CTSA Graduate Program

CTSA研究生计划

基本信息

  • 批准号:
    10396575
  • 负责人:
  • 金额:
    $ 91.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-05-01 至 2023-07-31
  • 项目状态:
    已结题

项目摘要

The success of the biomedical research enterprise depends upon a robust pipeline of scientists with diverse expertise, well-trained in the core competencies of clinical and translational science (CTS). Major threats to this pipeline include the mismatch between the needs of the modern research workforce and the narrow training received in most biomedical PhD programs. Additionally, clinicians face an increasingly difficult transition to stable career development funding without rigorous research training. For almost two decades, the Tufts Sackler CTS Graduate Program, the training core of Tufts CTSI, has successfully trained clinician-scientists across the spectrum of translational research, emphasizing later stages of translation (T2-T4) with a broad impact on health. With this CTSA renewal, we will substantially expand and enhance our TL1 Program commensurate to the growth of Tufts CTSI to meet the larger training needs, building on the history of excellence in our MS/PhD CTS Program, by the following aims: AIM 1) we will provide rigorous training in the core competencies of CTS to a diverse set of scholars, including more PhD-trained biomedical scientists. We will leverage the broadened partnerships of the Tufts CTSI, including the Tufts University Sackler School, the Jackson Laboratory, the Massachusetts Institute of Technology (MIT), and Northeastern University, and a strengthened connection to the Tufts Friedman School of Nutrition Science and Policy. AIM 2) we will expand the mentoring and research experiences to enhance the individual development plans of TL1 fellows and all CTS Graduate Program students. This will include offering four specialized TL1 tracks, emphasizing institutional strengths: Comparative Effectiveness Research; One Health; Drug and Device Development; Health Policy. We will also establish innovative research externships – based at partner institutions and around Boston’s rich biotech hub – and new seminars and studios on topics critical for success in the modern translational workforce, including stakeholder/community engagement, team science, rigor and transparency, academic-industry partnerships, and clinical trial innovations. We will equip clinician-scientists and biomedical PhD scientists with the skills and experience necessary to succeed in an environment that has shifted to broadly-engaged, team-based translational research.
生物医学研究事业的成功依赖于一支强大的科学家队伍,他们拥有不同的 专业知识,在临床和转化科学(CTS)的核心能力方面训练有素。对此的主要威胁 流水线包括现代研究劳动力的需求与狭隘的培训之间的不匹配 在大多数生物医学博士项目中获得。此外,临床医生面临着越来越困难的过渡到 无需严格的研究培训即可获得稳定的职业发展资金。近二十年来,塔夫特一家 塔夫茨CTSI的培训核心-萨克勒CTS研究生项目成功地培养了临床医生-科学家 横跨翻译研究的各个领域,强调翻译的后期阶段(T2-T4)和广泛的 对健康的影响。通过此次CTSA续订,我们将大幅扩展和增强我们的TL1计划 与Tuft CTSI的增长相称,以满足更大的培训需求,基于 在我们的硕士/博士CTS项目中的卓越表现,通过以下目标:目标1)我们将在 CTS的核心能力提供给一批不同的学者,包括更多受过博士培训的生物医学科学家。我们 将利用塔夫茨CTSI扩大的伙伴关系,包括塔夫茨大学萨克勒学院、 杰克逊实验室、麻省理工学院(MIT)和东北大学,以及 加强了与塔夫茨·弗里德曼营养科学和政策学院的联系。目标2)我们将进行扩张 指导和研究经验,以加强TL1研究员和ALL的个人发展计划 CTS研究生项目学生。这将包括提供四个专门的TL1曲目,强调 机构优势:比较有效性研究;同一健康;药物和器械开发; 卫生政策。我们还将建立创新的外部研究项目--在合作机构和周围 波士顿丰富的生物技术中心-以及关于现代科技成功关键主题的新研讨会和工作室 翻译员工队伍,包括利益相关者/社区参与、团队科学、严谨和透明度, 学术界和产业界的合作伙伴关系和临床试验创新。我们将装备临床医生-科学家和生物医学 拥有必要技能和经验的博士科学家,能够在一个已经转变为 广泛参与、基于团队的翻译研究。

