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

最优控制是一个术语，用来描述使太空竞赛成为可能的研究。尼尔·阿姆斯特朗·S的登月是因为了解了如何以最小的燃料消耗操纵太空火箭。这项工作背后的想法是，采用同样的基础工程科学，并将其应用于研究，通过了解如何以最佳方式部署抗生素，是否可以以某种方式最小化影响抗生素治疗的耐药性的演变。从理论上讲，我们已经可以做到这一点，我们能够创造出奇怪而奇妙的方法来将抗生素部署到生物系统中，以使其健康最大化。然而，过去已经提出了许多基于数学模型的生物学理论，当正确的实验被证明是完全错误的。对于种群生物学来说尤其如此，这是生物学的一个分支，研究微生物和其他细胞等相互作用的生物种群。现在，这项工作中的数学模型是种群生物学、细胞生物学和遗传学的混合体；太空研究人员有牛顿·S定律可以依靠，而种群生物学没有内在的物理规律。因此，理论概念在真正得到检验之前就坚持下来，这有时是该领域的一个特点。因此，我们想要对我们的理论进行彻底的测试，以确保它们在实验室中有效，然后我们才能继续尝试并说服医生们，循环使用不同的抗生素是一件好事。当然，骑自行车总比把它们混合成一种疗法要好，至少S就像我们的理论总是说的那样。这项研究将在很大程度上证明，在理论上可行的东西，在实验室里也是可行的，希望在实践中也能奏效。

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.