• Biomolecules & Therapeutics
• /
• v.19 no.1
• /
• pp.1-8
• /
• 2011

G-protein coupled receptors (GPCRs) constitute an important class of drug targets and are involved in every aspect of human physiology including sleep regulation, blood pressure, mood, food intake, perception of pain, control of cancer growth, and immune response. Radiometric assays have been the classic method used during the search for potential therapeutics acting at various GPCRs for most GPCR-based drug discovery research programs. An increasing number of diverse small molecules, together with novel GPCR targets identified from genomics efforts, necessitates the use of high-throughput assays with a good sensitivity and specificity. Currently, a wide array of high-throughput tools for research on GPCRs is available and can be used to study receptor-ligand interaction, receptor driven functional response, receptor-receptor interaction,and receptor internalization. Many of the assay technologies are based on luminescence or fluorescence and can be easily applied in cell based models to reduce gaps between in vitro and in vivo studies for drug discovery processes. Especially, cell based models for GPCR can be efficiently employed to deconvolute the integrated information concerning the ligand-receptor-function axis obtained from label-free detection technology. This review covers various platform technologies used for the research of GPCRs, concentrating on the principal, non-radiometric homogeneous assay technologies. As current technology is rapidly advancing, the combination of probe chemistry, optical instruments, and GPCR biology will provide us with many new technologies to apply in the future.

• Proceedings of the PSK Conference
• /
• 2003.04a
• /
• pp.252.2-252.2
• /
• 2003

It was difficult that we analysed the polymeric drugs for the physico-chemical properties. Sodium hyaluronate is a linear polysaccharide composed of repeating disaccharides of sodium glucuronate and N-acetyl glucosamine found throughout the tissues of the body with high concentrations in the vitreous humor. synovial fluid and umbilical cord. It has a role in regulating the interaction between adjoining tissues. (omitted)

• Proceedings of the Korean Society of Applied Pharmacology
• /
• 1996.04a
• /
• pp.259-261
• /
• 1996

• The Korean Journal of Physiology and Pharmacology
• /
• v.21 no.1
• /
• pp.107-115
• /
• 2017

Over the last decade, physiologically based pharmacokinetics (PBPK) application has been extended significantly not only to predicting preclinical/human PK but also to evaluating the drug-drug interaction (DDI) liability at the drug discovery or development stage. Herein, we describe a case study to illustrate the use of PBPK approach in predicting human PK as well as DDI using in silico, in vivo and in vitro derived parameters. This case was composed of five steps such as: simulation, verification, understanding of parameter sensitivity, optimization of the parameter and final evaluation. Caffeine and ciprofloxacin were used as tool compounds to demonstrate the "fit for purpose" application of PBPK modeling and simulation for this study. Compared to caffeine, the PBPK modeling for ciprofloxacin was challenging due to several factors including solubility, permeability, clearance and tissue distribution etc. Therefore, intensive parameter sensitivity analysis (PSA) was conducted to optimize the PBPK model for ciprofloxacin. Overall, the increase in $C_{max}$ of caffeine by ciprofloxacin was not significant. However, the increase in AUC was observed and was proportional to the administered dose of ciprofloxacin. The predicted DDI and PK results were comparable to observed clinical data published in the literatures. This approach would be helpful in identifying potential key factors that could lead to significant impact on PBPK modeling and simulation for challenging compounds.

• Mass Spectrometry Letters
• /
• v.10 no.2
• /
• pp.61-65
• /
• 2019

Korean ginseng (Panax ginseng Meyer) is a traditional herb used across the world to treat various diseases. Although, red ginseng is this herb's most famous product and has demonstrated diverse pharmacological activities, white ginseng (WG) is another ginseng product that is made fresh and individually regulated in Eastern Asia. Red and white ginseng show different characteristics due to distinct processing steps despite originating from the same plant, and the drug interactions induced by WG have not been well documented. Selegiline is a selective monoamine oxidase (MAO) inhibitor used as an antidyskinetic and antiparkinsonian agent. Here we developed a quantification method for selegiline in mouse plasma using a C8 stationary phase in triple quadrupole-mass spectrometry (LC-MS/MS) with multiple reaction monitoring (MRM). The validated LC-MS/MS method was successfully applied to determine the potential interaction with WG extract (0.1 g/kg/day) pre-administered for 4 weeks. The $AUC_{0-240min}$ of selegiline was altered due to a decrease in the absorption of selegiline with repeated administration of WG extract.

• Korean Journal of Clinical Pharmacy
• /
• v.21 no.3
• /
• pp.249-255
• /
• 2011

Objective: To examine the drug use (prescribing) pattern of serious drug-drug interactions (DDIs, contraindicated drug interactions) using real world data. Prescription patterns were examined in terms of dispensing types. Method: Retrospective drug utilization review (DUR) study was performed. One hundred and six datasets of serious DDIs (DDI pairs) were determined among DDI datasets that Ministry of Health & Welfare announced for the DUR system from 2004 to 2005. Electronically transacted ambulatory patients' prescription database to Health Insurance Assessment and Review Services (HIRA) from July, 2005 to June, 2006 was collected with personal information deidentified and analyzed in terms of types of dispensing as a contributing factor. Results: After prescription data analysis per each patient, total number of DDI cases using 95 DDI pairs was 5,511, which accounted for 2.6 cases per patients. DDI cases between two drugs from each of community pharmacy dispensing- type prescription were considerable (63% vs. 24% in those from each of in-institutional dispensing-type prescription and vs. 13% in those from a community pharmacy dispensing-type prescription and an in-institutional dispensingtype prescription). Conclusions: DDI cases from different prescribers were found to be significant. Thus, the concurrent DUR process between prescriptions from different physicians and institutions should be implemented for the safe drug use.

