The HMS Laboratory of Systems Pharmacology

HMS 系统药理学实验室

基本信息

批准号：
8769531
负责人：
PETER Karl SORGER
金额：
$ 234.61万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-01 至 2019-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8769531
关键词：
Address Advisory Committees Area Asthma Biochemistry Biological Sciences Biology Boston Cell Line Cell model Cells Cellular biology Chemicals Clinical Clinical Data Combined Modality Therapy Communities Complex Computational Biology Custom Data Development Discipline Disease Doctor of Philosophy Dose Drug Industry Drug Kinetics Drug Targeting Drug effect disorder Education Education and Outreach Educational workshop Engineering Environment Faculty Failure Fellowship Fibrosis Frequencies Funding Genomics Genotype Goals Government Grant Health Hospitals Housing Individual Industry Inflammatory Institution International Kinetics Knowledge Laboratories Lead Life Link Lung Machine Learning Measurement Measures Medical Medicine Methods Mining Modeling Molecular Molecular Biology Mus New Drug Approvals Organism Patients Pharmaceutical Chemistry Pharmaceutical Preparations Pharmacodynamics Pharmacologic Substance Pharmacology Pharmacology and Toxicology Phosphotransferases Physicians Physiological Physiology Population Postdoctoral Fellow Price Productivity Proteins Qualifying Reaction Time Records Reproducibility Research Research Personnel Research Project Grants Resistance Resolution Role Sampling Science Scientist Signal Transduction Societies Staging Structure Students System Systems Biology Therapeutic Therapeutic Index Time Tissues Translational Research Translations Underserved Population Variant Whole Organism Work advanced system base cancer type cell type cellular imaging cost design drug development drug discovery drug distribution extracellular improved innovation insight intravital imaging kinase inhibitor man mathematical model meetings member multi-scale modeling novel novel strategies novel therapeutics outreach outreach program pharmacodynamic model pharmacokinetic model programs receptor response success symposium theories tool translational medicine tumor xenograft web site young woman

项目摘要

PROJECT SUMMARY Systems and computational biologists, physician-scientists, pharmacologists, biochemists and cell biologists will collaborate in a new Laboratory of Systems Pharmacology (LSP) to apply a measure-model approach to understanding the mechanisms of action of therapeutic drugs in multiple disease areas. The LSP will pioneer the development of quantitative network-centric approaches to pharmacology and toxicology that include analysis of dose-time-response relationships at a single-cell level, modeling of cellular network dynamics and their perturbation by drugs, development of pharmacokinetic and pharmacodynamic models in mouse and ultimately in man and use of systematic approaches to identify and qualify new drug targets. Our approach combines mathematical modeling with empirical measurement (including work with clinical samples and data) and aims to create quantitative and predictive drug response models at different temporal and physical scales. We aim to reinvigorate pharmacology and toxicology as foundational disciplines of translational medicine, develop the conceptual underpinning for personalized and precision medicine and lower the cost of drug discovery by improving its predictability. Close interactions with industry and the FDA will help address the productivity gap in drug discovery and development. The LSP is innovative with respect to its goal of using problems in basic and translational pharmacology to link three disciplines (cell and molecular biology, computational biology and medicine) and its aim of advancing therapeutic science in the Boston area and beyond. Students and postdocs supervised by 18 faculty members, 2 independent postdoctoral fellows and two PhD-level staff from 7 institutions will work in immediate proximity in a new custom-designed laboratory. The lab will host a new graduate program in therapeutics and multi-factored outreach activities that will promote systems pharmacology internationally. These goals will be achieved through four inter-linked research programs (Aims 1-4), a core dedicated to efficient translation of LSP research (Aim 5), an education core and administrative/outreach activities (Aims 6-8). Aim 1 will focus on the determinants of dose-response at a single-cell level, including the role of cell-to-cell variability in fractional response and of timing and order-of-exposure in combination therapy. Aim 2 will take a network-level approach to understanding therapeutic, toxic and paradoxical drug responses by kinase inhibitors in three types of cancer. The mechanistic basis and consequences of poly-pharmacology will also be examined along with differential drug responsiveness by normal and diseased tissues. Aim 3 will address PK-PD by developing multi-scale models of drug actions at the level of cells, tissues and organisms and new methods for measuring drug distribution at the cellular and subcellular levels. Aim 4 will apply machine learning and causal reasoning to target discovery from clinical records in asthma, inflammatory disease and fibrosis and pursue a structure-guided approach to identifying regulators of "undruggable " targets.

项目摘要系统和计算生物学家，医师科学家，药物学家，生物化学家和细胞生物学家将在新的系统药理学实验室（LSP）中合作，以采用测量模型方法来了解多种疾病领域治疗药物的作用机理。 LSP将开发用于药理学和毒理学的定量网络方法的开发，包括分析单单元水平上的剂量时间 - 反应关系，对细胞网络动态的建模及其通过药物扰动的建模，在小鼠中的药代动力学和药态动力学模型的开发，以及在男子中的最终和使用系统的药物来确定和有资格的新药。我们的方法将数学建模与经验测量（包括使用临床样本和数据的工作）结合在一起，旨在在不同的时间和物理尺度上创建定量和预测性药物反应模型。我们旨在作为转化医学的基础学科，振兴药理学和毒理学，为个性化医学和精确医学开发概念上的基础，并通过提高其可预测性来降低药物发现成本。与行业和FDA的紧密互动将有助于解决药物发现和开发中的生产力差距。 LSP在其在基本和转化药理学中使用问题的目标具有创新性，以将三个学科（细胞和分子生物学，计算生物学和医学）联系起来及其在波士顿地区及其他地区推进治疗科学的目的。由18名教职员工监督的学生和博士后，2名独立的博士后研究员和来自7家机构的两名博士学位员工将立即在一个新的定制设计的实验室中立即工作。该实验室将举办一项新的治疗和多重外展活动研究生课程，该计划将在国际上促进系统药理学。这些目标将通过四个相互联系的研究计划（AIMS 1-4）实现，该计划致力于有效地翻译LSP研究（AIM 5），一种教育核心和行政/外展活动（AIMS 6-8）。 AIM 1将集中于单细胞水平上剂量反应的决定因素，包括细胞间变异性在分数反应中的作用以及组合治疗中的时间和暴露顺序。 AIM 2将采用网络级别的方法来理解三种癌症中激酶抑制剂的治疗，有毒和矛盾的药物反应。还将通过正常组织和患病组织来检查多种药理学的机械基础和后果。 AIM 3将通过在细胞，组织和生物的水平上开发多尺度的药物作用模型以及测量细胞和亚细胞水平药物分布的新方法来解决PK-PD。 AIM 4将将机器学习和因果推理应用于哮喘，炎症性疾病和纤维化中的临床记录中的发现，并采用结构引导的方法来识别“不可能”目标的调节剂。