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Applying a systems pharmacology approach to understanding glucagon-like peptide 1 receptor signalling bias

应用系统药理学方法了解胰高血糖素样肽 1 受体信号传导偏差

基本信息

批准号：
1643678
负责人：
金额：
--
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1643678
关键词：
Applying systems pharmacology approach understanding

项目摘要

The development of new efficacious drugs is a major challenge to the pharmaceutical industry. Despite continued improvements in production, costs continue to increase, while the number of approved drugs declines. This has been particularly evident in the development of drugs aimed at G protein-coupled receptors (GPCRs), a leading pharmaceutical target. Consequently, new approaches are required. Systems pharmacology (SP) is an emerging discipline combining mathematical and computational techniques to provide a more holistic view of pharmacology. Here we propose to, for the first time, develop and apply SP approaches to quantitatively model dose-dependent time-course data derived from GPCR signal transduction, specifically the Glucagon-like peptide 1 (GLP1) receptor. Only through producing the most quantitatively accurate models of GPCR signalling may we eventually be able to use computers to predict how drugs will react when administered to the general population. Generating quantitative models of GPCR signalling requires high quality, reproducible time-course data coupled to the ability to estimate, with absolute confidence, parameters that cannot be measured directly. SP approaches will allow us to perform these types of analyses. Biological data will be obtained using a range of robust second messenger assays for the GLP1 receptor obtained from mammalian cells. Computationally, we will utilise structural identifiability analysis to ascertain the uniqueness of the unknown model parameters, ensuring that our parameter estimation is as robust as possible. The true strength of our approach is the synergy between 'wet' experiments and 'dry' modelling, ensuring that the most appropriate experiments are performed.

开发新的有效药物是制药业面临的一个重大挑战。尽管生产不断改善，但成本继续增加，而批准的药物数量却在下降。这在针对G蛋白偶联受体（GPCR）（一种主要的药物靶点）的药物开发中尤其明显。因此，需要采取新的办法。系统药理学（SP）是一门新兴的学科，结合数学和计算技术，以提供更全面的药理学观点。在这里，我们建议，第一次，开发和应用SP的方法来定量模型的剂量依赖性的时间过程数据来自GPCR信号转导，特别是胰高血糖素样肽1（GLP 1）受体。只有通过产生最精确的GPCR信号模型，我们最终才能使用计算机来预测药物在一般人群中的反应。生成气相化学还原信号的定量模型需要高质量、可再现的时程数据，同时还需要有能力以绝对的置信度估计无法直接测量的参数。SP方法将允许我们执行这些类型的分析。将使用一系列从哺乳动物细胞中获得的GLP 1受体的稳健第二信使测定法获得生物学数据。在计算上，我们将利用结构可识别性分析来确定未知模型参数的唯一性，确保我们的参数估计尽可能稳健。我们方法的真正优势在于“湿”实验和“干”建模之间的协同作用，确保执行最合适的实验。