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Antimicrobial resistance (AMR) is a problem of utmost importance that must be tackled urgently if we are to escape returning to a pre-antibiotic era. Annual deaths caused worldwide as a result of AMR are currently estimated at 700,000, with a staggering projection of 10 million by 2050 if the problem is not adequately addressed [1]. Indeed the rise of AMR extends beyond bacterial infections and will render treatments that rely on immunosuppression, such as chemotherapy, unusable due to the risk of ensuing infection, intensifying the health and economic impacts of AMR.

Harnessing the skills of multiple disciplines will be key to tackling AMR. Mathematical modelling is an invaluable tool with which to test and develop treatments in silico and has been used successfully in a variety of medical applications. We seek to bring together mathematicians with scientists from diverse disciplines (e.g. microbiology, physics, computer science, clinicians, pharmaceutical companies) to share and discuss the most up to date approaches in using modelling to develop novel antibacterials.

State of the art approaches are required not only to develop novel treatments against bacterial infections, but also to design therapies specifically to minimise the likelihood of the emergence of AMR. In addition to conventional antibiotics, we will consider research into anti-virulence treatments that inhibit the ability of the bacteria to cause infection, rather than directly killing bacteria (as antibiotics do); in theory this change in mechanism of action should lower the selective pressure that gives rise to drug resistance emerging. Thus far, prototypes have generally been partially successful in experimental work; mathematical modelling will play a fundamental role in determining how to improve these treatments either through structural changes (represented by model parameter alterations), carefully designed dosing regimens (using optimisation techniques) or in combination with other treatment types.

A variety of mathematical approaches can be employed to model novel treatments and the emergence of AMR including, but not limited to, ordinary, partial and stochastic differential equations, asymptotic analysis for reduction of necessarily complex models, statistical inference for parameterisation, agent based modelling  and optimisation techniques. By bringing together people from these fields from across the world, the latest techniques and results in each of these will be showcased and discussed to ensure dissemination to relevant research groups.

[1] O’Neill. Antimicrobial resistance: tackling a crisis for the health and wealth of nations. https://amrreview.org/, 2014. [Online; accessed 10-April-2017].

Invited Speakers