1.Principles of transparency and clinical trial registration.
Translational and Clinical Pharmacology 2017;25(3):113-113
		                        		
		                        			
		                        			No abstract available.
		                        		
		                        		
		                        		
		                        	
3.Erratum: Clearance.
Translational and Clinical Pharmacology 2016;24(3):152-152
		                        		
		                        			
		                        			The third equation on page 44 should be corrected.
		                        		
		                        		
		                        		
		                        	
4.Erratum: R-based reproduction of the estimation process hidden behind NONMEM Part 2: First-order conditional estimation
Translational and Clinical Pharmacology 2018;26(2):99-99
		                        		
		                        			
		                        			The equations on page 162 should be corrected.
		                        		
		                        		
		                        		
		                        	
5.Erratum: Population Pharmacokinetic Analysis of Metformin Administered as Fixed-Dose Combination in Korean Healthy Adults
Suein CHOI ; Sangil JEON ; Seunghoon HAN ; Dong Seok YIM
Translational and Clinical Pharmacology 2018;26(3):143-143
		                        		
		                        			
		                        			In the published version of this article, the contents of Table 1 (‘Demographic characteristics of subjects’) are incorrect.
		                        		
		                        		
		                        		
		                        	
6.Changes of Plasma Components by the Plasma Exchange.
Hyo Jin CHUN ; Jae Ryong KIM ; Gyoung Yim HA ; Dong Seok JEON ; Dal Hyo SONG
Korean Journal of Blood Transfusion 1995;6(2):141-154
		                        		
		                        			
		                        			Therapeutic plasma exchange is used in almost every condition in which there is a plasma factor thought possibly to the etiology or pathogenesis of a disease or one of its manifestations. In order to evaluate plasma exchange using fresh frozen plasma as replacement solution, eighty four therapeutic plasma exchanges were carried out in eighteen patients. In standardized procedures, 1.5 times the calculated plasma volume was replaced with a Hartman's solution and fresh frozen plasma. Anticoagulation was achieved using a whole venous blood to 2.5% trisodium citrate in the ratio of 10 to 1. Total calcium, phosphorus, glucose, urea nitrogen, creatinine, bilirubin, alkaline phosphatase, amylase, creatine kinase, IgG, C3, total white and red blood cell count, hemoglobin, and differential count were not significantly affected by the procedure. In contrast, serum cholesterol, total protein, albumin, aspartate aminotransferase, alanine aminotransferase, ionized calcium, IgM, C4 and platelet were significantly decreased by the plasma exchange. All these measurements had returned to the first pre-exchange level within 24 hours, while the C4 and platelet count took between 24 and 72 hours, and the IgM level, between 72 hours and 1 week. These data indicated that in an isovolemic plasma exchange there was a transient but rapidly reversible effect on all the components studied, with C4 and platelet count, returning more slowly to pre-exchange level than the others, and IgM levels responding the slowest. In summary, plasma exchanges using fresh frozen plasma as replacement solution were assumed to be not significantly affected the function of various organs.
		                        		
		                        		
		                        		
		                        			Alanine Transaminase
		                        			;
		                        		
		                        			Alkaline Phosphatase
		                        			;
		                        		
		                        			Amylases
		                        			;
		                        		
		                        			Aspartate Aminotransferases
		                        			;
		                        		
		                        			Bilirubin
		                        			;
		                        		
		                        			Blood Platelets
		                        			;
		                        		
		                        			Calcium
		                        			;
		                        		
		                        			Cholesterol
		                        			;
		                        		
		                        			Citric Acid
		                        			;
		                        		
		                        			Creatine Kinase
		                        			;
		                        		
		                        			Creatinine
		                        			;
		                        		
		                        			Erythrocyte Count
		                        			;
		                        		
		                        			Glucose
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Immunoglobulin G
		                        			;
		                        		
		                        			Immunoglobulin M
		                        			;
		                        		
		                        			Nitrogen
		                        			;
		                        		
		                        			Phosphorus
		                        			;
		                        		
		                        			Plasma Exchange*
		                        			;
		                        		
		                        			Plasma Volume
		                        			;
		                        		
		                        			Plasma*
		                        			;
		                        		
		                        			Platelet Count
		                        			;
		                        		
		                        			Urea
		                        			
		                        		
		                        	
7.Simulation of the AUC Changes after Generic Substitution in Patients.
Journal of Korean Medical Science 2009;24(1):7-12
		                        		
