Development of Innovative Statistical Tools in Design of Scientific Experiments and Surveillance Studies

科学实验和监测研究设计中创新统计工具的开发

• 批准号: 0904125
• 负责人: Sam Hedayat
• 金额: $ 20万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0904125&HistoricalAwards=false
• 关键词: Development; Innovative; Statistical; Tools; Design

Providing flexibility to an experimenter in ensuring efficient and cost-effective data collection methods in pharmaceutical, biotechnological, agricultural and engineering studies have thrown up unprecedented challenges to the design theorists. The investigator develops innovative design-based techniques, in the classical sense as well as in the context of factorial experiments and crossover designs with immediate applications in such areas as biopharmaceutical trials, drug abuse liability trials, and evaluation of new drugs for unwanted effects on electrical properties of the heart, which includes QT/QTc trials in safety assessment. The issues of timely detection and prevention of various types of adverse health events such as drug toxicity, are gaining importance in surveillance related to public health and phase IV clinical trials. The investigator also explores and develops relevant innovative surveillance strategies and examine their relative performance with respect to several well-known optimality criteria and with reference to the role of statistical indicators [such as false alarm rate, delay time for true alarm, in-control average run length]. The investigator examines strategies for determining how frequently and how efficiently the adverse event rate should be monitored in the sense of timely detection and intervention, incurring minimal cost.The project develops innovative statistical theory and related computational methodologies in resolving some critical design and surveillance issues, not adequately addressed hitherto, covering such areas as pharmaceutical, biotechnological, agricultural and engineering studies. Researchers learn about cutting edge techniques to deal with some real life problems such as(i) the effects of environmental factors on quality of drug substance or shelf life for drug product or storage conditions, (ii) surveillance issues in medical sciences and public health [complicated cases of pregnancies, pandemic influenza, West Nile virus, severe acute respiratory syndrome [SARS], emission of radiation from hazardous pollutants in air / surface / water] and in drug toxicity study in Phase IV clinical trials. Practitioners utilize the findings for more insightful experimentation and data collection techniques in these fields. Advanced Undergraduate and Graduate students are trained in the statistical methods.

为实验者提供灵活性，以确保在制药，生物技术，农业和工程研究中的有效和具有成本效益的数据收集方法，给设计理论家带来了前所未有的挑战。研究者开发基于创新设计的技术，在经典意义上以及在析因实验和交叉设计的背景下，立即应用于生物制药试验，药物滥用责任试验和评价新药对心脏电特性的不良影响，包括安全性评估中的QT/QTc试验。及时发现和预防各种类型的不良健康事件（如药物毒性）的问题在与公共卫生和IV期临床试验相关的监测中越来越重要。研究者还探索和开发相关的创新监测策略，并检查其相对于几个众所周知的最优标准的相对性能，并参考统计指标的作用[如假警报率，真警报的延迟时间，控制平均运行长度]。研究者检查的策略，以确定如何频繁和如何有效的不良事件率应及时检测和干预的意义上进行监测，招致最低cost.The项目开发创新的统计理论和相关的计算方法，在解决一些关键的设计和监督问题，没有充分解决迄今为止，涵盖制药，生物技术，农业和工程研究等领域。研究人员学习尖端技术，以处理一些真实的生活问题，如（i）环境因素对原料药质量或药品保质期或储存条件的影响，（ii）医学和公共卫生中的监测问题[妊娠并发症、大流行性流感、西尼罗河病毒、严重急性呼吸道综合征[SARS]，空气/地表/水中有害污染物的辐射排放]以及IV期临床试验中的药物毒性研究。从业者利用这些发现在这些领域进行更有见地的实验和数据收集技术。高级本科生和研究生接受统计方法的培训。