ABSTRACT
An extended-release (ER) fixed-dose combination (FDC) of tramadol 37.5 mg/acetaminophen 325 mg was developed due to the demand for varying dosages. This study aimed to evaluate the pharmacokinetics (PKs) for two tablets of the new developed tramadol 37.5 mg/acetaminophen 325 mg ER FDC (DW-0920, Wontran Semi ER®) as test formulation compared to one tablet of the tramadol 75 mg/acetaminophen 650 mg ER FDC (DW-0919, Wontran ER®) as reference formulation. A randomized, open-label, 2-way crossover study was conducted in 30 healthy subjects. Subjects were orally administered one of 2 formulations followed by an alternate formulation with a 7-day washout period. Blood samples were collected up to 36 hours post-dose. Plasma concentrations of tramadol and acetaminophen were determined using a validated high-performance liquid chromatography with tandem mass spectrometric method. The geometric mean ratios (GMRs) and their 90% confidence intervals (90% CIs) of test formulation to reference formulation were calculated for the maximum plasma concentration (Cmax) and the area under the plasma concentration-time curve from zero to the last measurable time point (AUClast). The PK profiles of 2 formulations were comparable. The GMRs (90% CI) of Cmax and AUClast for tramadol were 1.086 (1.047–1.127) and 1.008 (0.975–1.042), respectively. The corresponding values for acetaminophen were 0.956 (0.897–1.019) and 0.986 (0.961–1.011), respectively. All the values were within the bioequivalence range of 0.80–1.25. Two tablets of DW-0920 were comparable to one tablet of DW-0919. The DW-0920 may be used for optimal pharmacotherapy for pain control with a lower dose.
ABSTRACT
Genetic polymorphisms of enzymes and transporters associated with the absorption, distribution, metabolism, and elimination (ADME) of drugs are one of the major factors that contribute to interindividual variations in drug response. In the present study, we aimed to elucidate the pharmacogenetic profiles of the Korean population using the Affymetrix Drug Metabolizing Enzyme and Transporters (DMET™) platform. A total of 1,012 whole blood samples collected from Korean subjects were genotyped using the DMET™ plus microarray. In total, 1,785 single nucleotide polymorphism (SNP) markers for 231 ADME genes were identified. The genotype and phenotype of 13 clinically important ADME genes implemented in the Clinical Pharmacogenetics Implementation Consortium guidelines were compared among different ethnic groups. Overall, the genotype frequencies of the Korean population were similar to those of the East Asian population. Several genes, notably CYP2C19 and VKORC1, showed marked differences in Koreans compared to Europeans (EURs) or Africans (AFRs). The percentage of CYP2C19 poor metabolizers was 15% in Koreans and less than 3% in EURs or AFRs. The frequencies of causative SNPs of the VKORC1 gene for the low warfarin dose phenotype were 90%, 60%, and 10% in Koreans, EURs and AFRs, respectively. Our findings can be utilized for optimal pharmacotherapy in Korean patients.
ABSTRACT
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 (Cmax ) and area under the curve until the last measurable time point (AUClast ) 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 Cmax and 1.0167 (0.9347–1.1059), 0.9575 (0.9317–0.9841), and 1.0561 (1.0170–1.0967) for AUClast , 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.
ABSTRACT
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.
