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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 農藝學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23192
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dc.contributor.advisor劉仁沛
dc.contributor.authorPei-Ying Tsaien
dc.contributor.author蔡蓓瑩zh_TW
dc.date.accessioned2021-06-08T04:46:41Z-
dc.date.copyright2009-07-31
dc.date.issued2009
dc.date.submitted2009-07-30
dc.identifier.citationChow S.C., and J.P. (2008). Design and Analysis of Bioavailability and Bioequivalence Studies, 3th Ed. , CRC/ Chapman and Hall, Taylor and France, New York.
FDA (2001). Guidance on Statistical Approach to Establishing Bioequivalence, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Rockville, MD.
FDA (2003a). Second Draft Guidance on Bioavailability and Bioequivalence Studies for Nasal Aerosols and Nasal Sprays for Local Action, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Rockville, MD.
FDA (2003b). Statistical Information from the June 1999 Draft Guidance and Statistical Information for In Vitro Bioequivalence Data Posted on August 18, 1999, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Rockville, MD.
Graybill, F.A. and Wang, C.M. (1980). Confidence intervals on nonnegative linear combinations of variances. Journal of the American Statistical Association, 75,869–873.
Howe, W.G. (1974). Approximate confidence limit on mean of X+Y where X and Y are two tabled independent random variables. Journal of the American Statistical Association, 69, 789–794.
Hsu, J.C., Hwang, J.T.G., Liu, H.K., and Ruberg, S.J. (1994). Confidence intervals associated with tests for bioequivalence. Biometrika, 81, 103–114.
Hyslop, T., Hsuan, F., and Holder, D.J. (2000). A small sample confidence interval approach to assess individual bioequivalence. Statistics in Medicine, 19, 2885–2897.
Lee, A.F.S. and Fineberg, N.S. (1991). A fitted test for the Behrens–Fisher problem. Communications in Statistics—Theory and Methods, 20, 653–666.
Lee Y.H, Shao J. and Chow S.C. (2004). Modified large-sample confidence intervals for linear combinations of variance components: extension, theory, and application Journal of the American Statistical Association, 99, 467-478.
Ting, N., Burdick, R.K., Graybill, F.A., Jeyaratnam, S., and Lu, T.-F.C. (1990). Confidence intervals on linear combinations of variance components that are unrestricted in sign. Journal of Statistical Computation and Simulation, 35, 135–143.
Yue C.H. (2008). Statistical Evaluation of In Vitro Bioequivalence for Nasal Aerosols and Nasal Sprays for Local Action: Droplet Size Distribution, Master Thesis, National Taiwan University.
MATLAB 7.6.0 (R2008a) (2008). The MathWorks, Inc. Natick, MA, OSA.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23192-
dc.description.abstract由於鼻藥噴霧劑(Nasal aerosols)與鼻腔噴霧器(Nasal sprays)之噴霧藥效皆為局部性作用藥品,不易藉由血液的流動進入人體器官中,因此我們利用藥劑生體可用率(Bioequivalence)與生體相等性(Bioequivalence)的機器實驗來評估兩種藥物的藥效性是否相等。美國食品與藥物管理局(簡稱FDA)(2003b),提出以95%信賴上界來作為比較兩種藥物的生體相等性(Bioequivalence)之標準。Hyslop, Hsuan和Holder首先在2000年將此標準線性化並提出相對應之統計方法。因在評估噴霧器實驗有批次、生命階段與檢體等不同變因,我們根據二階段巢式隨機模式的變方分析之大樣本修正法(MLS)來尋求線性化準則95%信賴上限。最後利用各種樣本數及不同變異數組合下之模擬資料,以經驗型I誤差和經驗檢定力來評估由延伸之變方分析大樣本修正法(MLS)是否能求得一個較佳的95%信賴上界。最後我們以一個實例介紹本方法在實務上之應用。zh_TW
dc.description.abstractFor some locally acting products such as nasal aerosols and nasal sprays that are not intended to be absorbed into the bloodstream, the in vitro bioavailability / bioequivalence studies based on machinery experiments are used to measure that whether the two drug products provide the same therapeutic effect. According to the U.S. Food and Drug Administration (FDA) draft guidance (2003b), the evaluation of the in vitro bioequivalence (BE) between two drug products would be determined by comparing the upper 95% confidence limit of with zero. This method was first proposed by Hyslop, Hsuan and Holder (2000) based on a linearized bioequivalence criterion. However, their method does not consider the variations due to different sources. Hence, we apply the method of modified large-sample (MLS) for the variance components under the 2-stage nested random-effects model for construction of the upper 95% confidence limit. The total variance of the 95% upper limit considers the variance components due to lot, life stage and sample which are obtained through the MLS method. The results of empirical size and empirical power from simulation under different sample size and variance combinations are provided to investigate the performance of the extended MLS method. A numerical example illustrates the proposed method.en
