Pharmacometabolomics Research Network

药物代谢组学研究网络

• 批准号: 7935819
• 负责人: Rima F Kaddurah-Daouk
• 金额: $ 7.8万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-15 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7935819
• 关键词: Achievement; Address; Adverse reactions; Affect; Alberta province; Animal Model; Animals; Antihypertensive Agents; Area; Atherosclerosis; Award; Biochemical; Biochemical Pathway; Biochemistry; Bioinformatics; Biological; Biological Assay; Biological Markers; Biological Models; Biomedical Research; Body Fluids; Cardiovascular system; Cell Culture System; Cell Line; Cells; Clinical; Communities; Complement; Complex; DNA Resequencing; Data; Data Analyses; Databases; Detection; Development; Diagnosis; Discipline; Disease; Drug Exposure; Drug Monitoring; Drug effect disorder; Drug usage; Electrochemistry; Environment; Enzymes; Florida; Foundations; Future; Gene Expression; Generations; Genes; Genetic Polymorphism; Genome; Genomics; Genotype; Glucose; Goals; Health Status; Heart; Hypertension; Inborn Errors of Metabolism; Individual; Informatics; Injury; Institution; Interdisciplinary Study; Investments; Knowledge; LDL Cholesterol Lipoproteins; Maps; Mass Spectrum Analysis; Measures; Medical; Mental Depression; Metabolic; Mind; Modeling; Molecular; NIH Program Announcements; Non-Insulin-Dependent Diabetes Mellitus; Pathway Analysis; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Pharmacology; Pharmacotherapy; Phenotype; Physicians; Pilot Projects; Plasma; Play; Prevention; Principal Investigator; Process; Proteins; Proteomics; Public Health; Reaction; Research; Resources; Role; Sampling; Science; Screening procedure; Selective Serotonin Reuptake Inhibitor; Series; Spectrometry; System; Techniques; Technology; Testing; Therapeutic; Tissues; Translating; United States National Institutes of Health; Validation; Variant; Washington; Wisconsin; base; cardiovascular disorder risk; clinical practice; drug development; drug discovery; drug mechanism; drug metabolism; functional genomics; human disease; human subject; member; metabolomics; microbiome; neuropsychiatry; organizational structure; prevent; protein expression; public health relevance; repository; response; small molecule; tool; transcriptomics; virtual

DESCRIPTION (provided by applicant): This proposal represents a response to Program Announcement PAR-07-412 "Preapplication for Large- Scale Collaborative Project Award ". The applicants propose to create an interdisciplinary research consortium with the goal of integrating the rapidly evolving science of metabolomics with molecular pharmacology and pharmacogenomics to move toward the creation of a new discipline - "Pharmacometabolomics" a discipline that will transform our ability to individualize therapy. Specifically, we propose the formation of a multi-institution research consortium involving centers of excellence in metabolomics and metabolomic bioinformatics, joined with centers of excellence in molecular pharmacology and pharmacogenomic science. The purpose is to create an environment in which a cooperative iterative process of hypothesis generation, testing, and validation will be applied to achieve the union of metabolomic and pharmacologic science to create "Pharmacometabolomics". Achievement of that goal would have the potential to dramatically accelerate advances in our understanding of mechanisms of disease, drug action, and variation in response to therapy. It would provide a treating physician with knowledge and biomarkers that can reduce an inadequate trial-and-error process in selecting the right drug for each patient. Through a partnership with members of the Pharmacogenetics Research Network and leveraging large investments already made by NIH we plan to employ metabolomic analyses to study drug response phenotypes by using prototypic drugs used to treat cardiovascular and neuropsychiatric disease as "testbeds" for the development and application of Pharmacometabolomics. That process will generate broadly based, biochemically precise "metabolomic signatures" to complement and extend the clinical response phenotypes currently being used to select drugs and monitor drug therapy and also to complement and extend genomic, transcriptomic and proteomic information with regard to drug response. This process would result in the generation of new hypotheses that will be tested in experimental animal and cultured cell systems - leading, in turn, to new translational hypotheses to which metabolomic analyses could also be applied. The ultimate goal of the proposed research consortium would be the creation of an environment in which it will be possible to develop Pharmacometabolomics as a truly "interdisciplinary" biomedical discipline that can contribute to a "Systems Pharmacology" approach to the study of drug effects leading to a more personalized approach to therapy. PUBLIC HEALTH RELEVANCE: Pharmacometabolomics is the application of metabolomic science to understand drug effect and variation in drug response phenotypes. A "Therapeutic Revolution" has transformed modern drug therapy. Therefore, it is increasingly important that we understand which patients might best respond to drug therapy without suffering adverse drug reactions. Creation of the Pharmacometabolomics Research Network proposed in this application would have a significant public health impact by helping make it possible to better understand and individualize drug therapy.

描述（由申请人提供）：本建议书是对计划公告PAR-07-412“大型合作项目奖预申请”的回应。申请人建议创建一个跨学科研究联盟，其目标是将快速发展的代谢组学科学与分子药理学和药物基因组学相结合，以创建一个新的学科-“药物代谢组学”，该学科将改变我们的个性化治疗能力。具体而言，我们建议成立一个多机构研究联盟，包括代谢组学和代谢组学生物信息学的卓越中心，与分子药理学和药物基因组学的卓越中心联合。其目的是创造一个环境，在其中一个合作的假设生成，测试和验证的迭代过程将被应用到实现代谢组学和药理学科学的联盟，创造“药物代谢组学”。这一目标的实现将有可能大大加快我们对疾病机制、药物作用和治疗反应变化的理解。它将为治疗医生提供知识和生物标志物，可以减少为每个患者选择正确药物的不充分的试错过程。通过与药物遗传学研究网络成员的合作，并利用NIH已经进行的大量投资，我们计划采用代谢组学分析，通过使用用于治疗心血管和神经精神疾病的原型药物作为药物代谢组学开发和应用的“试验台”来研究药物反应表型。这一过程将产生基础广泛的、生物化学上精确的“代谢组学特征”，以补充和扩展目前用于选择药物和监测药物治疗的临床反应表型，并补充和扩展与药物反应有关的基因组、转录组和蛋白质组信息。这一过程将导致产生新的假设，这些假设将在实验动物和培养的细胞系统中进行测试，进而导致新的翻译假设，代谢组学分析也可以应用于这些假设。拟议的研究联盟的最终目标将是创造一个环境，在这个环境中，将有可能发展药物代谢组学作为一个真正的“跨学科”生物医学学科，可以有助于“系统药理学”的方法来研究药物的影响，从而导致一个更个性化的治疗方法。 公共卫生关系：药物代谢组学是应用代谢组学来了解药物效应和药物反应表型的变化。一场“治疗革命”改变了现代药物治疗。因此，我们了解哪些患者对药物治疗反应最好，而不会发生药物不良反应，这一点越来越重要。本申请中提出的药物代谢组学研究网络的创建将有助于更好地理解和个性化药物治疗，从而对公共卫生产生重大影响。