Prediction of Antibiotic Resistance: Time for a New Preclinical Paradigm?

Morten O. A. Sommer, Christian Munck, Rasmus Vendler Toft-Kehler, Dan I. Andersson

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development. In this Opinion article, we argue that the traditional procedures that are used for the prediction of antibiotic resistance today could be markedly improved by including a broader analysis of bacterial fitness, infection dynamics, horizontal gene transfer and other factors. This will lead to more informed preclinical decisions for continuing or discontinuing the development of drug candidates.
    Original languageEnglish
    JournalNature Reviews Microbiology
    Volume15
    Issue number11
    Pages (from-to)689–696
    Number of pages8
    ISSN1740-1534
    DOIs
    Publication statusPublished - 2017

    Bibliographical note

    CBS Library does not have access to the material

    Keywords

    • Antibacterial drug resistance
    • Antibiotics
    • Antimicrobial resistance
    • Bacterial evolution
    • Bacterial genetics
    • Clinical microbiology
    • Policy and public health in microbiology

    Cite this

    Sommer, M. O. A., Munck, C., Toft-Kehler, R. V., & Andersson, D. I. (2017). Prediction of Antibiotic Resistance: Time for a New Preclinical Paradigm? Nature Reviews Microbiology, 15(11), 689–696. https://doi.org/10.1038/nrmicro.2017.75