• Biotechnology and Bioprocess Engineering:BBE
• /
• v.6 no.5
• /
• pp.326-331
• /
• 2001

With the aim of developing of pH-sensitive controlled drug release system, a poly(Llysine) (PLL) based cationic semi-interpenetrating polymer network (semi-IPN) has been synthesized. This cationic hydrogel was designed to swell at lower pH and de-swell at higher pH and therefore be applicable for achieving regulated drug release at a specific pH range. In addition to the pH sensitivity, this hydrogel was anticipated to interact with an ionic drug, providing another means to regulate the release rate of ionic drugs. This semi-IPN hydrogel was prepared using a free-radical polymerization method and by crosslinking of the polyethylene glycol (PEG)-methacrylate polymer through the PLL network. The two polymers were penetrated with each other via interpolymer complexation to yield the semi-IPN structures. The PLL hydrogel thus prepared showed dynamic swelling/de-swelling behavior in response to pH change, and such a behavior was influenced by both the concentrations of PLL and PEG-methacrylate. Drug release from this semi-IPN hydrogel was also investigated using a model protein drug, streptokinase. Streptokinase release was found to be dependent on its ionic interaction with the PLL backbones as well as on the swelling of the semi-IPN hydrogel. These results suggest that a PLL semi-IPN hydrogel could potentially be used as a drug delivery platform to modulate drug release by pH-sensitivity and ionic interaction.

• Biomolecules & Therapeutics
• /
• v.17 no.3
• /
• pp.299-304
• /
• 2009

Rosiglitazone maleate (RGM) is widely used for improving insulin resistance. RGM is a moderate inhibitor of cytochrome P450 2C8 (CYP2C8) and is also mainly metabolized by CYP2C8. The aim of this study was to determine whether the effect of RGM on CYP2C8 is altered by co-treatment with other drugs, and whether amlodipine camsylate (AC) changes the pharmacokinetics (PK) of RGM. Of the 11 drugs that are likely to be co-administered with RGM in diabetic patients, seven drugs lowered the $IC_{50}$ value of RGM on CYP2C8 by more than 80%. In vitro CYP2C8 inhibitory assays of RGM in combination with drugs of interest showed that the $IC_{50}$ of RGM was decreased by 98.9% by AC. In a pharmacokinetic study, Sprague-Dawley (SD) rats were orally administered 1 mg/kg of RGM following by single or 10-consecutive daily administrations of 1.5 mg/kg/day of AC. No significant changes in the pharmacokinetic parameters of RGM were observed after a single administration of AC, but the AUC and $C_{max}$ values of RGM were significantly reduced by 36% and 31%, respectively, by multiple administrations of AC. In conclusion, RGM was found to be affected by AC by in vitro CYP2C8 inhibition testing, and multiple dosing of AC appreciably changed the pharmacokinetics of RGM. These findings suggest that a drug interaction exists between AC and RGM.

• Korean Journal of Clinical Pharmacy
• /
• v.16 no.2
• /
• pp.155-164
• /
• 2006

Great inter-variability in drug response and adverse drug reactions is related to inter-variability of drug bioavailability, drug interaction and patient's disease and physyological state that cause change in absorption, distribution, metabolism and excretion of drugs. However, these alone do not sufficiently predict and explain inter-variability in drug response. In recent studies, it is reported that inter-variability in drug response and adverse drug reactions may largely resulted from genetically determined differences in drug absoption, distribution, metabolism and drug target proteins. Especially, the major human drug-metabolizing enzymes such as CYP450, N-acetyl tranferase, thiopurine S-methyl transferase, glutathione S-transferase are identified as the major gene variants that cause inter-individual variability in drug's response and adverse drug reactions. These variations may have most significant implications for those drugs that have narrow therapeutic index and serious adverse drug reactions. Therefore, the genetic variation such as polymorphisms in drug metabolizing enzymes can affect the response of individuals to drugs that are used in the treatment of depression, psychosis, cancer, cardiovascular disorders, ulcer and gastrointestinal disorders, pain and epilepsy, among others. This review describes the pharmacogenomics of the drug metabolizing enzymes associated with the drug response and its clinical applications.

• Interdisciplinary Bio Central
• /
• v.5 no.2
• /
• pp.3.1-3.7
• /
• 2013

Recently, the productivity of drug discovery has gradually decreased as the limitations of single-target-based drugs for various and complex diseases become exposed. To overcome these limitations, drug combinations have been proposed, and great efforts have been made to predict efficacious drug combinations by statistical methods using drug databases. However, previous methods which did not take into account biological networks are insufficient for elaborate predictions. Also, increased evidences to support the fact that drug effects are closely related to metabolic enzymes suggested the possibility for a new approach to the study drug combinations. Therefore, in this paper we suggest a novel approach for analyzing drug combinations using a metabolic network in a systematic manner. The influence of a drug on the metabolic network is described using the distance between the drug target and an enzyme. Target-enzyme distances are converted into influence scores, and from these scores we calculated the correlations between drugs. The result shows that the influence score derived from the targetenzyme distance reflects the mechanism of drug action onto the metabolic network properly. In an analysis of the correlation score distribution, efficacious drug combinations tended to have low correlation scores, and this tendency corresponded to the known properties of the drug combinations. These facts suggest that our approach is useful for prediction drug combinations with an advanced understanding of drug mechanisms.