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Updated: Jul 5, 2025
Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach
Published on: December 14, 2019
Forecasting antimicrobial resistance evolution
Jens Rolff1, Sebastian Bonhoeffer2, Charlotte Kloft3
1Evolutionary Biology, Institute of Biology, Freie Universität Berlin, Berlin, Germany.
Abstract:
Antimicrobial resistance (AMR) is a major global health issue. Current measures for tackling it comprise mainly the prudent use of drugs, the development of new drugs, and rapid diagnostics. Relatively little attention has been given to forecasting the evolution of resistance. Here, we argue that forecasting has the potential to be a great asset in our arsenal of measures to tackle AMR. We argue that, if successfully implemented, forecasting resistance will help to resolve the antibiotic crisis in three ways: it will (i) guide a more sustainable use (and therefore lifespan) of antibiotics and incentivize investment in drug development, (ii) reduce the spread of AMR genes and pathogenic microbes in the environment and between patients, and (iii) allow more efficient treatment of persistent infections, reducing the continued evolution of resistance. We identify two important challenges that need to be addressed for the successful establishment of forecasting: (i) the development of bespoke technology that allows stakeholders to empirically assess the risks of resistance evolving during the process of drug development and therapeutic/preventive use, and (ii) the transformative shift in mindset from the current praxis of mostly addressing the problem of antibiotic resistance a posteriori to a concept of a priori estimating, and acting on, the risks of resistance.
Insights
Forecasting antimicrobial resistance (AMR) can combat the antibiotic crisis by guiding sustainable drug use, reducing resistance gene spread, and enabling efficient infection treatment. This proactive approach requires new technology and a mindset shift.
Area of Science:
- Microbiology
- Public Health
- Pharmacology
Background:
- Antimicrobial resistance (AMR) poses a significant global health threat.
- Current strategies focus on drug stewardship, new drug development, and diagnostics.
- Forecasting the evolution of resistance remains an under-addressed area.
Purpose of the Study:
- To highlight the potential of forecasting as a crucial tool against AMR.
- To outline how resistance forecasting can mitigate the antibiotic crisis.
- To identify key challenges for implementing resistance forecasting.
Main Methods:
- Conceptual analysis and argumentation.
- Literature review on AMR and forecasting methodologies.
- Identification of technological and mindset-related barriers.
Main Results:
- Forecasting can extend antibiotic lifespan and incentivize drug development.
- It can reduce the environmental and inter-patient spread of AMR.
- Forecasting enables better treatment of persistent infections, curbing further resistance evolution.
Conclusions:
- Successful AMR forecasting requires novel technologies for risk assessment.
- A paradigm shift from reactive to proactive resistance management is essential.
- Implementing forecasting will significantly enhance global efforts to combat AMR.
