A UK Quantitative Systems Pharmacology Network

英国定量系统药理学网络

• 批准号: EP/N005481/1
• 负责人: Marcus Tindall
• 金额: $ 20.32万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 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=EP%2FN005481%2F1
• 关键词: UK; Quantitative; Systems; Pharmacology; Network

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.

药物开发是一个既耗时又昂贵的过程。从一种化合物被确定具有可能的治疗效果到可以在临床上使用，不仅需要十年的时间，而且需要数亿英镑的投资。在实验室中成功测试一种化合物并不意味着它在动物或人体试验中就会成功，即使是成功的动物试验也可能导致人体试验的失败--这是由于不同规模的生物学的复杂性造成的。平均而言，每九种药物化合物中只有一种得到了美国和欧洲监管机构的全面开发和批准。这种低流失率对制药公司来说是不利的，无论是在时间和成本方面，还是最终对我们整个社会来说都是不利的。考虑到个体差异，在单细胞尺度上的理解不容易在人类组织、器官、整个人类和整个人口中转化为相同的行为。我们希望设计适合大规模人群使用的药物，同时考虑到人群中不同个体之间的差异。我们可用来解决这一问题的一种技术是定量方法，如机械论数学建模和数据分析。目前对生物系统的了解可以用来开发数学模型，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。将亚细胞信息集成到整个个体机械数学模型中，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”是因为该领域使用量化的过程和数据来进行预测，而“系统”是因为这种方法是整个系统的整体(从单个细胞到器官再到整个个体)。这是一个新的科学领域，需要理论建模人员(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，以确保它的成功。在英国的学术机构和领先的生物制药和生物技术行业都可以找到来自这些领域的个人研究人员，他们需要团结起来，使这一新领域在英国蓬勃发展。为了满足这一需求，我们将在QSP中建立一个英国网络。该网络将把来自工业界和学术界的英国制药科学家与理论科学家聚集在一起，交流知识并解决QSP方面的问题。该网络将安排大约三个讲习班(每年一个)，其中两个讲习班将通过演讲、海报会议和关于这一新兴领域关键主题的小组讨论来分享知识。第三期讲习班将利用数学建模专业知识解决学术和工业网络成员所强调的合格标准物质问题。卫星会议将使与会者能够进一步探讨主要讲习班产生的想法。我们的网络已经得到了生物制药和生物技术部门的大力支持，在英国设有办事处，以及领先的学术机构。该网络将导致：(1)新的合作；(2)项目申请(补助金、奖学金、研究金)；(3)科学出版物；(4)开放获取数学模型及其相关代码；(5)提高英国医药、生命和物理科学界对QSP的认识；(6)对工业界(和学术界)的人员进行关于建模工具和支持技术的教育和培训；(7)提高公众对QSP在开发新药和治疗剂方面的认识；(Viii)促进开发数学模型，作为目前用于推断药物的疗效和毒性反应的体外和体内动物系统的替代品；以及(Ix)发展和加强英国与系统药理学研究方面的其他关键国际倡议之间的国际联系。

项目成果

A pharmacokinetic-pharmacodynamic model for chemoprotective agents against malaria.

• DOI: 10.1002/psp4.12875
• 发表时间: 2023-01
• 期刊: CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY
• 影响因子: 3.5
• 作者: Cherkaoui-Rbati, Mohammed H.;Andenmatten, Nicole;Burgert, Lydia;Egbelowo, Oluwaseun F.;Fendel, Rolf;Fornari, Chiara;Gabel, Michael;Ward, John;Mohrle, Jorg J.;Gobeau, Nathalie
• 通讯作者: Gobeau, Nathalie

Modeling bispecific monoclonal antibody interaction with two cell membrane targets indicates the importance of surface diffusion.

• DOI: 10.1080/19420862.2016.1178437
• 发表时间: 2016-07
• 期刊: mAbs
• 影响因子: 5.3
• 作者: Sengers BG;McGinty S;Nouri FZ;Argungu M;Hawkins E;Hadji A;Weber A;Taylor A;Sepp A
• 通讯作者: Sepp A