Mathematical modelling of resistance emergence.

Sir, We read with great interest the article by Magee 1 and the associated correspondence. We would like to add to the discussion from our perspective. Using mathematical modelling and simulations, the study by Magee has offered us insights on resistance emergence from the global societal viewpoint (resistance epidemiology). 1 If these models are predictive, they are powerful research tools that would allow us to have a glimpse of the future as a result of any intervention (or the lack of) in public healthcare policy. Similar approaches have been used to evaluate the effectiveness of various treatment protocols to prevent the spread of antimicrobial resistance. 2,3 However, these models generally use assumed model parameter values (as opposed to values derived from collected data) to make predictions with respect to qualitative intervention(s), and many times the computer simulations could not be validated prospectively. Our group and others have been working on modelling of antimicrobial resistance at a different scale (experimental therapeutics). Using a mathematical modelling approach to understand the relationship between the antimicrobial exposure in a single patient and the likelihood of resistance emergence, we strive to rationally design dosing regimens that suppress (delay) the emergence of resistance. Such efforts can be evidenced by a selected list of our work published recently. 4–6 While the mathematical structures of these models may differ somewhat, the model parameter estimates are almost invariably derived from actual experimental data, and in most cases the model predictions are supported by prospective validation. We are hopeful that dosing regimens for new (and existing) antimicrobial agents will be designed more scientifically in the future, with the objective of long-term resistance suppression in mind, in addition to clinical cure of the patients and toxicity avoidance. It is our vision that the work of both groups of researchers could be combined in the future to provide a more robust assessment of the impact of antimicrobial agents’ utilization on the emergence of resistance.