Network Based Predictive Drug Discovery for Alzheimer's Disease

 描述(由申请人提供)：R34计划拨款的目的是支持在设计阿尔茨海默病系统药物发现翻译中心时所涉及的努力、会议、实地考察和其他事实调查过程。该中心将包括负责提供关键技术服务的核心设施和将侧重于特定分子机制和/或预测的药理学干预的途径/药物项目。项目负责人将负责将每个项目(靶向途径、药物)以最高效率通过相关的核心。路径和项目将不断地重新评估优先事项。规划期的目标如下：(具体目标1)组建一支具有适当专业知识的研究人员团队，为他们的生产性交流和协作制定最有效的战略；(具体目标2)制定一项计划，以生成和利用在人类和各种动物模型中收集的各种遗传和基因组数据，以确定可翻译的药效学生物标记物，并能够在不同的患者群体中对药物反应决定因素进行建模；(具体目标3)制定一项计划，以建立多尺度的药理机制计算模型，以弥合细胞一级生化模型和生物体一级PK/PD和神经成像模型之间的分歧；(具体目标4)规划最有效的目标确认战略，这将涉及对以下方面的影响进行量化分析 跨越多种生物复杂性的治疗靶点上的小分子和生物制品；(具体目标5)规划最有效的分子研究战略 由蛋白质组、基因组和环境水平的差异引起的单细胞、器官和患者一级药物反应差异的生理根源；(具体目标6)为临床前和临床药物开发期间全面和系统的失效分析开发系统方法；(具体目标7)制定在出版前快速和广泛共享数据、分析和研究工具和模型的最有效战略；(具体目标8)确保开放源码数据的实现，并制定战略，消除共享数据、生物样本和研究工具的法律/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、翻译生物信息学和其他定量科学领域的培训制定课程、讲习班和研讨会；(具体目标10)为初级工作人员提供短期培训，为高级团队成员提供短期休假，以扩大现有专业知识或开发实现翻译中心计划目标所必需的新专业知识(S)。在规划年内，R34调查人员预测这些目标将会实现，并为撰写中心提案奠定基础。

 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.