ABSTRACT
Sulfonylurea (SU) and dipeptidyl peptidase-4 (DPP-4) inhibitors are most common secondary agents that are added to metformin monotherapy. Real-world studies have become increasingly important in providing evidence of treatment effectiveness in clinical practice and real-world data could help appropriate therapeutic information. Therefore, this study aims to compare the glycemic effectiveness of SU and DPP-4 inhibitors, which are added to metformin monotherapy in real clinical practice using electronic medical record (EMR) data. EMR data of type 2 diabetes patients treated at Seoul National University Hospital from December 2002 to December 2012 were retrieved and analyzed. The patients were divided into three groups: patients who maintained metformin monotherapy (M), and patients who added SU (MS) or DPP-4 inhibitors (MD) to metformin monotherapy. The mean change in HbA1c level, the proportion of patients achieving the HbA1c target < 7.0%, proportion of patients with treatment failure, and probability of treatment failure occurrence and changes in prescription were evaluated to compare glycemic control efficacy between SU and DPP-4 inhibitors. The MS showed significantly greater reduction in the Hb1Ac level than MD. The proportion of patients achieving HbA1c < 7.0% is higher in MD, whereas the proportion of patients with treatment failure was greater in MS. The probability of the treatment failure and probability of changes in the prescription were lower in MD than MS with hazard ratio of 0.499 and 0.579, respectively. In conclusion, this real-world study suggested that DPP-4 inhibitors are expected to show more durable glycemic control efficacy than SU in long-term use.
ABSTRACT
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.
ABSTRACT
Sulfonylurea (SU) and dipeptidyl peptidase-4 (DPP-4) inhibitors are most common secondary agents that are added to metformin monotherapy. Real-world studies have become increasingly important in providing evidence of treatment effectiveness in clinical practice and real-world data could help appropriate therapeutic information. Therefore, this study aims to compare the glycemic effectiveness of SU and DPP-4 inhibitors, which are added to metformin monotherapy in real clinical practice using electronic medical record (EMR) data. EMR data of type 2 diabetes patients treated at Seoul National University Hospital from December 2002 to December 2012 were retrieved and analyzed. The patients were divided into three groups: patients who maintained metformin monotherapy (M), and patients who added SU (MS) or DPP-4 inhibitors (MD) to metformin monotherapy. The mean change in HbA1c level, the proportion of patients achieving the HbA1c target < 7.0%, proportion of patients with treatment failure, and probability of treatment failure occurrence and changes in prescription were evaluated to compare glycemic control efficacy between SU and DPP-4 inhibitors. The MS showed significantly greater reduction in the Hb1Ac level than MD. The proportion of patients achieving HbA1c < 7.0% is higher in MD, whereas the proportion of patients with treatment failure was greater in MS. The probability of the treatment failure and probability of changes in the prescription were lower in MD than MS with hazard ratio of 0.499 and 0.579, respectively. In conclusion, this real-world study suggested that DPP-4 inhibitors are expected to show more durable glycemic control efficacy than SU in long-term use.
ABSTRACT
Combination therapies of antihypertensive drugs are recommended in cases where hypertension is not controlled by monotherapy. This study aimed to compare the pharmacokinetics (PKs) between fixed-dose combination (FDC) of fimasartan/amlodipine 60/10 mg and the corresponding loose combination. Because of the high intra-subject variability for maximum plasma concentration (C(max)) of fimasartan, a randomized, open-label, 3×3 partial replicated crossover design was adopted. Subjects received a single dose of FDC of fimasartan/amlodipine 60/10 mg or the corresponding loose combination in each period. Blood samples for PK analysis were collected up to 48 hours for fimasartan and 144 hours for amlodipine, respectively. Geometric mean ratios (GMRs) and its 90% confidence intervals (CIs) of the FDC to the loose combination for C(max) and area under the concentration-time curve from time 0 to the last quantifiable time point (AUC(last)) were calculated. Sixty healthy subjects were randomized, and 57 subjects completed the study. The concentration-time profiles of fimasartan and amlodipine were similar between the FDC and loose combination. The GMRs (90% CIs) of the FDC to the loose combination for C(max) and AUC(last) were 1.0440 (0.9202–1.1844) and 1.0412 (0.9775–1.1090) for fimasartan, and 1.0430 (1.0156–1.0711) and 1.0339 (1.0055–1.0631) for amlodipine, respectively. The GMRs and its 90% CIs for C(max) and AUC(last) of fimasartan and amlodipine were included not only in the scaled bioequivalence criteria but also in the conventional bioequivalence criteria. In conclusion, FDC of fimasartan/amlodipine 60/10 mg showed comparable PK profiles with the corresponding loose combination, which suggests their bioequivalence.
