Computational Medicine in the Heart, Integrated Training Program

心脏计算医学综合培训计划

• 批准号: 10556918
• 负责人: Alison L Marsden
• 金额: $ 20.1万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10556918
• 关键词: Heart; Medicine; Training Programs

Project Summary Cardiovascular (CV) diseases are rising causes of morbidity and mortality worldwide. There is excitement that computational medicine, an emerging field combining engineering disciplines with the life sciences, will enable scientific and clinical breakthroughs and accelerate bench-to-bedside translation. However, few training programs exist in this field, and so trainees often learn ad hoc. We seek funding for a new multidisciplinary T32 program in Computational medicine in the Heart: Integrated training Program (CHIP) at Stanford. CHIP will provide cutting-edge training for 3 post-PhD, -MD or -MD/PhD fellows annually, each undergoing 2 years of training at the intersection of engineering, CV physiology and medicine. Trainees will pursue a cutting-edge research project mentored by faculty with complementary expertise in engineering and the life sciences, and select didactic courses to build expertise, grow professionally, and develop community. The forward-looking vision of CHIP addresses key priorities of several National Agencies and fills current gaps in interdisciplinary training. Stanford CHIP leverages faculty and resources at top-ranked Schools of Engineering, Medicine and Humanities and Sciences. The T32 is co-directed by a physician-engineer and an engineer-physiologist, bringing 38 faculty from 13 Departments and Divisions with strong emphasis on women and under - represented minorities. Key support is provided by the inter-disciplinary Cardiovascular Institute (CVI) and the Institute for Computational and Mathematical Engineering (ICME) at Stanford. Faculty will provide trainees with research opportunities in CV science spanning cell-to-organ and bench-to-bedside, as well as computational science, clinical care, and therapeutic innovation. The faculty are highly collaborative and have exceptional track records of launching trainees into independent scientific careers. Applicant selection and all aspects of the program stress inclusion of trainees from under-represented groups. Trainees will not be required to have backgrounds in both engineering and life sciences. The T32 will provide tailored teaching of CV science to engineers, engineering to life-science fellows, and advanced cross- disciplinary topics to each. Core didactics also include ethics, the responsible conduct of science, methods to ensure reproducibility. Diversity, equity and inclusion are central for trainees and faculty. Evaluation will be both constructive and bidirectional between trainees and faculty. In summary, the CHIP T32 at Stanford provides post-MD, post-PhD and post-MD/PhD graduates with world-class training at the intersection of bioengineering, CV science and medicine. The T32 is well positioned for success due to the co-location of these top-tier resources on a single campus in Silicon Valley, a hub of innovation in data science, artificial intelligence and therapy. Our aspirational goal is that CHIP graduates will become global scientific leaders at the cusp of engineering, physiology and medicine.

项目摘要 心血管（CV）疾病是全球发病率和死亡率上升的原因。有 令人兴奋的是，计算医学，一个新兴的领域相结合的工程学科与生活 科学，将使科学和临床突破，并加快从实验室到床边的转变。 然而，这一领域的培训项目很少，因此受训者经常临时学习。 我们寻求资助一个新的多学科T32计划在计算医学的心脏： 斯坦福大学的综合培训项目。CHIP将为3名博士后，-MD或 -MD/PhD研究员每年，每个人都在工程，CV的交叉点接受2年的培训 生理学和医学。学员将从事由教师指导的尖端研究项目， 在工程和生命科学方面的互补专业知识，并选择教学课程，以建立专业知识， 专业成长，发展社区。CHIP的前瞻性愿景解决了以下关键优先事项 它填补了目前跨学科培训方面的空白。 斯坦福大学CHIP利用一流的工程学院、医学院和 人文和科学。T32由一位物理工程师和一位工程生理学家共同指导， 带来了来自13个部门和部门的38名教师，重点是妇女和妇女以下， 代表少数民族。跨学科心血管研究所（CVI）和 斯坦福大学计算与数学工程研究所。学院将为学员提供 CV科学的研究机会，涵盖细胞到器官和实验室到床边，以及计算 科学、临床护理和治疗创新。教师是高度合作，并有特殊的 将受训人员投入独立的科学事业的记录。 申请人的选择和方案的所有方面都强调将代表性不足的 组受训人员不需要同时具有工程和生命科学背景。T32将 为工程师提供量身定制的CV科学教学，为生命科学研究员提供工程学，并提供先进的跨学科教学， 每个人都有自己的主题。核心教学法还包括道德、负责任的科学行为、 确保再现性。多样性，公平性和包容性是学员和教师的核心。评价将 在学员和教员之间既有建设性又是双向的。 总之，斯坦福大学的CHIP T32为后MD，后PhD和后MD/PhD毕业生提供 在生物工程，CV科学和医学的交叉领域提供世界一流的培训。T32定位良好 由于这些顶级资源在硅谷的单一校园中的共同定位， 数据科学、人工智能和治疗的创新。我们的理想目标是CHIP毕业生 将成为工程学、生理学和医学领域的全球科学领导者。