physiological factors in the gastrointestinal tract or changes in gastric acid pH after tegoprazan administration.

Predicting the systemic exposure and lung concentration of nafamostat using physiologically-based pharmacokinetic modeling.

Nafamostat has been actively studied for its neuroprotective activity and effect on various indications, such as coronavirus disease 2019 (COVID-19). Nafamostat has low water solubility at a specific pH and is rapidly metabolized in the blood. Therefore, it is administered only intravenously, and its distribution is not well known. The main purposes of this study are to predict and evaluate the pharmacokinetic (PK) profiles of nafamostat in a virtual healthy population under various dosing regimens. The most important parameters were assessed using a physiologically based pharmacokinetic (PBPK) approach and global sensitivity analysis with the Sobol sensitivity analysis. A PBPK model was constructed using the SimCYP® simulator. Data regarding the in vitro metabolism and clinical studies were extracted from the literature to assess the predicted results. The model was verified using the arithmetic mean maximum concentration (Cmax), the area under the curve from 0 to the last time point (AUC0-t), and AUC from 0 to infinity (AUC0-∞) ratio (predicted/observed), which were included in the 2-fold range. The simulation results suggested that the 2 dosing regimens for the treatment of COVID-19 used in the case reports could maintain the proposed effective concentration for inhibiting severe acute respiratory syndrome coronavirus 2 entry into the plasma and lung tissue. Global sensitivity analysis indicated that hematocrit, plasma half-life, and microsomal protein levels significantly influenced the systematic exposure prediction of nafamostat. Therefore, the PBPK modeling approach is valuable in predicting the PK profile and designing an appropriate dosage regimen.

Prediction of Fluoxetine and Norfluoxetine Pharmacokinetic Profiles Using Physiologically Based Pharmacokinetic Modeling.

Fluoxetine is a selective serotonin reuptake inhibitor that is metabolized to norfluoxetine by cytochrome P450 (CYP) 2D6, CYP2C19, and CYP3A4. A physiologically based pharmacokinetic model for fluoxetine and norfluoxetine metabolism was developed to predict and investigate changes in concentration-time profiles according to fluoxetine dosage in the Korean population. The model was developed based on the Certara repository model and information gleaned from the literature. Digitally extracted clinical study data were used to develop and verify the model. Simulations for plasma concentrations of fluoxetine and norfluoxetine after a single dose of 60 or 80 mg fluoxetine were made based on 1000 virtual healthy Korean individuals using the SimCYP version 19 simulator. The mean ratios (simulated/observed) after a single administration of 80 mg fluoxetine for maximum plasma concentration, area under the plasma concentration-time curve, and apparent clearance were 1.12, 1.08, and 0.93 for fluoxetine; the ratios of maximum plasma concentration and area under the plasma concentration-time curve were 1.08 and 1.08, respectively, for norfluoxetine, indicating that the simulated concentration-time profiles of fluoxetine and norfluoxetine fitted the observed profiles well. The developed model was used to predict plasma fluoxetine and norfluoxetine concentration-time profiles after repeated administrations of fluoxetine in Korean volunteers. This physiologically based pharmacokinetic model could provide basic understanding of the pharmacokinetic profiles of fluoxetine and its metabolite under various situations.

Physiologically-based pharmacokinetic model for clozapine in Korean patients with schizophrenia.

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.

Urinary Metabolomic Profiling after Administration of Corydalis Tuber and Pharbitis Seed Extract in Healthy Korean Volunteers.

Pharmacometabolomics is a useful tool to identify biomarkers that can assess and predict response after drug administration. The primary purpose of pharmacometabolomics is to better understand the mechanisms and pathways of a drug by searching endogenous metabolites that have significantly changed after drug administration. DA-9701, a prokinetic agent, consists of Pharbitis seed and Corydalis tube extract and it is known to improve the gastrointestinal motility. Although the overall mechanism of action of DA-9701 remains unclear, its active ingredients, corydaline and chlorogenic acid, act as a 5-HT3 and D2 receptor antagonist and 5-HT4 receptor agonist. To determine the significant metabolites after the administration of DA-9701, a qualitative analysis was carried out using ultra-high performance liquid chromatography coupled with orbitrap mass spectrometer followed by a multivariate analysis. Seven candidates were selected and a statistical analysis of fold change was performed over time. Our study concluded that all the seven selected metabolites were commonly involved in lipid metabolism and purine metabolism.