Subject(s)
Amlodipine , Antihypertensive Agents , Cross-Over Studies , Healthy Volunteers , Hypertension , Pharmacokinetics , Plasma , Therapeutic EquivalencyABSTRACT
BACKGROUND: The left internal thoracic artery (LITA) has been used as the first conduit of choice in coronary artery bypass grafting (CABG) because of excellent long-term patency and outcomes. However, no studies have examined substances other than nitric oxide that could be beneficial for the bypass conduit, native coronary artery or ischemic myocardium. This study was conducted to evaluate differences in metabolic profiles between the LITA and ascending aorta using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS). METHODS: Twenty patients who underwent CABG using the LITA were prospectively enrolled. Plasma samples were collected simultaneously from the LITA and ascending aorta. GC-TOF-MS based untargeted metabolomic analyses were performed and a 2-step volcano plot analysis was used to identify distinguishable markers from two plasma metabolome profiles. Semi-quantitative and quantitative analyses were performed using GC-TOF-MS and enzyme-linked immunosorbent assay, respectively, after selecting target metabolites based on the metabolite set enrichment analysis. RESULTS: Initial volcano plot analysis demonstrated 5 possible markers among 851 peaks detected. The final analysis demonstrated that the L-cysteine peak was significantly higher in the LITA than in the ascending aorta (fold change = 1.86). The concentrations of intermediate metabolites such as L-cysteine, L-methionine and L-cystine in the ‘cysteine and methionine metabolism pathway' were significantly higher in the LITA than in the ascending aorta (2.0-, 1.4- and 1.2-fold, respectively). Quantitative analysis showed that the concentration of hydrogen sulfide (H2S) was significantly higher in the LITA. CONCLUSION: The plasma metabolome profiles of the LITA and ascending aorta were different, particularly higher plasma concentrations of L-cysteine and H2S in the LITA.
Subject(s)
Humans , Aorta , Chromatography, Gas , Coronary Artery Bypass , Coronary Vessels , Cysteine , Cystine , Enzyme-Linked Immunosorbent Assay , Hydrogen Sulfide , Mammary Arteries , Mass Spectrometry , Metabolism , Metabolome , Metabolomics , Methionine , Myocardium , Nitric Oxide , Plasma , Prospective Studies , Spectrum AnalysisABSTRACT
PURPOSE: Human leukocyte antigen (HLA) has been recognized as the most important genetic risk factor for severe cutaneous adverse drug reactions (SCARs) caused by certain drugs. However, cumulated observations suggest the presence of genetic risk factors for SCARs other than drug-specific HLA. We aimed to identify a common genetic risk factor of SCARs across multiple drugs. METHODS: We performed 2 independent genome-wide association studies (GWASs). A total of 68 and 38 subjects with a diagnosis of SCAR were enrolled in each GWAS. Their allele frequencies were compared to those of healthy subjects in Korea. RESULTS: No single nucleotide polymorphism (SNP) with genome-wide significance was found in either GWAS. We next selected and annotated the 200 top-ranked SNPs from each GWAS. These 2 sets of annotated genes were then entered into the web interface of ConsensusPathDB for a pathway-level analysis. The Fas signaling pathway was significantly over-represented in each gene set from the 2 GWASs. CONCLUSIONS: Our observations suggest that the Fas signaling pathway may be a common genetic risk factor for SCARs across multiple drugs.
