统计学，医学的好帮手

贵刊《统计学：一门贯穿于临床研究始终的学科》一文提出统计学对临床研究的重要性。其实统计学在基础医学的试验设计和数据统计中也同样重要。医学试验设计中随机、对照、重复是三个最核心的要素。评定一个试验是否科学的关键就看这三要素是否合理的贯穿整个试验。这几要素也可作为日常人们判断一个药物是否有效的依据。想要做到这三点就必须要统计学的帮助。     

中医院计算机管理中药品编码的设计

本文概述了国内现有药品编码的优缺点，提出了药品编码设计的三要素；并根据中医院药品使用的特点，设计了一套新的药品编码。实践表明，该编码系统记忆方便、输入快捷、操作简单、实用性强。     

中专医护英语词汇教学应用刍议

词汇是语言的三要素之一,是语言的基本材料,是一切语言活动的基础。而中专学生在学习医护英语词汇上存在许多障碍。本文通过分析教师在平时词汇教学中碰到的问题,结合笔者在教学中的体会,对中专的英语词汇教学提出自己的一些看法,并设计了相关的教学策略。     

简约稳定性研究设计介绍

稳定性研究设计分为完全试验设计和简约试验设计2种。完全试验设计是指在全部的时间点考察全部批次的样品，简约试验设计指在部分时间点考察全部批次的样品。简约试验设计常用的有括弧法和矩阵法。简约设计的稳定性研究数据的处理与完全设计的稳定性研究数据的处理相同。     

均匀设计及其在药学科研设计中的应用

本文阐明如何使用均匀设计来解决药学领域中的多因素多水平的试验设计问题。均匀设计的最大优点是：试验的次数少，每个因素每个水平只做一次试验，且试验次数与水平数相等。而正交设计的试验次数则是水平数平方的整数掊。如果我们将均匀设计和多元统计相配合作综合分析，更利于分析各因素对试验结果的影响，定量地预测优化条件。所以均匀设计是值得在药学科研领域中推广应用的一种好的设计方法。     

均匀设计方法及其应用

利用统计学方法处理科学试验数据是当今在科学研究中重要的一个环节 ,但应当注意到在试验过程中试验设计是否合理直接影响到试验的结果和统计分析。另一方面 ,科学的试验设计可以大量的节省试验次数 ,达到试验的最佳效果。通过对均匀设计与正交设计的比较 ,说明了均匀设计可用较少的试验次数达到较好的试验效果 ,同时指出了其在应用中应注意的问题。     

均匀设计及其在药学中的应用

<正> 均匀设计是一种多因素试验设计方法。所谓试验设计是指对于即将进行的试验进行合理的安排,使之用尽量少的试验达到预期的目的。以往,对于多因素试验设计一般采用正交设计法。正交设计的特点是在各因素考察范围内使试验点“均匀分散,整齐可比”。“均匀分散”可使所选取的少量试验点均匀地散布在     

欧盟医药管理局对新抗菌药物临床试验策略和设计的考虑

试验设计是临床试验能否获得成功的关键。本文简要介绍了欧盟医药管理局对抗菌药物临床试验策略和设计的相关考虑,希望对我国创新性抗菌药物的临床试验设计和评价有所提示和参考。     

1期临床耐受性试验键盘设计方法

目的介绍国外新提出的1期临床试验设计方法——键盘设计(keyboard design)模型、试验流程及其操作性能,为国内1期临床试验设计提供新方法。方法举例对键盘设计进行介绍,并通过模拟研究对键盘设计、mTPI设计及3+3设计进行比较。结果键盘设计在确定最大耐受剂量的精确性及安全性上优于mTPI设计。结论键盘设计操作简单,性能优越,是一种科学、可靠、灵活安全的1期临床试验设计方法。     

如何认识重复测量设计——怎样在药物应用与监测研究中正确运用统计学（八）

重复测量设计是一种比较常见的试验设计类型,由于这种设计符合许多医学试验本身的特点,故在医学科研中使用的频率很高。本文对重复测量试验设计特点、类型进行了介绍,以及对一些实例进行分析,旨在帮助广大医学科研工作者能够正确认识此种设计类型,更好地将它应用到医学试验中。     

实验设计的概念与基础

为了有助于提高药学工作者制定实验设计方案的水平,本文概括性介绍了实验设计的概念和意义,阐述了实验设计的核心内容,即实验设计的三要素、四原则和实验设计类型。     

The design of an experiment using statistical power with a startle chamber study as an example

Using a startle chamber experiment as a case study, it is shown how the sensitivity of a study's design can be quantified by using the concept of statistical power and how the design can be planned to achieve the power desired. The purpose of the experiment was to compare background responses in three empty startle chambers. The study design nested groups of noise events into trials, entailing two sources of experimental error, variation within trials and between trials. For this nested design, the proper statistical analysis and calculation of power are described. It is shown how the power depends on the numbers of trials and events per trial (sampling effort), magnitudes of the sources of variability and background differences to be detected. A worked example shows the power associated with several sampling alternatives. Associated implications for cost and benefit are also discussed.     