Determination of candesartan or olmesartan in hypertensive patient plasma using UPLC-MS/MS.

Candesartan and olmesartan are angiotensin II receptor blockers (ARBs) used for the treatment of hypertension and heart failure. Quantitation methods for candesartan and olmesartan were developed using ultra-high performance liquid chromatography-tandem mass spectrometry following protein precipitation. Candesartan was separated using 5 mM ammonium formate (A) and 100% acetonitrile (B) and olmesartan was separated using 2 mM ammonium formate with 0.1% formic acid (A) and 100% acetonitrile (B). Separation was performed using an isocratic method with a Thermo hypersil GOLD C18 column. Electrospray ionization was used for analyte ionization and detection of candesartan, olmesartan, and the internal standards by multiple reaction monitoring. Developed method showed excellent linearity (r > 0.99) in the concentration range of 2-500 ng/mL for candesartan and 5-2,500 ng/mL for olmesartan. Accuracies were 86.70-108.8% for candesartan and 87.87-112.6% for olmesartan. These methods were able to successfully measure plasma candesartan or olmesartan concentrations in hypertensive patients. This study can be used for pharmacokinetic studies of candesartan or olmesartan in humans.

Bioanalytical Method Using Ultra-High-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry (UHPL-CHRMS) for the Detection of Metformin in Human Plasma.

Metformin is the first-line medicine for the treatment of type 2 diabetes. Drug interactions between metformin and other drugs, food, or beverages cannot only cause changes in the pharmacokinetic profiles but also affect the efficacy of metformin. The purpose of this study was to develop a rapid and reliable bioanalytical method for the detection of plasma metformin concentration in humans. To remove interfering substances in plasma, acidified acetonitrile (acetonitrile containing 0.1% formic acid) was added to samples. Ultra-high-performance liquid chromatography (UHPLC) coupled with high resolution mass spectrometry (HRMS) was used to analyze metformin and its internal standard (metformin-d6). Analyte separation was performed on a BEH HILIC analytical column (100 × 2.1 mm, 1.7 µm) using a gradient elution of 0.1% formic acid (A) and acetonitrile with 0.1% formic acid (B). The total chromatographic run time was 2 min. The developed method was validated for its linearity, accuracy and precision, selectivity (signal of interfering substance; analyte, lower limit of quantification (LLOQ) ≤ 20%; IS, IS ≤ 5%), sensitivity (LLOQ, 5 ng/mL; S/N ratio ≥ 10), stability (low quality control (LQC, 15 ng/mL), 2.95-14.19%; high quality control (HQC, 1600 ng/mL), -9.49-15.10%), dilution integrity (diluted QC (4000 ng/mL); 10-folds diluted QC (400 ng/mL); 5-folds diluted QC (800 ng/mL); accuracy, 81.30-91.98%; precision, ≤4.47%), carry-over (signal of double blank; analyte, LLOQ ≤20%; IS, IS ≤5%), and matrix effect (LQC, 10.109%; HQC, 12.271%) under various conditions. The constructed calibration curves were shown linear in the concentration range of 5-2000 ng/mL, with within- and between-run precision values of <8.19% and accuracy in the range of 91.13-105.25%. The plasma metformin concentration of 16 healthy subjects was successfully measured by applying the validated bioanalytical method.

Evaluation of the Effect of CYP2D6 Genotypes on Tramadol and O-Desmethyltramadol Pharmacokinetic Profiles in a Korean Population Using Physiologically-Based Pharmacokinetic Modeling.

Tramadol is a µ-opioid receptor agonist and a monoamine reuptake inhibitor. O-desmethyltramadol (M1), the major active metabolite of tramadol, is produced by CYP2D6. A physiologically-based pharmacokinetic model was developed to predict changes in time-concentration profiles for tramadol and M1 according to dosage and CYP2D6 genotypes in the Korean population. Parallel artificial membrane permeation assay was performed to determine tramadol permeability, and the metabolic clearance of M1 was determined using human liver microsomes. Clinical study data were used to develop the model. Other physicochemical and pharmacokinetic parameters were obtained from the literature. Simulations for plasma concentrations of tramadol and M1 (after 100 mg tramadol was administered five times at 12-h intervals) were based on a total of 1000 virtual healthy Koreans using SimCYP® simulator. Geometric mean ratios (90% confidence intervals) (predicted/observed) for maximum plasma concentration at steady-state (Cmax,ss) and area under the curve at steady-state (AUClast,ss) were 0.79 (0.69-0.91) and 1.04 (0.85-1.28) for tramadol, and 0.63 (0.51-0.79) and 0.67 (0.54-0.84) for M1, respectively. The predicted time-concentration profiles of tramadol fitted well to observed profiles and those of M1 showed under-prediction. The developed model could be applied to predict concentration-dependent toxicities according to CYP2D6 genotypes and also, CYP2D6-related drug interactions.