Subject(s)
Humans , Cicatrix , Diagnosis , Drug-Related Side Effects and Adverse Reactions , Gene Frequency , Genome-Wide Association Study , Healthy Volunteers , Korea , Leukocytes , Polymorphism, Single Nucleotide , Risk Factors , Stevens-Johnson SyndromeABSTRACT
BACKGROUND: The renal function of individuals is one of the reasons for the variations in therapeutic response to various drugs. Patients with renal impairment are often exposed to drug toxicity, even with drugs that are usually eliminated by hepatic metabolism. Previous study has reported an increased plasma concentration of indoxyl sulfate and decreased plasma concentration of 4β-hydroxy (OH)-cholesterol in stable kidney transplant recipients, implicating indoxyl sulfate as a cytochrome P450 (CYP) inhibiting factor. In this study, we aimed to evaluate the impact of renal impairment severity-dependent accumulation of indoxyl sulfate on hepatic CYP3A activity using metabolic markers. METHODS: Sixty-six subjects were enrolled in this study; based on estimated glomerular filtration rate (eGFR), they were classified as having mild, moderate, or severe renal impairment. The plasma concentration of indoxyl sulfate was quantified using liquid chromatography-mass spectrometry (LC-MS). Urinary and plasma markers (6β-OH-cortisol/cortisol, 6β-OH-cortisone/cortisone, 4β-OH-cholesterol) for hepatic CYP3A activity were quantified using gas chromatography-mass spectrometry (GC-MS). The total plasma concentration of cholesterol was measured using the enzymatic colorimetric assay to calculate the 4β-OH-cholesterol/cholesterol ratio. The correlation between variables was assessed using Pearson's correlation test. RESULTS: There was a significant negative correlation between MDRD eGFR and indoxyl sulfate levels. The levels of urinary 6β-OH-cortisol/cortisol and 6β-OH-cortisone/cortisone as well as plasma 4β-OH-cholesterol and 4β-OH-cholesterol/cholesterol were not correlated with MDRD eGFR and the plasma concentration of indoxyl sulfate. CONCLUSION: Hepatic CYP3A activity may not be affected by renal impairment-induced accumulation of plasma indoxyl sulfate.
Subject(s)
Humans , Cholesterol , Cytochrome P-450 CYP3A , Cytochrome P-450 Enzyme System , Cytochromes , Drug-Related Side Effects and Adverse Reactions , Gas Chromatography-Mass Spectrometry , Glomerular Filtration Rate , Indican , Kidney , Metabolism , Plasma , Spectrum Analysis , Transplant RecipientsABSTRACT
Because bioequivalence studies are performed using a crossover design, information on the intra-subject coefficient of variation (intra-CV) for pharmacokinetic measures is needed when determining the sample size. However, calculated intra-CVs based on bioequivalence results of identical generic drugs produce different estimates. In this study, we collected bioequivalence results using public resources from the Ministry of Food and Drug Safety (MFDS) and calculated the intra-CVs of various generics. For the generics with multiple bioequivalence results, pooled intra-CVs were calculated. The estimated intra-CVs of 142 bioequivalence studies were 14.7±8.2% for AUC and 21.7±8.8% for Cmax. Intra-CVs of Cmax were larger than those of area under the concentration-time curve (AUC) in 129 studies (90.8%). For the 26 generics with multiple bioequivalence results, the coefficients of variation of intra-CVs between identical generics (mean±sd (min ~ max)) were 38.0±24.4% (1.9 ~ 105.3%) for AUC and 27.9±18.2% (4.0 ~ 70.1%) for Cmax. These results suggest that substantial variation exists among the bioequivalence results of identical generics. In this study, we presented the intra-CVs of various generics with their pooled intra-CVs. The estimated intra-CVs calculated in this study will provide useful information for planning future bioequivalence studies. (This is republication of the article 'Transl Clin Pharmacol 2017;25:179-182' retracted from critical typographic errors. See the 'Retraction and Republication section of this issue for further information)
Subject(s)
Area Under Curve , Cross-Over Studies , Drugs, Generic , Sample Size , Therapeutic EquivalencyABSTRACT
The retraction has been agreed upon due to critical typographical errors throughout the contents from accidents at the manuscript editing step.
