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Innovative statistical methods for clinical trial pathways supporting regulatory drug approval

支持监管药物审批的临床试验路径创新统计方法

基本信息

批准号：
2270563
负责人：
金额：
--
依托单位：
University of Warwick
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2270563
关键词：
Innovative statistical methods clinical trial

项目摘要

Programme overview: This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to address important applied biomedical research questions in priority areas aligned with industry. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice. Project overview: Regulatory approval of new drugs is underpinned by provision of substantial evidence of effectiveness from clinical trials. This is often interpreted as requiring two independent confirmatory trials. Recent innovation in clinical trial design is challenging this interpretation, however, as trials conventionally conducted separately may be combined using an adaptive seamless design.In collaboration with Boehringer Ingelheim in Germany, this PhD project will focus on statistical methods for trial design and decision-making in adaptive confirmatory clinical trials. This will require a combination of theoretical and computational statistical methods, to explore optimal trial design and synthesis of evidence from different sources.

课程概述：这个由MRC资助的博士培训伙伴关系(DTP)将尖端的分子和分析科学与数据分析中的创新计算方法结合在一起，使学生能够在与行业保持一致的优先领域解决重要的应用生物医学研究问题。这是一个为期4年的课程，第一年包括一系列的教学模块和两个基于实验室的研究项目，这些项目导致了跨学科生物医学研究的硕士学位。前两个学期包括精选的教学模块，使学生能够在多学科的科学中获得坚实的基础。学生们还参加了由学术和行业专家主持的一系列大师课程，这些专家涉及分子、细胞和组织动力学、微生物学和传染病、应用生物医学技术以及人工智能和数据科学等领域。在第三学期和暑期，学生们在他们选择的实验室里进行两个为期十一周的研究项目。项目概述：新药的监管批准是由临床试验提供的有效证据支撑的。这通常被解释为需要两个独立的验证性试验。然而，最近临床试验设计方面的创新正在挑战这种解释，因为传统上单独进行的试验可以使用自适应无缝设计进行组合。这个博士项目将与德国的勃林格-英格尔海姆合作，专注于适应性验证性临床试验中试验设计和决策的统计方法。这将需要理论和计算统计方法的结合，以探索最佳试验设计和来自不同来源的证据的合成。