风险分析(工程)
抗生素耐药性
抗性(生态学)
生物
药物开发
过程(计算)
抗药性
重症监护医学
生物技术
业务
计算机科学
抗生素
药品
医学
生态学
药理学
操作系统
微生物学
作者
Jens Rolff,Sebastian Bonhoeffer,Charlotte Kloft,Rasmus Leistner,Roland R. Regoes,Michael Hochberg
标识
DOI:10.1016/j.tim.2023.12.009
摘要
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.
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