		                        			
		                        			To address the debate on the safety of generic substitution quantitatively, the author compared the change in AUC in virtual patients who were simulated for several different scenarios of generic substitution. In four scenarios of original (branded) to generic and generic to generic substitution, 5,000 virtual patients were simulated per scenario using the programming software R. The mean population AUC of generics ranged from 90-110% (scenarios A and B) and 80-123.5% (scenarios C and D) of the AUC of the original. Those patients who had an AUC change (ratio) as a result of drug substitution of less than 0.67 or greater than 1.5 were considered to be in potential danger due to the substitution. We found that less than 6% of patients fell outside of the cutoff range of 0.67-1.5 as a result of original to generic substitution. However, in the case of generic to generic substitution, the proportion was as high as 9-12%. This alerts us to the potential danger of generic substitution, especially for drugs with narrow therapeutic indices.
		                        		
		                        		
		                        		
		                        			*Area Under Curve
		                        			;
		                        		
		                        			Attitude to Health
		                        			;
		                        		
		                        			Computer Simulation
		                        			;
		                        		
		                        			Drug Prescriptions
		                        			;
		                        		
		                        			Drugs, Generic/*pharmacokinetics/therapeutic use
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Patients/psychology/statistics & numerical data
		                        			;
		                        		
		                        			Software
		                        			;
		                        		
		                        			Therapeutic Equivalency
		                        			
		                        		
		                        	
8.Clearance.
Translational and Clinical Pharmacology 2015;23(2):42-45
		                        		
		                        			
		                        			This tutorial deals with basic concepts of clearance, the most important parameter in pharmacokinetics but often challenging for students in clinical pharmacology. Its relationships with dose, concentration and elimination rate are discussed using a physical model and examples of commonly used drugs, as well as its physiological aspects pertaining to the blood flow to differing organs. Finally, application of clearance to the calculation of maintenance dose rate and half-life is used to show how it is essential in pharmacotherapy and clinical pharmacology.
		                        		
		                        		
		                        		
		                        			Drug Therapy
		                        			;
		                        		
		                        			Half-Life
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Pharmacokinetics
		                        			;
		                        		
		                        			Pharmacology, Clinical
		                        			
		                        		
		                        	
9.Current state of clinical trials in Korea.
Journal of the Korean Medical Association 2010;53(9):745-752
		                        		
		                        			
		                        			The number of clinical trials sponsored by global pharmaceutical companies performed in countries other than the U.S. and Western Europe has been steadily increasing over the past decade. Among those emerging countries, Korea deserves attention for its rapid growth in the number of trials and sites. As of 2009, Korea was ranked the tenth country in the number of clinical trials registered at http://clinicaltrials.gov. This is remarkable growth given that it was not included in the top 30 countries in 2005. High population density, qualified medical professionals, regulatory changes including Investigational New Drug-New Drug Application (IND/NDA) separation, acceptance of International Conferences on Harmonization-Good Clinical Practices (ICH-GCP) by Korea Food&Drug Administration (KFDA), and governmental policies to boost clinical trials were the most influential factors that caused such an outstanding achievement. The Korean National Enterprise for Clinical Trials (KoNECT), an organization founded to lead initiatives to improve the milieu for clinical trials, has been playing a pivotal role in the steering of 15 regional clinical centers designated by the government. Based upon improvements in infrastructure so far, diversity in therapeutic areas and the proportion of early phase trials are expected to grow. Korea has grown to be one of the major countries in the clinical trial market, which was made possible by the cooperation of industry, academia and government. Further investment and efforts to solve current challenges will allow such growth to continue into the next decade.
		                        		
		                        		
		                        		
		                        			Achievement
		                        			;
		                        		
		                        			Congresses as Topic
		                        			;
		                        		
		                        			Europe
		                        			;
		                        		
		                        			Investments
		                        			;
		                        		
		                        			Korea
		                        			;
		                        		
		                        			Population Density
		                        			
		                        		
		                        	
10.Analysis of 107 cases of chromosomal abnormalities.
Young Jae KIM ; Hyo Jin CHUN ; Dong Seok JEON ; Jae Ryong KIM ; Gyoung Yim HA
Korean Journal of Clinical Pathology 1992;12(4):513-522
		                        		
		                        			
		                        			No abstract available.
		                        		
		                        		
		                        		
		                        			Chromosome Aberrations*
		                        			
		                        		
		                        	
 
            
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