Network Based Predictive Drug Discovery for Alzheimer's Disease

基于网络的阿尔茨海默病预测药物发现

• 批准号: 8849718
• 负责人: Joel Thomas Dudley
• 金额: $ 36.65万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8849718
• 关键词: Alzheimer' s Disease; Animal Model; Animals; Area; Bioinformatics; Biological; Biological Markers; Biological Models; Cells; Charge; Chemicals; Clinical; Clinical Drug Development; Clinical Trials; Collaborations; Combined Modality Therapy; Communication; Complement; Complex; Computer Analysis; Computer Simulation; Core Assembly; Core Facility; Data; Data Collection; Databases; Detection; Development; Doctor of Medicine; Doctor of Philosophy; Educational Curriculum; Educational workshop; Ensure; Environment; Failure; Foundations; Frequencies; Friends; Generations; Genetic; Genome; Goals; Grant; Human; Immunofluorescence Immunologic; Intervention; Investigation; Legal; Maps; Medicine; Methods; Modeling; Molecular; Network-based; Organ; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacodynamics; Pharmacology; Physiological; Process; Proteome; Protocols documentation; Publications; Research; Research Personnel; Sampling; Science; Services; Site Visit; Staging; System; Systems Biology; Technology; Therapeutic; Training; Training and Education; Validation; Variant; Writing; base; biochemical model; cloud based; data sharing; design; drug discovery; member; neuroimaging; open source; patient population; pre-clinical; public health relevance; response; small molecule; symposium; therapeutic target; tool

 DESCRIPTION (provided by applicant): The purpose of the R34 planning grant is to support the effort, conferences, site visits, and other fact-finding processes involved in designing the translational center, Systems Medicine Drug Discovery for Alzheimer's disease. This Center will include Core Facilities charged with providing key technology services and Pathway/Drug-Based Projects that will focus on specific molecular mechanisms and/or predicted pharmacological interventions. Project leaders will be responsible for moving each project (target pathway, drug) through the relevant cores with maximum efficiency. Pathways and projects will undergo continual reassessment of priorities. The goals of the planning period are as follows: (Specific Aim 1) To assemble a team of investigators with appropriate expertise and to develop the most efficient strategy for their productive communication and collaboration; (Specific Aim 2) To develop a plan for generation and exploitation of diverse genetic and omic data collected in humans and various animal models to identify translatable pharmacodynamic biomarkers and enable modeling of drug response determinants in distinct patient populations; (Specific Aim 3) To develop a plan for establishment of multi-scale computational models of pharmacological mechanism, that bridges the divide between cell-level biochemical models and organism-level PK/PD and neuroimaging models; (Specific Aim 4) To plan the most efficient strategy for target validation that will involve conducting quantitative analysis of the effects of small molecules and biologics on therapeutic targets across multiple scales of biological complexity; (Specific Aim 5) To plan the most effective strategy for investigation of the molecular and physiological origins of variability in drug response at the single-cell, organ, and patient level that arises from differences at the level of the proteome, genome and environment; (Specific Aim 6) To develop systems approaches for comprehensive and systematic failure analysis during preclinical and clinical drug development; (Specific Aim 7) To develop the most efficient strategy for rapid and broad sharing of data, analytical and research tools, and models prior to publication; (Specific Aim 8) To ensure open source data enablement and to develop strategies for removing legal/IP barriers to sharing data, biological samples and research tools; (Specific Aim 9) To develop curricula, workshops and seminars for training in systems biology, systems pharmacology, pharmacometrics, PK/PD modeling, omics technologies, translational bioinformatics and other quantitative science areas; (Specific Aim 10) To provide short term training for junior staff and short term sabbaticals for senior team members to expand existing expertise or develop new expertise essential for achieving the programmatic goals of the translational center(s) initiative. Within the planning year, the R34 investigators predict that these Aims will be achieved and that the foundation will have been laid for writing the center proposal.

 描述（由申请人提供）：R34规划补助金的目的是支持设计翻译中心，阿尔茨海默病系统医学药物发现所涉及的努力，会议，现场访问和其他事实调查过程。该中心将包括核心设施，负责提供关键技术服务和途径/基于药物的项目，这些项目将侧重于特定的分子机制和/或预测的药理学干预。项目负责人将负责以最高效率将每个项目（靶向途径、药物）转移到相关核心。途径和项目的优先次序将不断得到重新评估。规划期间的目标如下：（具体目标1）组建一支具有适当专门知识的调查员队伍，并为他们的有效沟通和协作制定最有效的战略;（具体目标2）制定一项计划，用于生成和利用在人类和各种动物模型中收集的各种遗传和组学数据，以识别可翻译的药效学生物标志物，并建立药物模型不同患者人群中的反应决定因素;（具体目标3）制定建立药理学机制的多尺度计算模型的计划，弥合细胞水平生化模型与生物体水平PK/PD和神经影像学模型之间的鸿沟;（具体目标4）制定最有效的靶标验证策略，包括对 小分子和生物制剂在多个生物复杂性尺度上的治疗靶点;（具体目标5）计划最有效的分子研究策略 以及在单细胞、器官和患者水平的药物反应的变异性的生理学起源，其产生于蛋白质组、基因组和环境水平的差异;（具体目标6）开发系统方法，用于临床前和临床药物开发期间的全面和系统的故障分析;（具体目标7）制定最有效的战略，以便在出版前迅速和广泛地分享数据、分析和研究工具以及模型;（具体目标8）确保开放源数据的实现，并制定战略，消除共享数据、生物样本和研究工具的法律的/知识产权障碍;（具体目标9）为系统生物学、系统药理学、药物计量学、PK/PD建模、组学技术、转化生物信息学和其他定量科学领域;（具体目标10）为初级员工提供短期培训，为高级团队成员提供短期休假，以扩展现有专业知识或开发实现转化中心计划目标所必需的新专业知识。在规划年内，R34研究人员预测这些目标将实现，并为编写中心提案奠定基础。