Quantification of apixaban in human plasma using ultra performance liquid chromatography coupled with tandem mass spectrometry.

Apixaban, an inhibitor of direct factor Xa, is used for the treatment of venous thromboembolic events or prevention of stroke. Unlike many other anticoagulant agents, it does not need periodic monitoring. However, monitoring is still required to determine the risk of bleeding due to overdose or surgery. Usually, apixaban concentrations are indirectly quantified using an anti-factor Xa assay. However, this method has a relatively narrow analytical concentration range, poor selectivity, and requires an external calibrator. Therefore, the goal of current study was to establish an analytical method for determining plasma levels of apixaban using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). To this end, apixaban was separated using 2.5 mM ammonium formate (pH 3.0) (A) and 100% methanol containing 0.1% formic acid (B) using the gradient method with a Thermo hypersil GOLD column. The mass detector condition was optimized using the electrospray ionization (ESI) positive mode for apixaban quantification. The developed method showed sufficient linearity (coefficient of determination [r2 ≥ 0.997]) at calibration curve ranges. The percentage (%) changes in accuracy, precision, and all stability tests were within 15% of the nominal concentration. Apixaban concentration in plasma from healthy volunteers was quantified using the developed method. The mean maximum plasma concentration (Cmax) was 371.57 ng/mL, and the median time to achieve the Cmax (Tmax) was 4 h after administration of 10 mg apixaban alone. Although the results showed low extraction efficiency (~16%), the reproducibility (% change was within 15% of nominal concentration) was reliable. Therefore, the developed method could be used for clinical pharmacokinetic studies.

Determination of donepezil in human plasma using ultra performance liquid chromatography-tandem mass spectrometry.

An ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the quantification of donepezil in human plasma. Donepezil and donepezil-D4 were extracted from human plasma by liquid-liquid extraction using a mixture of hexane and ethyl acetate (70:30 v/v). The extracted samples were analyzed using a Thermo Hypersil Gold C18 column with 5% acetic acid in 20 mM ammonium acetate buffer (pH 3.3) and 100% acetonitrile as a mobile phase with the 60:40 (v:v) isocratic method, at a flow rate of 0.3 mL/min. The injection volume was 3 µL, and the total run time was 3 min. Inter- and intra-batch accuracies ranged from 98.0% to 110.0%, and the precision was below 8%. The developed method was successfully applied to the quantification of donepezil in human plasma. The mean (standard deviation) maximum concentration and the median (range) time to maximum concentration were 8.6 (2.0) ng/mL and 2.0 h (1.0~5.0 h), respectively, in healthy Koreans after oral administration of 5 mg donepezil.

Development of a UPLC-MS/MS method for the therapeutic monitoring of L-asparaginase.

This study aimed to develop a UPLC-MS/MS method for determining plasma levels of L-aspartic acid and L-asparagine and the activity of L-asparaginase. L-aspartic acid, L-asparagine, and L-aspartic acid-2,3,3-d3 were extracted from human plasma by protein precipitation with sulfosalicylic acid (30%, v/v). The plasma samples were analyzed using an Imtakt Intrada amino acid analysis column with 25 mM ammonium formate and 0.5% formic acid in acetonitrile as the mobile phase with step gradient method at a flow rate of 0.5 mL/min. The injection volume was 5 µL, and the total run time was 15 min. Inter- and intra-batch accuracies (%) ranged from 96.62-106.0% for L-aspartic acid and 89.85-104.8%, for L-asparagine, and the coefficient of variation (CV%) did not exceed 7%. The validation results for L-aspartic acid and L-asparagine satisfied the specified criterion, however, the results for L-asparaginase activity assay showed a borderline validity. This study could be a foundation for further development of therapeutic drug monitoring systems using UPLC-MS/MS.

