用SAS软件实现成组设计定量资料的统计分析

成组设计是药学科研中经常用到的一种实验设计方法,在临床药物疗效评价方面具有十分广泛的适用性.本文主要从成组设计的概念、成组设计统计分析方法的合理选用、如何使用SAS程序实现计算,以及如何解释结果这几个方面作一概述.     

苦参药材中苦参碱含量测定方法比较研究

目的采用高效液相色谱法(HPLC)建立苦参药材中苦参碱含量的测定方法.方法采用配对试验设计,将高效液相色谱法与薄层色谱扫描法(TLCS)测定苦参药材中苦参碱含量进行比较研究,对试验结果进行配对差值均数t检验.结果表明2种方法测定苦参药材中苦参碱含量无差别.结论高效液相色谱法(HPLC)可准确、简便、快速测定苦参药材中苦参碱含量.     

本刊关于论文统计学处理的要求

1.统计研究设计:应交代统计研究设计的名称和主要做法。如调查设计(分为前瞻性,回顾性或横断面调查研究);实验设计(应交代具体的设计类型,如自身配对设计,成组设计、交叉设计、析因设计.正交设计等);临床试验设计(应交代属于第几期临床试验,采用了何种盲法措施等)。主要做法应围绕四个基本原则(随机.对照、重复.均衡)概要说明,尤其要交代如何控制重要非试验因素的干扰和影响。     

本刊关于论文统计学处理的要求CSCD

1.统计研究设计:应交代统计研究设计的名称和主要做法。如调查设计(分为前瞻性、回顾性或横断面调查研究);实验设计(应交代具体的设计类型,如自身配对设计、成组设计、交叉设计.析因设计.正交设计等);临床试验设计(应交代属于第几期临床试验,采用了何种盲法措施等)。主要做法应围绕四个基本原则(随机、对照、重复均衡)概要说明,尤其要交代如何控制重要非试验因素的干扰和影响。     

用SAS软件实现随机区组设计定量资料的统计分析

随机区组设计是药学科研中控制重要的非试验因素时用到的一种试验设计方法,在临床药物疗效研究方面具有十分广泛的适用性.本文主要对随机区组设计的概念,统计分析方法的合理选用,如何使用SAS程序进行分析,以及如何解释结果几个方面作一概述.     

对来稿中统计学处理的有关要求

1.统计研究设计:应交代统计研究设计的名称和主要做法。如调查设计(分为前瞻性、回顾性还是横断面调查研究)、实验设计(应交代具体的设计类型,如自身配对设计、成组设计、交叉设计、析因设计、正交设计等)、临床试验设计(应交代属于第几期临床试验,采用了何种盲法措施等);主要做法应围绕4个基本原则(重复、随机、对照、均衡)概要说明,尤其要交代如何控制重要非试验因素的干扰和影响。     

本刊关于论文统计学处理的要求CSCD

1.统计研究设计:应交代统计研究设计的名称和主要做法。如调查设计(分为前瞻性、回顾性或横断面调查研究);实验设计(应交代具体的设计类型,如自身配对设计、成组设计、交叉设计、析因设计、正交设计等);临床试验设计(应交代属于第几期临床试验,采用了何种盲法措施等)。主要做法应围绕四个基本原则(随机、对照、重复、均衡)概要说明,尤其要交代如何控制重要非试验因素的干扰和影响。     

本刊关于论文统计学处理的要求

1.统计研究设计:应交代统计研究设计的名称和主要做法。如调查设计(分为前瞻性、回顾性或横断面调查研究);实验设计(应交代具体的设计类型,如自身配对设计、成组设计、交叉设计、析因设计、正交设计等);临床试验设计(应交代属于第几期临床试验,采用了何种盲法措施等)。主要做法应围绕四个基本原则(随机、对照、重复、均衡)概要说明,尤其要交代如何控制重要非试验因素的干扰和影响。     

读“摇瓶实验的数据处理”

