The within-host population and evolutionary dynamics of antibiotic treatment and resistance: what mathematical models and in mouseo experiments can tell us
Most of the rational (as opposed to purely empirical) design of antibiotic treatment regimes focuses on the worst-case situations, elderly and immune compromised patients in hospitals, where antibiotic treatment is necessary to save lives. However, more than 90% of antibiotic uses is in the community and employed primarily to treat immune competent patients to increase the reduce term and magnitude of the morbidity of acute bacterial infections that they would normally clear. Are the antibiotic treatment regimes designed for the worst-case situations optimal for the treatment of acute bacterial infections in immune competent patients? To address this question we have used mathematical and computer simulation models of the joint action of antibiotics and the innate immune system to explore the relationship between the rate of clearance of acute bacterial infections and the dose and term of antibiotic treatment. For our numerical analysis of the properties of these models, we use estimates of the pharmacodynamic parameters obtained in vitro for Staphylococcus aureus with bactericidal and bacteriostatic antibiotics. The results of our analysis suggest that if the innate immune system, primarily the phagocytic leucocytes, is adequately effective: (i) bacteriostatic and bactericidal will be similarly effective, (ii) low doses and short terms of use of antibiotics can be as effective as higher doses administered for longer periods, (iii) minority populations of bacteria resistant to the treating antibiotic will not ascend. I will consider how these predictions fit observations in treated patients, and how these hypotheses can be tested with experimental animals.