Interdisciplinary Training Program in Biostatistics and Personalized Medicine

描述(由申请人提供)：这项提案概述了一个新的生物统计学博士前培训计划，重点是基因组学和个性化医学的应用。主要教职员工来自斯坦福大学卫生研究与政策系和统计系。一群来自生物化学、遗传学、心脏病学和其他领域的附属教员为跨学科研究提供了必要的广度。该项目的学员在统计系攻读博士学位，重点是生物统计学；斯坦福大学目前不提供这一选项。除了满足PHD I统计的要求，拟议的计划还将包括生物医学科学的额外课程工作，在合作环境中经验的指导研究，以及负责任的研究行为培训。 公共卫生相关性：叙事医学越来越依赖高通量技术，以努力提供个性化护理，针对每个患者的特定特征进行治疗。为了将这些现代技术的输出转化为对医疗实践有用的信息，人们需要挖掘和理解大型而复杂的数据集。我们建议的项目将使学生掌握最先进的实验设计和数据分析方法，并将培训他们与医学科学家和生物学家有效合作的艺术。受训者将有能力接受分析新的复杂数据集的挑战，并从中提取具有改善患者护理和公共健康潜力的信息和知识。

DESCRIPTION (provided by applicant): This proposal outlines a new pre-doctoral training program in biostatistics that emphasizes applications to genomics and personalized medicine. Primary faculty members are from the Departments of Health Research & Policy and Statistics at Stanford University. A group of affiliate faculty from biochemistry, genetics, cardiology and other areas provide the necessary breadth for interdisciplinary research. The trainees in the program pursue a PhD in the Department of Statistics, with a concentration in Biostatistics; this option currently not available at Stanford. In addition to fulfilling the requirements of the PhD i Statistics, the proposed program will include additional course work in biomedical sciences, mentored research experienced in a collaborative setting, and training in the responsible conduct of research. PUBLIC HEALTH RELEVANCE: Narrative Medicine increasingly relies on high-throughput technologies in an effort to provide personalized care, targeting therapies to the specific characteristics of each patient. To translate the output of these modern technologies into information useful for medical practice, one needs to mine and understand large and complex datasets. The program that we propose will equip students with state-of-the-art methods for experimental design and data analysis, and will train them in the art of effective collaboration with medical scientists and biologists. Trainees will be empowered to take on the challenge of analyzing novel complex datasets, and from this, extract information and knowledge with the potential for improving patient care and public health.