The Optimal Deployment of Antibiotics: Whether, How and When to Switch

抗生素的最佳配置：是否、如何以及何时切换

• 批准号: G0802611/1
• 负责人: Robert Beardmore
• 金额: $ 11.46万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0802611%2F1
• 关键词: Optimal; Deployment; Antibiotics; Whether; How

Optimal control is a term used to describe the research that made much of the space-race possible. Neil Armstrong s moon landing was made possible by understanding how to manipulate a space rocket with minimal fuel expenditure. The idea behind this work is to take the same basic engineering science and to apply it by asking whether the evolution of resistance that blights antibiotic treatments can be somehow minimised by understanding how to deploy those antibiotics in an optimal way.We can already do this, in theoretical terms, and we are able to create weird and wonderful ways of deploying antibiotic to a biological system in order to maximise its health. However, a lot of biological theory based on mathematical modeling has been proposed in the past that turned out to be plain wrong when the right experiments were done. This is especially true of population biology, the branch of biology that treats interacting populations of organisms such as microbes and other cells. Now, the mathematical modeling in this work is a mix of population biology, cell biology and genetics; while space researchers have Newton s laws to lean on, population biology has no intrinsic, physical laws. As a result, it is sometimes a feature of the field that theoretical concepts stick before they are truly tested. So, we want to test our theories to destruction to make sure they work in the lab before we eventually go on to try and persuade medical practitonners that cycling different antibiotics is a good thing to do. Certainly, it is better to cycle than to mix them into a single treatment, at least that s what our theories always say. This research will go a long way to proving that what works in theory, also works in the lab, and hopefully in practise too.

最优控制是一个用来描述使太空竞赛成为可能的研究的术语。尼尔·阿姆斯特朗的登月是通过了解如何以最少的燃料消耗操纵太空火箭而实现的。这项工作背后的想法是利用同样的基础工程科学，并通过了解如何以最佳方式使用抗生素来最大限度地减少破坏抗生素治疗的耐药性进化来应用它。我们已经可以在理论上做到这一点，我们能够创造出奇怪而奇妙的方式将抗生素部署到生物系统中，以最大限度地提高其健康。然而，过去提出的许多基于数学建模的生物学理论在正确的实验中被证明是错误的。种群生物学尤其如此，这是生物学的分支，研究微生物和其他细胞等生物种群的相互作用。现在，这项工作中的数学建模是群体生物学、细胞生物学和遗传学的混合;虽然空间研究人员有牛顿定律可以依靠，但群体生物学没有内在的物理定律。因此，有时候，理论概念在真正得到检验之前就已经存在了，这是该领域的一个特点。所以，我们想测试我们的理论破坏，以确保他们在实验室工作之前，我们最终继续尝试和说服医疗界的抗生素循环是一件好事。当然，最好是循环，而不是混合成一个单一的治疗，至少这是我们的理论总是说。这项研究将大大有助于证明理论上可行的方法在实验室中也有效，希望在实践中也有效。