건강 자원자와 고혈압 환자에서 fimasartan의 집단 약동학 연구

학위논문 (석사)-- 서울대학교 융합과학기술대학원 융합과학부, 2017. 8. Lee, Hyeong Ki.Introduction: Fimasartan is a newly developed antihypertensive agent that selectively blocks the type 1 angiotensin II receptor. The objectives of this study were to develop a population pharmacokinetic (PK) model of fimasartan and to identify significant covariates that may affect the population PK parameters in healthy subjects and patients with hypertension. Method: A total of 3,978 fimasartan plasma concentrations were obtained from 268 subjects enrolled in 11 clinical trials including a first-in-human study, drug-interaction studies, and a proof-of-concept dose-response study. A population PK model was developed using nonlinear mixed-effects modeling analysis methods implemented in NONMEM (ver. 7.40). The iterative-two stage, Stochastic Approximation Expectation-Maximization and Monte-Carlo Importance Sampling assisted by mode a posteriori estimation with mu-referencing were implemented, which was followed by model qualification using goodness of fit plots and visual predictive checks (VPCs). Results: A two-compartment linear model with mixed absorption (zero- + first-order), lag time and first-order elimination adequately described plasma fimasartan concentration. A proportional error models were used to account for remained intra-subject variability. The typical values of population PK parameters (inter-individual variability, CV%) of apparent clearance, apparent central volume of distribution, and fraction absorbed via first-order process was 159 L/h (53.7%), 371 L (71.8%), and 0.367 (114.6%). Covariates such as body weight and age were included in the model. Model evaluation by goodness of fit plots and VPCs suggested that the proposed model was adequate and robust with good precision. Discussion: The final population PK model adequately described the observed plasma concentration of fimasartan in various population groups. Body weight and hepatic impairment status were selected as significant covariate of the final population PK model for fimasartan.INTRODUCTION 1 METHODS 4 CLINICAL TRIALS AND SUBJECTS 4 POPULATION PHARMACOKINETIC ANALYSIS 8 Population pharmacokinetic model development 8 Population pharmacokinetic model evaluation 18 RESULT 19 DEMOGRAPHIC CHARACTERISTIC 19 POPULATION PHARMACOKINETIC ANALYSIS 22 MODEL EVALUATION 28 DISCUSSION 34 CONCLUSION 38 REFERENCE 39 APPENDICES 42 ABSTRACT IN KOREAN 76Maste