dc.description.provenanceMade available in DSpace on 2021-06-08T04:46:41Z (GMT). No. of bitstreams: 1
ntu-98-R96621203-1.pdf: 1652829 bytes, checksum: cdd2eb91a8c79500c2a97de6346b319b (MD5)
Previous issue date: 2009
en
dc.description.tableofcontentsChapter 1Introduction...................................1
Chapter 2 Study Design and Data Collection Of In Vitro Bioequivalence..........................................3
2.1 Study Design for In Vitro Studies...................3
2.2 Tests and Metrics...................................4
2.2.1 Emitted Dose Uniformity, Priming/Re-Priming, and Tail-Off Profile.................................................4
2.2.2 Droplet Size Distribution (DSD)...................6
2.2.3 Spray Pattern.....................................7
2.2.4 Plume Geometry....................................8
Chapter 3 Statistical Methods3.1 In Vitro Bioequivalence
(BE) Data..............................................10
3.1 In Vitro Bioequivalence (BE) Data..................10
3.2 Nonprofile Analysis Using a Confidence Interval
Approach...............................................11
3.2.1 The Linear Statistical Model of Two-Stage Nested
Design.................................................11
3.2.2 The Bioequivalence Criterion for Comparison......13
3.2.3 Confidence Interval Method.......................14
3.2.4 Hypothesis of the Criteria.......................15
3.2.5 Bioequivalence Upper Limit.......................16
3.3 MLS Confidence Interval for Variance Components....17
3.3.1 MLS Method with Extension to Dependent Estimators
of Variance Components.................................18
3.3.2 BE Tests Based on MLS Method.....................20
Chapter 4 Example......................................30
4.1 Research Design....................................30
4.2 Statistical Analysis...............................31
4.2.1 Estimations for Linearized Criteria..............32
4.2.2 The 95% Upper Confidence Bounds for Linearized
Criteria...............................................34
4.3 Results Based on MLS Method........................38
Chapter 5 Simulation Study.............................52
5.1 Simulation Process.................................52
5.2 Simulation Results.................................53
5.2.1 Empirical size...................................53
5.2.2 Empirical power..................................54
Chapter 6 Discussion and Conclusion....................63
References.............................................72
Appendix A.............................................74
dc.language.isoen
dc.subject鼻藥噴霧劑zh_TW
dc.subject變方分析zh_TW
dc.subject95%信賴上界zh_TW
dc.subject鼻腔噴霧器zh_TW
dc.subject大樣本修正法zh_TW
dc.subject生體可用率與生體相等性zh_TW
dc.subjectNasal Aerosolsen
dc.subjectVariance Componentsen
dc.subjectMLSen
dc.subjectUpper 95% Confidence Limiten
dc.subjectIn Vitro Bioequivalence and Bioavailabilityen
dc.subjectNasal Spraysen
dc.title變方成份分析於體外生物相等性統計評估之研究zh_TW
dc.titleA Study on Statistical Evaluation of In Vitro Bioequivalence with Consideration of Variance Componentsen
dc.typeThesis
dc.date.schoolyear97-2
dc.description.degree碩士
dc.contributor.oralexamcommittee廖振鐸,季瑋珠
dc.subject.keyword鼻藥噴霧劑,鼻腔噴霧器,生體可用率與生體相等性,95%信賴上界,大樣本修正法,變方分析,zh_TW
dc.subject.keywordNasal Aerosols,Nasal Sprays,In Vitro Bioequivalence and Bioavailability,Upper 95% Confidence Limit,MLS,Variance Components,en
dc.relation.page85
dc.rights.note未授權
dc.date.accepted2009-07-30
dc.contributor.author-college生物資源暨農學院zh_TW
dc.contributor.author-dept農藝學研究所zh_TW
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