替硝唑凝胶处方筛选研究

为筛选具有抗氧、防腐及耐寒的替硝唑凝胶处方,本文采用正交法、选择溶媒、抗氧剂和防腐剂三个可变因素,并设置不同水平进行实验比较.结果表明,以丙二醇和乙醇作替硝唑的混合溶媒,并配以抗氧剂获得质量稳定的替硝唑凝胶.     

替硝唑凝胶处方筛选研究

为筛选具有抗氧、防腐及耐寒的替硝唑凝胶处方,本采用正交法、选择溶媒、抗氧剂和防腐剂三个可变因素,并设置不同水平进行实验比较。结果表明,以丙二醇和乙醇作替硝唑的混合溶媒,并配以抗氧剂获得质量稳定的替硝唑凝胶。     

一个针对药学专业的分析化学综合设计性实验

将综合设计性实验引入药学专业的分析化学实验教学中,结合学校实验条件,选择测定女贞子中的黄酮含量,指导学生自行设计实验方案,独立完成实验内容,写出实验总结。旨在培养、提高本科药学专业学生学习兴趣和创新能力。     

遗传算法在均匀试验设计最优条件选择中的应用

目的探讨遗传算法在均匀试验设计最优条件选择中的应用。方法利用甘草苷提取工艺均匀试验设计结果,以中心化二次回归模型为目标函数,用遗传算法搜索最优试验条件。结果甘草苷中心化二次回归模型有统计学意义,遗传算法确定的最优试验条件:52%的甲醇溶液冷浸11 h,超声提取77 min,甘草苷提取量预测值达到了29.65 mg/g,比2号试验最高提取量增加了2.67 mg/g,提高了10%。结论以二次回归模型为目标函数,利用遗传算法确定的均匀试验最优条件客观性强、精度高,为均匀试验设计优化分析提供了合理的新方法。     

Mixture experiment methods in the development and optimization of microemulsion formulations

Microemulsion formulations represent an interesting delivery vehicle for lipophilic drugs, allowing for improving their solubility and dissolution properties. This work developed effective microemulsion formulations using glyburide (a very poorly-water-soluble hypoglycaemic agent) as a model drug. First, the area of stable microemulsion (ME) formations was identified using a new approach based on mixture experiment methods. A 13-run mixture design was carried out in an experimental region defined by constraints on three components: aqueous, oil and surfactant/cosurfactant. The transmittance percentage (at 550 nm) of ME formulations (indicative of their transparency and thus of their stability) was chosen as the response variable. The results obtained using the mixture experiment approach corresponded well with those obtained using the traditional approach based on pseudo-ternary phase diagrams. However, the mixture experiment approach required far less experimental effort than the traditional approach. A subsequent 13-run mixture experiment, in the region of stable MEs, was then performed to identify the optimal formulation (i.e., having the best glyburide dissolution properties). Percent drug dissolved and dissolution efficiency were selected as the responses to be maximized. The ME formulation optimized via the mixture experiment approach consisted of 78% surfactant/cosurfacant (a mixture of Tween 20 and Transcutol, 1:1, v/v), 5% oil (Labrafac Hydro) and 17% aqueous phase (water). The stable region of MEs was identified using mixture experiment methods for the first time.     

临床生物化学开放性实验的学习心得

通过与以往传统教学不同的临床生化开放性实验课的学习,使得我们学生在自己动脑动手的过程中大胆的进行科研设计,学会如何自己去选定实验题目,如何确定切实可行的实验方法 ,如何对实验数据进行处理和分析。在实验的过程中真正的作为学习的主体来学习,从而进一步提高我们创造性思维和科学研究的能力。     

医药数理统计中正交试验方法研究

结合Excel及SPSS软件的应用,对正交试验在解决实际问题中的若干数据处理方法进行比较,目的是使学生更好地掌握正交试验设计的方法,把它更广泛地应用到药学、药理学的实验设计中,提高试验的科学性,达到简便、快捷和准确的统计效果。     

Experiment design for nonparametric models based on minimizing Bayes Risk: application to voriconazole$$^{}$$

An experimental design approach is presented for individualized therapy in the special case where the prior information is specified by a nonparametric (NP) population model. Here, a NP model refers to a discrete probability model characterized by a finite set of support points and their associated weights. An important question arises as to how to best design experiments for this type of model. Many experimental design methods are based on Fisher information or other approaches originally developed for parametric models. While such approaches have been used with some success across various applications, it is interesting to note that they largely fail to address the fundamentally discrete nature of the NP model. Specifically, the problem of identifying an individual from a NP prior is more naturally treated as a problem of classification, i.e., to find a support point that best matches the patient’s behavior. This paper studies the discrete nature of the NP experiment design problem from a classification point of view. Several new insights are provided including the use of Bayes Risk as an information measure, and new alternative methods for experiment design. One particular method, denoted as MMopt (multiple-model optimal), will be examined in detail and shown to require minimal computation while having distinct advantages compared to existing approaches. Several simulated examples, including a case study involving oral voriconazole in children, are given to demonstrate the usefulness of MMopt in pharmacokinetics applications.