Association of TNF-alpha G-308A gene polymorphism with depression: a meta-analysis.

BACKGROUND: Although many studies have investigated the association of a single nucleotide polymorphism in TNF-α G-308A gene with depression, their association is still controversial. To clarify this, we performed a meta-analysis. METHOD: Studies related to TNF-α G-308A and depression were retrieved from PubMed, Medline, Embase, and Scopus (up to April 18, 2017). The odds ratios (ORs) and 95% confidence intervals (CIs) were estimated in the models of allele comparison (G vs A), homozygote comparison (GG vs AA), dominant (GG vs GA + AA), and recessive (GG + GA vs AA) to estimate the strength of the associations. RESULTS: A total of 10 case-control studies were included in this meta-analysis. Overall, no significant association between TNF-α G-308A and depression was found (G vs A: OR [95% CI] =1.09 [0.92, 1.29]; GG vs AA: 1.24 [0.71, 2.15]; GG vs GA + AA: 1.01 [0.76, 1.35]; GG + GA vs AA: 1.22 [0.70, 2.13]). In subgroup analyses by ethnicity or age group, no statistically significant association between TNF-α G-308A polymorphisms and depression was shown. CONCLUSION: This meta-analysis revealed that TNF-α G-308A polymorphism is not associated with susceptibility to depression.

Effects of Music Therapy on the Cardiovascular and Autonomic Nervous System in Stress-Induced University Students: A Randomized Controlled Trial.

OBJECTIVE: Stress is caused when a particular relationship between the individual and the environment emerges. Specifically, stress occurs when an individual's abilities are challenged or when one's well-being is threatened by excessive environmental demands. The aim of this study was to measure the effects of music therapy on stress in university students. DESIGN: Randomized controlled trial. PARTICIPANTS: Sixty-four students were randomly assigned to the experimental group (n = 33) or the control group (n = 31). INTERVENTION: Music therapy. OUTCOME MEASURES: Initial measurement included cardiovascular indicators (blood pressure and pulse), autonomic nervous activity (standard deviation of the normal-to-normal intervals [SDNN], normalized low frequency, normalized high frequency, low/high frequency), and subjective stress. After the first measurement, participants in both groups were exposed to a series of stressful tasks, and then a second measurement was conducted. The experimental group then listened to music for 20 minutes and the control group rested for 20 minutes. A third and final measurement was then taken. RESULTS: There were no significant differences between the two groups in the first or second measurement. However, after music therapy, the experimental group and the control group showed significant differences in all variables, including systolic blood pressure (p = .026), diastolic blood pressure (p = .037), pulse (p < .001), SDNN (p = .003), normalized low frequency (p < .001), normalized high frequency (p = .010), and subjective stress (p = .026). CONCLUSION: Classical music tends to relax the body and may stimulate the parasympathetic nervous system. These results suggest music therapy as an intervention for stress reduction.

Development of a Simulation Scenario and Evaluation Checklist for Patients With Asthma in Emergency Care.

Care for patients with asthma requires prompt and effective decision-making abilities. Many nursing students report a lack of preparedness and competence with respect to their ability to perform nursing duties. Simulation-based learning has been developed as a potential solution to this problem. Moreover, the simulation scenario with an evaluation checklist offers a reliable evaluation strategy for the education and training of clinical decision-making skills among nursing students. The simulation scenario and evaluation checklist developed in this study offer a means to improve patient safety during asthma care in the emergency care unit, as well as to improve nursing students' problem-solving competencies and communication with patients with asthma.

[Effects of taping therapy on the deformed angle of the foot and pain in hallux valgus patients].

PURPOSE: This study was to examine the effects of Taping therapy on the deformed angle of the foot and pain in hallux valgus patients. METHOD: The subjects were 24 feet from 15 patients who were diagnosed withhallus valgus at the orthopedic department of K University Hospital in Seoul. Taping therapy was conducted 15 times overall during a four-week period. Data was analyzed using descriptive statistics and t-test. RESULT: The deformed angle of the foot of the hallus valgus patients significantly improved from 21.95 (4.38) to 18.75 (4.80) after Taping therapy. Pain significantly decreased from 4.73 (1.56) to 3.45 (2.21) after Taping therapy. CONCLUSION: The result shows that Taping therapy is effective in improving the deformed angle of the foot and in decreasing pain in the hallux valgus patients.