藥物濃度時間側寫之統計模式及其應用;Statistical Models for Drug Concentration-Time Profiles and Their Applications.

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/56939

Title:	藥物濃度時間側寫之統計模式及其應用;Statistical Models for Drug Concentration-Time Profiles and Their Applications.
Authors:	陳玉英
Contributors:	中央大學統計研究所
Keywords:	藥學;統計學
Date:	2008-09-01
Issue Date:	2012-10-01 15:07:31 (UTC+8)
Publisher:	行政院國家科學委員會
Abstract:	針對藥物開發進行的第一期臨床試驗的藥物動力學研究，主要目的即是探求該藥物在血液或血漿中濃度隨時間變化的側寫。此一血中藥物濃度時間側寫經常提供該藥物藥效或/和毒性的有用資訊。常用於描述個人側寫的有開放一階單區及一般注入式的雙區模式。然而，因為個人與個人之間的差異性，就整體側寫而言，經常考慮隨機效應模式，因此使得估計整體側寫模式之參數變得較為複雜。此一二年期的研究計畫擬在第一年提出具有廣泛右偏分布藥物濃度的單區及雙區統計模式，使之不再限於對數常態分布或甘馬分布。除針對個人及整體側寫模式估計相關參數，並且進行選模的工作。第二年計畫將專注於上述模式的應用，除討論如何針對個人側寫模式建立信賴帶，也進行與整體側寫比較之下具有極端個人側寫的診斷。 ; The major purpose of the pharmacokinetic study in Phase I of a clinical trial for drug development is to investigate the profile of the concentration of the drug in plasma or blood over time. Note that the drug concentration-time profile usually provides with valuable information about the efficacy and/or toxic effect of the drug. An open, first order, one-compartment and an ordinary two-compartment model with infusion are often employed to describe the mean concentration of a single individual’s profile. However, due to intra-individual variation, random effects are usually introduced for the population concentration profile and hence result into much complication on the estimation of related parameters. In the first year of the two-year research project, we consider the one-compartment and two-compartment models for a general class of right-skewed distributions, which do not confine only to the lognormal or gamma distribution. We then estimate the parameters involved in the individual and population profile models and suggest procedures for model selection. In the second year of the research project, we focus on the application of the proposed models. We discuss not only how to construct the confidence band for the individual profile, but also how to detect extreme effects on certain individual profiles away from the population one. ; 研究期間 9708 ~ 9807
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Graduate Institute of Statistics] Research Project

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