Literature DB >> 32525023

A survey of within-host and between-hosts modelling for antibiotic resistance.

Josephine N A Tetteh1, Franziska Matthäus2, Esteban A Hernandez-Vargas3.   

Abstract

Antibiotic resistance is a global public health problem which has the attention of many stakeholders including clinicians, the pharmaceutical industry, researchers and policy makers. Despite the existence of many studies, control of resistance transmission has become a rather daunting task as the mechanisms underlying resistance evolution and development are not fully known. Here, we discuss the mechanisms underlying antibiotic resistance development, explore some treatment strategies used in the fight against antibiotic resistance and consider recent findings on collateral susceptibilities amongst antibiotic classes. Mathematical models have proved valuable for unravelling complex mechanisms in biology and such models have been used in the quest of understanding the development and spread of antibiotic resistance. While assessing the importance of such mathematical models, previous systematic reviews were interested in investigating whether these models follow good modelling practice. We focus on theoretical approaches used for resistance modelling considering both within and between host models as well as some pharmacodynamic and pharmakokinetic approaches and further examine the interaction between drugs and host immune response during treatment with antibiotics. Finally, we provide an outlook for future research aimed at modelling approaches for combating antibiotic resistance.
Copyright © 2020 Elsevier B.V. All rights reserved.

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Year:  2020        PMID: 32525023     DOI: 10.1016/j.biosystems.2020.104182

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  3 in total

Review 1.  The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling.

Authors:  Martin Zwanzig
Journal:  Comput Struct Biotechnol J       Date:  2020-12-29       Impact factor: 7.271

2.  Comparing optimization criteria in antibiotic allocation protocols.

Authors:  Alastair Jamieson-Lane; Alexander Friedrich; Bernd Blasius
Journal:  R Soc Open Sci       Date:  2022-03-23       Impact factor: 2.963

3.  Vibrio alginolyticus Survives From Ofloxacin Stress by Metabolic Adjustment.

Authors:  Yue Yin; Yuanpan Yin; Hao Yang; Zhuanggui Chen; Jun Zheng; Bo Peng
Journal:  Front Microbiol       Date:  2022-03-16       Impact factor: 5.640

  3 in total

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