Improving the ability of antimicrobial susceptibility tests to predict clinical outcome accurately: Adding metabolic evasion to the equation
| Autor: | Frédéric Peyrane, Nicolas Tesse, Jason Tasse, Guennaëlle Dieppois |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
ANTIMICROBIAL SUSCEPTIBILITY TESTS Physical protection Microbial Sensitivity Tests Bioinformatics Outcome (game theory) 03 medical and health sciences 0302 clinical medicine Antibiotic resistance Drug Resistance Bacterial Drug Discovery Humans Medicine Pharmacology Bacteria business.industry Decision Trees Bacterial Infections Antimicrobial Evasion (ethics) Anti-Bacterial Agents Patient management Treatment Outcome 030104 developmental biology 030220 oncology & carcinogenesis Target attainment business |
| Zdroj: | Drug Discovery Today. 26:2182-2189 |
| ISSN: | 1359-6446 |
| DOI: | 10.1016/j.drudis.2021.05.018 |
| Popis: | Antimicrobial susceptibility tests (AST) are based on the minimal inhibitory concentration (MIC), the method used worldwide to guide antimicrobial therapy. Despite its relevance in correctly predicting clinical outcome for most acute infections, this approach is misleading for multiple clinical cases in which pathogens do not grow rapidly, uniformly or with physical protection. This behaviour, named ‘metabolic evasion’ (ME), enables bacteria to survive antimicrobials. ME can result from different, and sometimes combined, bacterial mechanisms such as biofilms, intracellular growth, persisters or dormancy. We discuss how ME can influence the MIC-based probability of target attainment. We identify clinical cases in which this approach is undermined by ME and propose a new approach that takes ME into account in order to improve patient management and the evaluation of innovative drugs. |
| Databáze: | OpenAIRE |
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