Improving predictions of the risk of resistance development against new and old antibiotics
The methods used today by academic researchers and the pharmaceutical industry to assess the risk of emergence of resistance, for example during development of new antibiotics or when assessing an old antibiotic, are sub-optimal. Even though easy to perform, the presently used serial passage procedu...
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Published in | Clinical microbiology and infection Vol. 21; no. 10; pp. 894 - 898 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.10.2015
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Subjects | |
Online Access | Get full text |
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Summary: | The methods used today by academic researchers and the pharmaceutical industry to assess the risk of emergence of resistance, for example during development of new antibiotics or when assessing an old antibiotic, are sub-optimal. Even though easy to perform, the presently used serial passage procedures, minimal prevention concentration measurements and determination of mutation rates in vitro are generally providing inadequate knowledge for risk assessment and making decisions to continue/discontinue drug development. These methods need to be complemented and replaced with more relevant methods such as determination of whether resistance genes already pre-exist in various metagenomes, and the likelihood that these genes can transfer into the relevant pathogens and be stably maintained. Furthermore, to determine the risk of emergence of mutationally conferred resistance the fitness effect of the resistance mechanism is key, as this parameter will determine the ability of the resistant mutants to be maintained and enriched in the host after they have emerged. This information combined with knowledge of bacterial population sizes and growth and killing dynamics at relevant infection sites should allow for better forecasting of the risk of resistance emerging in clinical settings. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 |
ISSN: | 1198-743X 1469-0691 1469-0691 |
DOI: | 10.1016/j.cmi.2015.05.012 |