ABSTRACT
In this report, we present a case study of how pharmacogenomics and pharmacometabolomics can be useful to characterize safety and pharmacokinetic profiles in early phase new drug development clinical trials. During conducting a first-in-human trial for a new molecular entity, we were able to determine the mechanism of dichotomized variability in plasma drug concentrations, which appeared closely related to adverse drug reactions (ADRs) through integrated omics analysis. The pharmacogenomics screening was performed from whole blood samples using the Affymetrix DMET (Drug-Metabolizing Enzymes and Transporters) Plus microarray, and confirmation of genetic variants was performed using real-time polymerase chain reaction. Metabolomics profiling was performed from plasma samples using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. A GSTM1 null polymorphism was identified in pharmacogenomics test and the drug concentrations was higher in GSTM1 null subjects than GSTM1 functional subjects. The apparent drug clearance was 13-fold lower in GSTM1 null subjects than GSTM1 functional subjects (p < 0.001). By metabolomics analysis, we identified that the study drug was metabolized by cysteinylglycine conjugation in GSTM functional subjects but those not in GSTM1 null subjects. The incidence rate and the severity of ADRs were higher in the GSTM1 null subjects than the GSTM1 functional subjects. Through the integrated omics analysis, we could understand the mechanism of inter-individual variability in drug exposure and in adverse response. In conclusion, integrated multi-omics analysis can be useful for elucidating the various characteristics of new drug candidates in early phase clinical trials.
Subject(s)
Chromatography, Liquid , Drug-Related Side Effects and Adverse Reactions , Incidence , Mass Screening , Mass Spectrometry , Metabolomics , Pharmacogenetics , Plasma , Real-Time Polymerase Chain ReactionABSTRACT
BACKGROUND/AIMS: Concerns that proton pump inhibitors (PPIs) diminish the efficacy of clopidogrel could hamper the appropriate prescription of PPIs. We evaluated the influence of pantoprazole on the antiplatelet effect of clopidogrel compared with ranitidine, which is regarded as safe, after stratification of the population according to the presence of a cytochrome (CYP) 2C19 polymorphism in Korea. METHODS: Forty patients who underwent dual antiplatelet therapy were randomized to receive pantoprazole (n=20) or ranitidine (n=20). Platelet aggregation was evaluated by impedance aggregometry at baseline (D0) and 8 days after acid-lowering treatments (D9). CYP2C19 was genotyped by polymerase chain reaction restriction fragment length polymorphism. RESULTS: After co-treatment, the percentage of clopidogrel low-response was 11.1% (2/18) in the pantoprazole group and 10.5% (2/19) in the ranitidine group (p=0.954). The impedance values with adenosine diphosphate stimulus after acid-lowering treatments did not significantly differ between the two groups. In a multiple regression analysis, only ST-elevation myocardial infarction was marginally associated with a reduced antiplatelet effect (odds ratio, 12.07; 95% confidence interval, 0.84 to 173.78). However, pantoprazole use did not affect the antiplatelet effect after correction for the CYP2C19 polymorphism. CONCLUSIONS: This study showed that pantoprazole does not increase platelet aggregation in patients receiving dual antiplatelet therapy (ClinicalTrials.gov number: NCT02733640).