《抗生素》1979年第四卷第五期张若飞同志“摇瓶实验的数据处理”一文介绍用数理统计方法处理摇瓶实验数据的知识,对从事抗生素工艺研究的同志学习和运用生物统计是有帮助的,对提高抗生素工艺研究的水平是有益的。本人读后也受到不少启发.同时觉得还有几点值得进一步商榷和探讨。 一、配对设计 在原文“四、两组实验数据的比较”中.以“每种培养基各进9只摇瓶米比较两种培养基的优劣”为例,介绍t测验法。作者采用配对设计,但对配对的理由未作明确说明,我们仅能从“差数标准差的计算表”上的“重复数”去理解“每种培养基各进9只摇瓶”是分九批(次),每批各进1只摇瓶进行试验的.也只有这样的实验数据才可以配对,如果两种培养基同时各进9只摇瓶,所得的数据应属于两样本平均值的比较,就不能根据两组摇瓶的相对序号进行配对了。 在发酵工艺研究中,比较两种培养基的优劣,常用的实验设计是“每种培养基,一批各进3 产摇瓶,共做三批实验”,这样所得的数据应如何统计处理呢?可先分别求出每批实验3只摇瓶数据的均     

研究设计应交代的内容

研究设计应告知研究设计的名称和主要方法。如调查设计（分为前瞻性、回顾性还是横断面调查研究）,实验设计（应明确具体的设计类型,如自身配对设计、成组设计、交叉设计、析因设计、正交设计等）,     

多种统计学优化方法在盐酸川芎嗪缓释制剂处方设计中的比较研究

处方优化方法的合理选用对高效、经济地设计药物剂型发挥着很大的作用。目前在药剂学研究中普遍应用的统计学实验设计方法有正交设计、均匀设计、析因设计、单纯形设计及中央多点等距设计(CCD)等。本文以盐酸川芎嗪(TMPH)缓释片剂为模型药物,通过其优化设计过程,对多种优化方法的设计要求和预测能力进行了横向对比,期望能有助于处方优化方法的合理选择。     

Ⅱ类骨质量下短种植体表面设计对骨界面应力分布的影响

目的：探讨骨质量和种植体表面设计对短种植体-骨界面应力分布的影响。方法：利用3D-Doctor软件和ABAQUS软件建立Ⅴ形螺旋设计、反支撑形螺旋设计、支撑形螺旋设计和鳍式非螺旋设计的短种植体植于Ⅰ类骨质量的上颌骨后区的三维有限元法模型4个。对所有模型进行垂直和侧向加载，分析比较周围骨组织的应力分布和Von-Mises应力峰值。结果：垂直向和侧向加载时，反支撑形和支撑形螺纹设计与鳍式非螺旋设计都表现出较好的应力分布特征。结论：支撑形螺旋设计、反支撑形螺旋设计和鳍式非螺旋设计均适用于短种植体，应避免应用Ⅴ形螺旋表面设计。     

Design of population pharmacokinetic experiments using prior information

A population pharmacokinetic study design is a group of elementary designs each composed of a set of sampling times to be performed in a number of subjects in the design. Design factors such as the number of elementary designs, proportion of subjects in each elementary design, number of samples per subject, and sampling times in the subjects need to be carefully balanced in the design of a study. An optimally designed population pharmacokinetic study will give the best combination of these design factors and involves application of statistical experimental design principles to non-linear population pharmacokinetic models. Information from previous experiments, the literature, and experience in the form of model and parameter estimates are used to design a future study by optimization of a design criterion within some constraints. This work provides a brief background of approaches to the designs of a population pharmacokinetic experiment and a review of optimal design methodologies that have been developed for designing population pharmacokinetic experiments. Computer application programs and software that have been developed together with options available in them are also reviewed.     

