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Published on: March 30, 2014
Evaluation of a new antiresistic strategy to manage antibiotic resistance
Hong Ming Tan1, Ambika C Lall2, Jussi Keppo1
1National University of Singapore Business School, Singapore; Institute of Operations Research and Analytics, Singapore.
Objectives:
Systemic strategies for combating antimicrobial resistance (AMR) currently focus on limiting antibiotic use and have been generally insufficient in preventing the rise of AMR. Additionally, they often generate other adverse incentives, such as discouraging pharmaceutical companies from investing in research and development of new antibiotics, further exacerbating the problem. This paper proposes a novel systemic strategy for tackling AMR, which we term 'antiresistics': any intervention (whether a small molecule, genetic element, phage, or whole organism) that reduces resistance rates in pathogen populations. A prime example of an antiresistic would be a small molecule that specifically disrupts the maintenance of antibiotic resistance plasmids. Of note, an antiresistic would be expected to have a population-level effect and not necessarily be useful on a time scale relevant to individual patients.
Methods:
We developed a mathematical model to assess the effect of antiresistics on population resistance levels and calibrated it to longitudinal data available at the country level. We also estimated potential effects on idealised rates for the introduction of new antibiotics.
Results:
The model shows that greater use of antiresistics allows for greater usage of existing antibiotics. This leads to an ability to maintain a constant overall rate of antibiotic efficacy with a slower rate of developing new antibiotics; subsequently, antiresistics have a positive benefit on the effective lifetime and thus profitability of antibiotics.
Conclusions:
By directly reducing resistance rates, antiresistics can provide clear qualitative benefits (which may be quantitatively large) in terms of existing antibiotic efficacy, longevity, and alignment of incentives.
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