项目成果

期刊论文数量(49)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Bayesian Decision Analysis: An Underutilized Tool in Veterinary Medicine.
ASO Author Reflections: Predicting Complications in Breast Cancer Surgery Using the BCSRc.
  • DOI:
    10.1245/s10434-021-09763-9
  • 发表时间:
    2021-09
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Jonczyk MM;Chatterjee A
  • 通讯作者:
    Chatterjee A
A Second Prone Dose Algorithm for Patients Undergoing Spinal Anesthesia During Thoracolumbar Surgeries.
针对胸腰椎手术期间接受脊髓麻醉的患者的第二种俯卧剂量算法。
  • DOI:
    10.1227/ons.0000000000000497
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wang,AndyY;Olmos,Michelle;Ahsan,Tameem;Kanter,Matthew;Liu,Penny;Balonov,Konstantin;Riesenburger,RonI;Kryzanski,James
  • 通讯作者:
    Kryzanski,James
A Novel Algorithm for Improving the Prehospital Diagnostic Accuracy of ST-Segment Elevation Myocardial Infarction.
一种提高 ST 段抬高型心肌梗死院前诊断准确性的新算法。
  • DOI:
    10.1017/s1049023x23006635
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    2.2
  • 作者:
    Goebel,Mat;Westafer,LaurenM;Ayala,StephanieA;Ragone,El;Chapman,ScottJ;Mohammed,MasoodR;Cohen,MarcR;Niemann,JamesT;Eckstein,Marc;Sanko,Stephen;Bosson,Nichole
  • 通讯作者:
    Bosson,Nichole
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DAVID M KENT其他文献

DAVID M KENT的其他文献

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{{ truncateString('DAVID M KENT', 18)}}的其他基金

CTSA Predoctoral T32 at Tufts University
塔夫茨大学 CTSA 博士前 T32
  • 批准号:
    10621977
  • 财政年份:
    2023
  • 资助金额:
    $ 91.99万
  • 项目类别:
Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): A Platform for Pragmatic Evidence Generation for Stroke and Dementia Prevention
人工智能检测隐性脑血管疾病(C2D2AI):中风和痴呆症预防的实用证据生成平台
  • 批准号:
    10591063
  • 财政年份:
    2023
  • 资助金额:
    $ 91.99万
  • 项目类别:
CTSA Postdoctoral T32 at Tufts University
塔夫茨大学 CTSA 博士后 T32
  • 批准号:
    10621976
  • 财政年份:
    2023
  • 资助金额:
    $ 91.99万
  • 项目类别:
CTSA Graduate Program
CTSA研究生计划
  • 批准号:
    10159335
  • 财政年份:
    2018
  • 资助金额:
    $ 91.99万
  • 项目类别:
CTSA Graduate Program
CTSA研究生计划
  • 批准号:
    9624034
  • 财政年份:
    2018
  • 资助金额:
    $ 91.99万
  • 项目类别:
Enabling Comparative Effectiveness Research in Silent Brain Infarction Through Natural Language Processing and Big Data
通过自然语言处理和大数据实现无症状脑梗塞的比较有效性研究
  • 批准号:
    9365110
  • 财政年份:
    2017
  • 资助金额:
    $ 91.99万
  • 项目类别:
Value of Personalized Risk Information
个性化风险信息的价值
  • 批准号:
    8796340
  • 财政年份:
    2014
  • 资助金额:
    $ 91.99万
  • 项目类别:
Value of Personalized Risk Information
个性化风险信息的价值
  • 批准号:
    8628511
  • 财政年份:
    2013
  • 资助金额:
    $ 91.99万
  • 项目类别:
An Online Searchable Field Synopsis of Clinical Prediction Models in Cardiovascular Disease
心血管疾病临床预测模型的在线可搜索领域概要
  • 批准号:
    9072292
  • 财政年份:
    2013
  • 资助金额:
    $ 91.99万
  • 项目类别:
Value of Personalized Risk Information
个性化风险信息的价值
  • 批准号:
    8742028
  • 财政年份:
    2013
  • 资助金额:
    $ 91.99万
  • 项目类别:

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