大数据和人工智能技术用于计算机辅助药物设计的研究进展

大数据和人工智能（AI）技术不仅可以对海量的生物医学数据进行准确和综合地分析,而且可以帮助构建药物设计领域的预测模型。随着算法和统计方法的发展,大数据和AI技术已应用于计算机辅助药物设计（CADD）。CADD可被用于有效克服药物设计领域的困难,从而高效地设计和开发新药。介绍了药物设计和发现过程中数据预处理和建模步骤、药物设计和发现过程中基于AI的建模方法、大数据和AI技术在CADD中的最新应用,以期为我国药物设计和开发提供参考。     

临床试验Williams设计中样本含量的估算方法

在临床试验中,2组交叉设计应用已相当广泛,其样本含量估算方法也被研究者所熟悉。多组交叉试验由Williams首先提出,因此被称为Wil-liams设计。本文介绍基于Williams设计的样本含量估算方法,并提供示例分析,供研究者参考使用。     

Design of small molecule libraries for NMR screening and other applications in drug discovery

There are conceptual differences between high-throughput screening (HTS) and fragment-based screening by NMR. The number of compounds in libraries for NMR screening may be significantly smaller than those used for HTS. Because one relies on a small library its design is significantly important and is the object of this article. A short introduction on fragment-based NMR screening approaches will be provided. Although there are currently very few reports describing the design of libraries of small molecules for NMR screening, aspects of the question of how to compile diverse collections of small molecular fragments useful for drug design were previously addressed for the purposes of combinatorial library design and de novo drug design. As these disciplines are highly interrelated and are applied in an interconnected manner with NMR screening within the drug discovery process, a review of combinatorial library design and especially the building block or fragment selection strategies applied for combinatorial library design and de novo design is well suited to reveal fundamental strategies and potential techniques for the design of NMR screening libraries. This section will be rounded off by a report on hands-on-experience with the design of the Novartis second-site NMR screening library and practical considerations for the design of compound mixtures. Rather than providing an exact protocol general guidelines will be indicated.     

微球给药系统的工艺优化研究

目的 :阐述微球制备工艺中的优化技术。方法 :检索近年来国内外文献并进行整理和归纳。结果 :单因素设计、正交设计、均匀设计、因子设计是目前微球工艺中常用的优化方法。结论 :通过上述方法优化微球的制备工艺 ,可在一定条件下达到经济、高效的目的 ,更理想的优化技术尚有待研究     

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。     

A Bayesian Approach to the ICH Q8 Definition of Design Space

Manufacturers of pharmaceuticals and biopharmaceuticals are facing increased regulatory pressure to understand how their manufacturing processes work and to be able to quantify the reliability and robustness of their manufacturing processes. In particular, the ICH Q8 guidance has introduced the concept of design space. The ICH Q8 defines design space as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality.” However, relatively little has been put forth to date on how to construct a design space from data composed of such variables. This study presents a Bayesian approach to design space based upon a type of credible region first appearing in Peterson's work.This study considers the issues of constructing a Bayesian design space, design space reliability, the inclusion of process noise variables, and utilization of prior information, as well as an outline for organizing information about a design space so that manufacturing engineers can make informed changes as may be needed within the design space.     

Design of population pharmacokinetic experiments using prior information

A population pharmacokinetic study design is a group of elementary designs each composed of a set of sampling times to be performed in a number of subjects in the design. Design factors such as the number of elementary designs, proportion of subjects in each elementary design, number of samples per subject, and sampling times in the subjects need to be carefully balanced in the design of a study. An optimally designed population pharmacokinetic study will give the best combination of these design factors and involves application of statistical experimental design principles to non-linear population pharmacokinetic models. Information from previous experiments, the literature, and experience in the form of model and parameter estimates are used to design a future study by optimization of a design criterion within some constraints. This work provides a brief background of approaches to the designs of a population pharmacokinetic experiment and a review of optimal design methodologies that have been developed for designing population pharmacokinetic experiments. Computer application programs and software that have been developed together with options available in them are also reviewed.