반도체 배선용 저유전 물질에서 구리 확산에 대한 전기적, 기계적 특성 평가

학위논문(석사)--서울대학교 대학원 :재료공학부,2004.Maste

저선량 방사선 피폭에 따른 인체위해도 평가를 위한 동물실험자료의 알로메트릭 스케일링 연구

학위논문(석사)--서울대학교 대학원 :공과대학 에너지시스템공학부,2020. 2. 김은희.사람에 대한 고선량 방사선 피폭 효과는 비교적 잘 정립되어 있는 반면, 저선량 방사선 피폭에 대해서는 여전히 논란이 많다. DDREF 도출과 같은 저선량 방사선에 대한 분석은 주로 역학 연구에 의해 진행되어왔는데, 역학 연구는 정확한 피폭 선량을 알기 어렵고 배경 위험도에 비해 방사선 피폭으로 인한 위험도 증가 정도가 작기 때문에 정확한 분석을 알기 어렵다는 내재적 단점이 있다. 이러한 이유로, 역학 연구를 보완하기 위해 동물과 세포에 대한 방사선 피폭 실험이 진행되어왔다. BEIR VII과 같은 여러 연구에서 사람에 대한 역학조사와 동물실험 자료를 바탕으로 저선량 방사선에 대한 연구가 진행되어 왔다. 이와 같은 연구들은 동물과 사람에 대해 같은 선량 기준을 가지고 분석을 진행하였다. 하지만, 일부 연구에 따르면 방사선으로 인한 사람의 반응과 다른 종의 반응이 다를 가능성이 있기에 이를 같은 기준으로 적용시키는 것이 옳지 않을 것으로 보인다. 이와 유사하게 화학물질에 대한 독성의 종 특이성은 오랜 기간 연구되어 왔고, 이는 알로메트리와 같은 방식으로 비교적 잘 정립 되어있다. 본 연구에서 알로메트리를 이용하여 새로운 선량 스케일링 방법을 제안하고 검증하고자 하였으며, 이 과정에서 BEIR VII의 방법을 사용하여 ERA와 Janus의 쥐 피폭 데이터를 분석하였다.‘¾법칙’을 사용하여 사람에 대한 0~1.5 Gy의 선량 범위에 해당하는 쥐의 선량 범위로 0~11 Gy를 선택하고 분석을 진행하였다. 이와 같은 새로운 선량 범위의 분석에서 LQ모델이 선형모델보다 더 반응을 잘 설명하였고, 분석결과와 도출된 DDREF의 분포가 사람의 것과 유사한 결과를 보였다. 이러한 점을 고려하여, 사람에게 적용되는 선량 기준을 동물 노출 데이터에 그대로 적용시키기 보다는 각 종의 특성에 근거하여 다른 선량 기준을 적용 시켜야 더 정확한 결과를 얻을 수 있을 것으로 생각되고, 그 기준으로 각 종별 무게의 차이를 이용하는 것이 하나의 선택지가 될 수 있을 것이라고 생각한다.While the effect of high dose radiation on humans is well established, the effect of low dose radiation is still controversial. This analysis such as the derivation of DDREF is conducted mainly on epidemiological studies. However, since epidemiological analysis has inherent flaws that it is hard to know the exact exposed dose. Moreover, the increased risk with low dose radiation is hard to be distinguished because of the low increase of risk compared to the background risk. For these reasons, additional radiation exposure experiments to cells and animals have been conducted to supplement epidemiological investigations. Several studies on low dose radiation such as BEIR VII were conducted with human epidemiology and animal studies. These studies analyzed different sources with the same dose scale to derive DDREF. However, some studies indicate that the reaction of humans from radiation is different from that of other species. Species specificity of toxic chemicals has been studied for a long time and it is relatively well established by the name of allometry. In this study, I suggested and verified a new dose scaling method with reflecting the difference in the weight of the animal species and conducted an analysis of mouse exposure data from ERA and Janus using BEIR VII's method. With the allometric method, the new dose range for the mouse that I used as a corresponding dose range of 0-1.5 Gy for the human is 0-11Gy based on'3/4 Rule'. Radiation exposure data of mouse in the dose range of 0-11Gy fits better on the LQ model than the linear model. Besides, the tendency of the results and derived DDREF distributions showed similar to those of humans. In view of these points, it is thought that the dose standard applied to humans should not be applied to animal exposure data and allometric scaling methods from weight comparison would be a good option for the application of animal radiation exposure data to humans.Chapter 1 Introduction 1 Chapter 2 Backgrounds and advance studies 3 2.1 Backgrounds 3 2.1.1 Risk models of low dose radiation exposure 3 2.1.2 Linear quadratic model & DDREF 6 2.1.3 Derivation of DDREF 10 2.2 Advance sutdies 12 2.2.1 DDREF derivation from various human epidemiological data: Kocher et al. 12 2.2.2 DDREF derivation from various human epidemiological data and animal studies: BEIR VII 15 2.2.3 Radiation animal studies 17 2.2.4 Equivalent dose across animal species: Chemical Toxin 19 2.2.5 Equivalent dose across animal species: Radiation 20 Chapter 3 Methods 21 3.1 BEIR VII’s LQ model 21 3.2 Selection of dose range 24 3.3 Selection of data 25 3.4 Kocher et al.’s DDREF derivation 27 Chapter 4 Results 30 4.1 Fitting experiment data up to 11 Gy 30 4.1.1 BEIR VII’s LQ model 30 4.1.2 Linear model 30 4.2 Fitting experiment data up to 1.5 Gy 36 4.2.1 BEIR VII’s LQ model 36 4.2.2 Linear model 36 Chapter 5 Discussion 41 5.1 Grounds for change of dose range 41 5.1.1 Possible reason for poor regression of the LQ model in the dose range of 0-1.5 Gy 41 5.1.2 Advantages of the LQ model over the linear model for explanation of the results: Qualitative advantages 42 5.1.3 Advantages of the LQ model over the linear model for explanation of the results: Quantitative advantages 43 5.1.4 Comparison the results with human data 45 5.1.5 Comparison of DDREFs: mouse vs human mortality data 47 5.2 Further studies on animal data 49 Chapter 6 Conclusion 50 Reference 52 국문초록 59Maste

제2언어 습득에서 유형론적 보편성과 유표성의 역할

학위논문(석사)--서울대학교 대학원 :외국어교육과 독어전공,2000.Maste