A UK Quantitative Systems Pharmacology Network

药物开发是一个耗时且昂贵的过程。从一种化合物被确定为具有可能的治疗益处到在临床上可用，不仅需要十年的时间，而且需要数百万英镑的投资。在实验室中成功测试一种化合物并不意味着它将在动物或人体试验中成功，即使成功的动物试验也可能导致人体试验的失败-这是生物学在不同尺度上的复杂性的结果。平均而言，只有九分之一的药物化合物得到美国和欧洲监管机构的充分开发和批准。这种低流失率对制药公司来说是不好的，无论是在时间和成本方面，最终对我们这个社会也是不好的。鉴于个体差异，对单细胞规模的理解并不容易转化为对人体组织、器官、整个人类和整个人群的相同行为。我们希望设计用于大规模人群使用的药物，同时考虑人群中个体之间的差异。我们可以用来解决这一问题的一种技术是定量方法，如机械数学建模和数据分析。生物系统的现有知识可用于开发数学模型，以确定关键的实验室实验，减少对动物的依赖，并更早地确定哪些化合物最有可能失败或成功。将亚细胞信息整合到整个个体的机械数学模型中，以专门帮助药物治疗学的发展，被称为定量系统药理学（QSP）。“定量”是因为该领域使用定量的过程和数据来进行预测，“系统”是因为该方法在整个系统中是整体的（单个细胞到器官到整个个体）。这是一个新的科学领域，需要理论建模者（数学家，统计学家，工程师）与生命和制药科学家之间的强有力的互动，以确保其成功。来自这些领域的研究人员可以在英国的学术机构和领先的生物制药和生物技术部门找到，并需要聚集在一起，让这个新领域在英国蓬勃发展。为了满足这一需求，我们将在QSP建立一个英国网络。该网络将汇集来自工业界和学术界的英国制药科学家，以及理论科学家，以交流知识并解决QSP中的问题。该网络将围绕三个研讨会（每年一个）进行安排，其中两个将通过关于这一新兴领域关键主题的讲座，海报会议和小组讨论来分享知识。第三个讲习班将利用数学建模专门知识，解决学术界和工业界网络成员强调的快速启动方案问题。卫星会议将使与会者能够进一步探讨主要研讨会产生的想法。我们的网络已经得到了来自生物制药和生物技术领域的大力支持，在英国设有站点，并拥有领先的学术机构。该网络将导致：（一）新的合作;（二）项目申请（三）科学出版物;（四）开放获取数学模型及其相关代码;（五）提高联合王国制药、生命和物理科学界对快速启动方案的认识;（六）为工业界人员提供教育和培训（七）提高公众对快速启动方案在开发新药和治疗剂方面的认识;（viii）促进数学模型的发展，作为目前用于推断药物功效和毒性反应的离体和体内动物系统的替代物;以及（ix）发展和加强英国与其他主要国际系统药理学研究倡议之间的国际联系。

Drug development is a time consuming and expensive process. From the time a compound is identified as having possible therapeutic benefits through to being available in the clinic, takes not only the order of a decade, but 100's of millions of pounds of investment. Successful testing of a compound in the laboratory does not imply that it will be successful in animal or human trials, and even successful animal tests can lead to failure in human trials - a result of the complexity of biology at different scales. On average only one in nine drug compounds is fully developed and approved by US and European regulatory authorities. This low attrition rate is poor for drug companies, both in terms of time and costs, and ultimately us as a society.Understanding on the single cell scale does not easily translate to the same behaviour in human tissue, organs, whole humans and the overall population given individual differences. We wish to design drugs for large scale population use whilst accounting for the variation between individuals within a population. One technology available to us for tackling this issue is quantitative methods such as mechanistic mathematical modelling and data analysis. Current knowledge of a biological system can be used to develop mathematical models to identify key laboratory experiments, reduce reliance on animals and identify earlier which compounds are most likely to fail or succeed. The integration of subcellular information into whole individual mechanistic mathematical models to specifically assist in the development of pharmaco-therapeutics has been termed Quantitative Systems Pharmacology (QSP). "Quantitative" because the area uses quantitated processes and data to make predictions and "Systems" because the approach is holistic across the system (single cell to organ to whole individual). This is a new area of science which will require strong interactions between theoretical modellers (mathematicians, statisticians, engineers) and life and pharmaceutical scientists to ensure its success. Individual researchers from each of these areas can be found in both UK academic institutions and leading biopharmaceutical and biotechnology sectors and need to be brought together to allow this new field to thrive and develop in the UK.To meet this need we will establish a UK Network in QSP. The network will bring together UK pharmaceutical scientists from industry and academia, with theoretical scientists to exchange knowledge and tackle problems in QSP. The network will be arranged around three workshops (one per year), two of which will share knowledge through talks, poster sessions and group discussion on key topics in this burgeoning field. A third workshop will bring mathematical modelling expertise to bear on QSP problems highlighted by the academic and industrial network members. Satellite meetings will allow participants to further explore ideas generated from the main workshops. Our network already has strong support from biopharmaceutical and biotechnology sectors, with sites in the UK, and leading academic institutions. The network will lead to: (i) new collaborations; (ii) project applications (grant, studentship, fellowship); (iii) scientific publications; (iv) open access mathematical models and their associated code; (v) greater awareness of QSP in the UK pharmaceutical, life and physical science communities; (vi) education and training for those based in industry (and academia) on modelling tools and techniques to support; (vii) greater public awareness of QSP in the development of new drugs and therapeutic agents; (viii) foster the development of mathematical models as surrogates for the ex-vivo and in-vivo animal systems currently used to extrapolate efficacy and toxicity responses to drugs; and (ix) develop and strengthen international links between the UK and other key international initiatives in Systems Pharmacology research.