Subject(s)
Humans , Adenosine Diphosphate , Cytochrome P-450 CYP2C19 , Cytochromes , Drug Interactions , Electric Impedance , Korea , Myocardial Infarction , Platelet Aggregation , Polymerase Chain Reaction , Polymorphism, Restriction Fragment Length , Prescriptions , Proton Pump Inhibitors , RanitidineABSTRACT
The aim of this study was to examine the effects of CYP2C19*2 and *3 genetic polymorphisms on omeprazole pharmacokinetic (PK) and pharmacodynamic (PD) responses. Twenty-four healthy Korean volunteers were enrolled and given 20 mg omeprazole orally once daily for 8 days. The genotypes of CYP2C19 single nucleotide polymorphisms (SNPs) (*2, *3, and *17) were screened. The plasma concentrations of omeprazole, omeprazole sulfone, and 5-hydroxy (5-OH) omeprazole were determined by liquid chromatography with tandem mass spectrometry (LC-MS/MS). The noncompartmental method was used for the determination of PK parameters. Change of mean pH and proportion (%) of time of gastric pH above 4.0 were estimated. The poor metabolizer (PM) group had the lowest metabolic ratio and exhibited the highest area under the curve (AUC) for omeprazole among the CYP2C19 phenotype groups. The PM group showed the greatest change of mean pH and the highest % time of gastric pH above 4.0. The relationship between AUC of omeprazole and % time of gastric pH above 4.0 was confirmed. The study demonstrates that CYP2C19*2 and *3 influence the PKs and PDs of omeprazole in Korean healthy volunteers. Clinical trial registry at the U.S. National Institutes of Health (https://clinicaltrials.gov), number NCT02299687.
Subject(s)
Area Under Curve , Chromatography, Liquid , Cytochrome P-450 CYP2C19 , Genotype , Healthy Volunteers , Hydrogen-Ion Concentration , Methods , Omeprazole , Phenotype , Plasma , Polymorphism, Genetic , Polymorphism, Single Nucleotide , Tandem Mass Spectrometry , VolunteersABSTRACT
Because bioequivalence studies are performed using a crossover design, information on the intra-subject coefficient of variation (intra-CV) for pharmacokinetic measures is needed when determining the sample size. However, calculated intra-CVs based on bioequivalence results of identical generic drugs produce different estimates. In this study, we collected bioequivalence results using public resources from the Ministry of Food and Drug Safety (MFDS) and calculated the intra-CVs of various generics. For the generics with multiple bioequivalence results, pooled intra-CVs were calculated. The estimated intra-CVs of 142 bioequivalence studies were 14.7±8.2% for AUC and 21.7±8.8% for C(max). Intra-CVs of C(max) were larger than those of area under the concentration-time curve (AUC) in 129 studies (90.8%). For the 26 generics with multiple bioequivalence results, the coefficients of variation of intra-CVs between identical generics (mean±sd (min ~ max)) were 38.0±24.4% (1.9 ~ 105.3%) for AUC and 27.9±18.2 % (4.0 ~ 70.1%) for C(max). These results suggest that substantial variation exists among the bioequivalence results of identical generics. In this study, we presented the intra-CVs of various generics with their pooled intra-CVs. The estimated intra-CVs calculated in this study will provide useful information for planning future bioequivalence studies.
Subject(s)
Area Under Curve , Cross-Over Studies , Drugs, Generic , Sample Size , Therapeutic EquivalencyABSTRACT
Diuretic therapy for the treatment of edema in patients with end-stage renal disease (ESRD) is unsatisfactory, and a combination of thiazide and loop diuretics may produce better clinical effects. To evaluate the influence of thiazide on loop diuretic therapy for ESRD, we performed a crossover study of furosemide versus hydrochlorothiazide plus furosemide treatment. The diuretic effects of furosemide (160 mg i.v.) alone versus a combination of hydrochlorothiazide (100 mg p.o.) and furosemide were studied in ten ESRD patients with proteinuria greater than 1 g/day. The diuretic effects were compared for 24 h urine volume and electrolyte excretion. To detect the influence of thiazide that may have been obscured in the widely dispersed data, pharmacodynamic analysis of urine furosemide excretion rate versus fractional excretion of sodium (FeNa) was also performed using mixed-effect modeling. Combination therapy was not significantly different from furosemide monotherapy in terms of 24 h urine volume, chloride, or sodium excretion. Hydrochlorothiazide was not a significant covariate in the furosemide effect for the pharmacodynamic model. In patients with ESRD and severe proteinuria (>1,000 mg/day), the combination of hydrochlorothiazide with furosemide therapy did not increase the diuretic effect of furosemide.