Using predictive models to optimise the treatment of bacterial infections: combining a novel anti-virulence therapy with antibiotics
As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. In this talk, we consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy works by competitively inhibiting the binding of bacteria to host cells. This prevents the bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural clearance. We develop mathematical models to describe the anti-adhesion treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Our models predicted that, when used in isolation, anti-adhesion therapy can at best reduce the bacterial burden, whereas elimination of all bacteria may be possible when combined with regular debridement. We then extend our models to include treatment with antibiotics, using them to predict the optimum treatment regimes for this combination therapy.