Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

构建现代远程开放教育考试体系初探

现代远程开放教育是基于以学习者为中心的开放学习和个别化学习。我们应从素质教育的培养目标出发 ,依据现代考试测量理论 ,利用现代科技手段 ,建立现代远程开放教育考试体系 ,客观、准确地评价学习者的进步状况以及在学识、能力等方面达到的水平 ,使学习者在学习过程中不断自我完善 ,培养他们积极进取的精神     

四种企业成本控制模式的比较分析及启示

面对日趋激烈的市场竞争环境 ,成本控制成为决定企业生存与发展的关键因素。对目前国内外较为典型的四种成本控制模式的比较分析 ,将为我国企业成本控制模式的选择提供有益的启示     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

劳动能力丧失损害赔偿的理论依据问题

劳动能力本质上属于健康权人格利益,不是独立的人格权。劳动能力的丧失是原来具有劳动能力的自然人受到他人的侵害后而致使身体残疾的结果。劳动能力丧失赔偿的所得丧失说、劳动能力丧失说、生活来源丧失说,都存在缺陷,应当予以重构。在确定我国丧失劳动能力损害赔偿制度的理论论据时,应当采用一种更为科学的理论,即以劳动能力为基础的收入丧失说。在实践中,则要以此为依据来确定劳动收入赔偿金、残疾用具费、生活上增加的必需支出、特殊医疗费、被扶养人生活费、精神抚慰金等内容。     

西南科技大学岗位聘任制和岗位津贴制的改革与探索

为适应事业单位试行人员聘用的需要,更为学校适应新形势发展的需要,西南科技大学以全员聘用和岗位聘任为突破口,实行了人事分配制度改革,建立了“以岗定酬”的岗位津贴制。通过对学校人事分配制度改革的思路和具体做法的介绍,以进一步完善和推行全员聘任制。     

作业成本法存在的问题及相应对策

作业成本法与传统成本计算最大的不同在于它不是以成本论成本 ,而是把着眼点放在成本发生的前因后果上 ,实现了成本计算与控制的结合。作业成本法的关键在于划分作业、寻找作业动因。本文在介绍作业成本法理论的基础上 ,重点探讨如何对第四类作业即发生间接成本、期间费用的作业进行划分 ,寻找作业动因     

基于资源观的大学-企业合作创新研究

以资源观理论为基础,分析大学与企业的合作动因以及对资源的要求,强调技术资源对协作伙伴选择的决定性作用,从而进一步完善资源观理论.     

Physiologically Based Liver Modeling and Risk Assessment

Because of the inherent complexity of biological systems, there is often a choice between a number of apparently equally applicable physiologically based models to describe uptake and metabolism processes in toxicology or risk assessment. These models may fit the particular data sets of interest equally well, but may give quite different parameter estimates or predictions under different (extrapolated) conditions. Such competing models can be discriminated by a number of methods, including potential refutation by means of strategic experiments, and their ability to suitably incorporate all relevant physiological processes. For illustration, three currently used models for steady-state hepatic elimination--the venous equilibration model, the parallel tube model, and the distributed sinusoidal perfusion model--are reviewed and compared with particular reference to their application in the area of risk assessment. The ability of each of the models to describe and incorporate such physiological processes as protein binding, precursor-metabolite relations and hepatic zones of elimination, capillary recruitment, capillary heterogeneity, and intrahepatic shunting is discussed. Differences between the models in hepatic parameter estimation, extrapolation to different conditions, and interspecies scaling are discussed, and criteria for choosing one model over the others are presented. In this case, the distributed model provides the most general framework for describing physiological processes taking place in the liver, and has so far not been experimentally refuted, as have the other two models. These simpler models may, however, provide useful bounds on parameter estimates and on extrapolations and risk assessments.