Core 1: Translational and Clinical Resource Core

核心 1:转化和临床资源核心

基本信息

项目摘要

ABSTRACT The Translational and Clinical Resource Core (TRAC Core) of the AACORT was developed to expedite the translation of the insight we have gained into alopecia areata (AA) pathogenesis from our GWAS and immunological studies into novel effective treatments. The TRAC Core will facilitate procurement of well-characterized, high quality human AA tissue samples, linked to multiple disease parameters including detailed clinical data, genetic data, immunologic and treatment response data. The TRAC core will provide guidance to foster seamless transition from study design and planning, procurement of biosamples and or data, through to the generation of experimental data, and then coordinate with the DATA Core for analyses. The TRAC core will facilitate investigator interface with the AA registry and the Columbia University Recruitment registry, and enable optimal collection and preservation of biosamples, as well as coordinate transport and processing of samples from distant sites. The core provides access to the National Alopecia Areata Registry Database, allowing access to almost 11,000 individuals who have given consent to be re-contacted for translational research in AA. We have also created our own Columbia University IRB approved database of patients in the NY metropolitan area with AA who wish to be contacted for participation in research. Additionally, the TRAC Core will provide data coordination and biostatistical expertise in the design of pre-clinical and clinical studies. The TRAC Core will provide patient ascertainment and procurement of AA tissue samples (skin/scalp, blood, feces, microbiome, immune cells) for the purpose of building an AA expression database from human and mouse models, which will be a critical resource that will be extensively utilized by each of the AACORT components. The TRAC Core resources will support the Research Project and Pilot and Feasibility studies, and interface closely with the DATA Core. In addition, the TRAC Core will promote communication and collaboration between preclinical and clinical researchers of AA, bridging the knowledge obtained from animal models to investigate the pathogenesis, immunopathology, and treatment of AA. By facilitating seamless access to biosamples from a well-defined patient population, and supporting researchers with services to enhance scientific rigor, the TRAC Core is positioned to facilitate the progress of translational investigation of AA pathophysiology and treatment.
摘要 AACORT的翻译和临床资源核心(TRAC核心)的开发旨在 加快翻译的见解,我们已经获得了斑秃(AA)的发病机制 从我们的GWAS和免疫学研究中转化为新的有效治疗方法。核心预算资源调拨目标将 促进获得表征良好的高质量人类AA组织样本,与 多种疾病参数,包括详细的临床数据、遗传数据、免疫学和 治疗反应数据。核心预算资源调拨目标核心资源将为促进无缝过渡提供指导 从研究设计和规划、生物样本和/或数据的采购,到 生成实验数据,然后配合DATA Core进行分析。的 TRAC核心将促进研究者与AA登记中心和哥伦比亚大学的联系 招募登记,并实现生物样本的最佳收集和保存,以及 协调来自遥远地点的样品的运输和处理。核心提供访问 国家斑秃登记数据库,允许访问近11,000人 已同意再次联系以进行AA的转化研究。我们还 创建了我们自己的哥伦比亚大学IRB批准的纽约大都会患者数据库 与AA谁希望被联系参与研究领域。此外,TRAC 核心将在临床前和临床试验设计中提供数据协调和生物统计专业知识。 临床研究。TRAC核心将为患者提供AA的确定和采购 用于构建目的的组织样本(皮肤/头皮、血液、粪便、微生物组、免疫细胞) 来自人类和小鼠模型的AA表达数据库,这将是一个关键资源 这将被AACOT的每一个组成部分广泛使用。TRAC核心资源 将支持研究项目和试点和可行性研究,并与 数据核心。此外,核心预算资源调拨目标核心资源将促进各组织之间的沟通与合作, AA的临床前和临床研究人员,桥接从动物模型获得的知识 探讨AA的发病机制、免疫病理学和治疗。通过促进 无缝访问来自明确定义的患者人群的生物样本,并支持 研究人员的服务,以提高科学的严谨性,TRAC核心定位,以促进 AA的病理生理学和治疗的转化研究进展。

项目成果

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Julian M. Mackay-Wiggan其他文献

Basal Cell Carcinoma: An Evidence-Based Treatment Update
  • DOI:
    10.1007/s40257-014-0070-z
  • 发表时间:
    2014-04-15
  • 期刊:
  • 影响因子:
    8.800
  • 作者:
    Charlotte M. Clark;Megan Furniss;Julian M. Mackay-Wiggan
  • 通讯作者:
    Julian M. Mackay-Wiggan

Julian M. Mackay-Wiggan的其他文献

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{{ truncateString('Julian M. Mackay-Wiggan', 18)}}的其他基金

Translational and Precision Medicine Resources Core (TRAP)
转化和精准医学资源核心 (TRAP)
  • 批准号:
    9324141
  • 财政年份:
  • 资助金额:
    $ 30.78万
  • 项目类别:
Translational and Precision Medicine Resources Core (TRAP)
转化和精准医学资源核心 (TRAP)
  • 批准号:
    9087993
  • 财政年份:
  • 资助金额:
    $ 30.78万
  • 项目类别:
Translational and Precision Medicine Resources Core (TRAP)
转化和精准医学资源核心 (TRAP)
  • 批准号:
    9765065
  • 财政年份:
  • 资助金额:
    $ 30.78万
  • 项目类别:

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