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

在制药、生物技术、农业和工程研究中，为实验者提供灵活性，以确保有效和具有成本效益的数据收集方法，这对设计理论家提出了前所未有的挑战。研究者开发创新的基于设计的技术，在经典意义上，以及在析因实验和交叉设计的背景下，在生物制药试验、药物滥用责任试验和评估新药对心脏电学特性的不良影响等领域立即应用，其中包括安全性评估中的QT/QTc试验。在与公共卫生和第四期临床试验有关的监测中，及时发现和预防各种类型的不良健康事件（如药物毒性）的问题越来越重要。研究者还探索和开发了相关的创新监测策略，并根据几个众所周知的最优性标准和参考统计指标的作用（如虚警率、真警延迟时间、控制平均运行长度）检查了它们的相对性能。研究人员检查了在及时发现和干预的意义上确定不良事件发生率监测的频率和效率的策略，从而产生最小的成本。该项目发展创新的统计理论和有关的计算方法，以解决一些迄今未得到充分解决的关键设计和监测问题，涉及诸如制药、生物技术、农业和工程研究等领域。研究人员学习尖端技术，以处理一些现实生活中的问题，例如：(i)环境因素对药品质量或药品保质期或储存条件的影响；（ii）医学和公共卫生方面的监测问题[复杂的怀孕病例、大流行性流感、西尼罗河病毒、严重急性呼吸系统综合症[SARS]]；[空气/地表水/水中有害污染物的辐射]和第四期临床试验的药物毒性研究。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方面的培训。

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.