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

项目摘要/摘要 在新兴的数据科学计算工具时代，生物统计学家需要发挥基本作用 在健康科学研究中的作用。迫切需要鼓励美国公民和永久居民 继续生物统计学方面的研究生培训。设计、实施和分析临床试验和 观察性研究；监管政策的制定；以及实验室实验的概念 这是由生物统计学家几十年来的基本贡献决定的。基因组学、医学研究进展 成像技术和计算生物学；日益强调精确度和循证 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 接受培训，以便在多学科环境中有效协作，并开发统计和机器 学习方法以应对这个数据丰富的健康科学革命性时代带来的挑战 研究。拟议的夏季计划包括世界知名的临床科学家和 来自当地两所大学的生物统计学家将为学生参与者提供一个巨大的学习机会 基本而又现代的统计方法，对于从如此庞大和复杂的数据中发现新的见解至关重要 生物医学数据，还说明了在分析时可能出现的混淆和偏差的潜在陷阱 生物医学数据。因此，拟议的培训方案的一个独特特点是让参与者接触到 不仅有基本的统计方法，还有计算机科学和生物信息学的主题，这将是 在创建解决复杂研究问题所需的多学科团队方面具有无可估量的价值，这些问题通常 需要多管齐下。拟议的为期六周的培训计划将围绕 NIH的翻译科学光谱，并将通过 生物统计学家的贡献推动了科学的发展。在BASIC的最初几周之后 生物统计学方法的培训，该计划将在一场数据黑客马拉松风格的比赛中达到高潮 参与者将利用在计划期间获得的统计和科学知识来产生最大 创新、统计合理、科学相关并有效沟通的对一组 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 在全国范围内，通过演讲、实地考察和分析来自真实健康科学的数据， 激励他们继续进行研究生培训。该计划将借鉴过去大量的合作和 两所本土世界知名大学资源互补，为参会人员提供无与伦比的 该领域的观点，包括屡获殊荣的讲师、国际知名的方法学和临床 研究人员，以及一个有丰富机会展示生物统计学职业生涯的当地地区。特别努力将是 为从代表性不足的群体中招募参与者而制定的。参赛者在完成后将被跟踪，以及 就读统计学研究生院并从事生物统计学职业的人数将被记录在案。

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.