Preparing the Next Generation of Biostatisticians in the Era of Data and Translational Sciences

在数据和转化科学时代培养下一代生物统计学家

• 批准号: 10219349
• 负责人: Sujit Kumar Ghosh
• 金额: $ 24.98万
• 依托单位: NORTH CAROLINA STATE UNIVERSITY RALEIGH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10219349
• 关键词: Address; Adoption; Area; Attention; Award; Bioinformatics; Biomedical Research; Biometry; Biostatistical Methods; Clinical; Collaborations; Communities; Complex; Computational Biology; Conceptions; Data; Data Science; Development; Discipline; Electronic Health Record; Enrollment; Ensure; Environment; Evaluation; Evidence Based Medicine; Exposure to; Faculty; Future; Genomics; Goals; Health Sciences; Health system; Imaging technology; Institution; International; Joints; Knowledge; Learning; Medical Imaging; Medical center; Methodology; Methods; Modeling; Modernization; Names; National Heart, Lung, and Blood Institute; North Carolina; Observational Study; Participant; Play; Policies; Positioning Attribute; Principal Investigator; Program Effectiveness; Request for Applications; Research; Research Personnel; Research Training; Resources; Role; Schools; Science; Scientist; Statistical Methods; Strategic Planning; Structure; Students; Talents; Training; Training Programs; Translational Research; Translations; Underrepresented Populations; United States National Institutes of Health; Universities; analytical method; big biomedical data; career; career development; clinical trial analysis; cohort; computer science; computerized tools; data resource; design; education research; experience; field trip; graduate student; health science research; innovation; insight; instructor; interest; investigator training; laboratory experiment; lectures; lens; machine learning method; multidisciplinary; next generation; programs; public health research; recruit; response; skills; sound; statistical and machine learning; statistics; summer institute; summer program; summer research; tool; undergraduate student

PROJECT SUMMARY/ABSTRACT In the era of newly emerging computational tools for data science, biostatisticians need to play a fundamental role in health sciences research. There is an urgent need to encourage US Citizens and Permanent Residents to pursue graduate training in biostatistics. The design, conduct, and analysis of clinical trials and observational studies; the setting of regulatory policy; and the conception of laboratory experiments have been shaped by the fundamental contributions of biostatisticians for decades. Advances in genomics, medical imaging technologies, and computational biology; the increasing emphasis on precision and evidence-based medicine; and the widespread adoption of electronic health records; demand the skills of biostatisticians trained to collaborate effectively in a multidisciplinary environment and to develop statistical and machine learning methods to address the challenges presented by this data-rich revolutionary era of health sciences research. The proposed summer program which includes world-renowned clinical scientists and biostatisticians from two local universities, will provide an immense opportunity for student participants to learn basic yet modern statistical methods that are critical to uncovering new insights from such big and complex biomedical data and also illustrate the potential pitfalls of confounding and bias that may arise when analyzing biomedical data. A unique feature of the proposed training program is thus to expose the participants to not only basic statistical methods but also to the topics of computer science and bioinformatics which will be invaluable in creating the multidisciplinary teams required to tackle the complex research questions that often requires multipronged approaches. The proposed six-week training program will be structured around the NIH's Translation Science Spectrum and will introduce participants to opportunities in biostatistics through the lens of the science advanced by the contributions of biostatisticians. Following an initial set of weeks on basic training of biostatistical methods, the program will culminate in a data hack-a-thon style competition in which participants will employ the statistical and scientific knowledge gained during the program to produce the most innovative, statistically-sound, scientifically-relevant and effectively-communicated response to a set of research questions. The proposed research education program will enroll up to 20 such participants from across the nation and, through lectures, field trips, and opportunities to analyze data from real health sciences, inspire them to pursue graduate training. The program will draw upon considerable past collaborations and complementary resources of two local world-renowned universities to provide participants with an unparalleled view of the field, including award-winning instructors, internationally known methodological and clinical researchers, and a local area rich in opportunities to showcase careers in biostatistics. Special efforts will be made to enroll participants from underrepresented groups. Participants will be followed after completion, and the numbers attending graduate school in statistics and pursuing biostatistics careers will be documented.

项目总结/摘要 在数据科学新兴计算工具的时代，生物统计学家需要发挥基础作用， 在健康科学研究中的作用。我们迫切需要鼓励美国公民和永久居民 进行生物统计学的研究生培训。临床试验的设计、实施和分析， 观察性研究;监管政策的制定;以及实验室实验的概念， 几十年来生物统计学家的基本贡献形成的。基因组学、医学、 成像技术和计算生物学;越来越强调精确性和循证医学 医学;以及电子健康记录的广泛采用;需要生物统计学家的技能 经过培训，能够在多学科环境中进行有效合作， 学习方法，以应对这个数据丰富的健康科学革命时代所带来的挑战 research.拟议的暑期课程，其中包括世界知名的临床科学家和 来自本地两所大学的生物统计学家，将为学生提供一个巨大的机会，学习 基本而现代的统计方法，对于从如此庞大而复杂的数据中发现新的见解至关重要。 生物医学数据，也说明了在分析时可能出现的混淆和偏见的潜在陷阱 生物医学数据。因此，拟议的培训方案的一个独特之处是， 不仅基本的统计方法，而且计算机科学和生物信息学的主题，这将是 在创建多学科团队解决复杂的研究问题，往往需要宝贵的 需要多管齐下拟议的为期六周的培训计划将围绕 美国国立卫生研究院的翻译科学谱，并将介绍参与者在生物统计学的机会，通过 科学的透镜是由生物统计学家的贡献所推动的。经过最初几周的基础训练， 生物统计方法培训，该计划将以数据黑客通村式的比赛达到高潮，其中 参与者将利用在计划中获得的统计和科学知识， 创新、合理、科学相关和有效沟通的对策， 研究问题。拟议的研究教育计划将招收多达20名这样的参与者， 通过讲座、实地考察和分析来自真实的健康科学数据的机会， 鼓励他们继续深造。该计划将借鉴大量过去的合作， 两所本地世界知名大学的资源互补，为参加者提供无与伦比的 该领域的观点，包括获奖教师，国际知名的方法和临床 研究人员和当地丰富的机会，展示在生物统计学的职业生涯。将特别努力 从代表性不足的群体中招募参与者。完成后将跟踪参与者， 将记录统计学研究生院和从事生物统计职业的人数。