Literature DB >> 24566269

In vitro microbial culture models and their application in drug development.

Saurabh Vyawahare1, Qiucen Zhang2, Alexandra Lau3, Robert H Austin4.   

Abstract

Drug development faces its nemesis in the form of drug resistance. The rate of bacterial resistance to antibiotics, or tumor resistance to chemotherapy decisively depends on the surrounding heterogeneous tissue. However, in vitro drug testing is almost exclusively done in well stirred, homogeneous environments. Recent advancements in microfluidics and microfabrication introduce opportunities to develop in vitro culture models that mimic the complex in vivo tissue environment. In this review, we will first discuss the design principles underlying such models. Then we will demonstrate two types of microfluidic devices that combine stressor gradients, cell motility, large population of competing/cooperative cells and time varying dosage of drugs. By incorporating ideas from how natural selection and evolution move drug resistance forward, we show that drug resistance can occur at much greater rates than in well-stirred environments. Finally, we will discuss the future direction of in vitro microbial culture models and how to extend the lessons learned from microbial systems to eukaryotic cells.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibiotics; Evolution; Microbes; Microfluidics; Resistance

Mesh:

Substances:

Year:  2014        PMID: 24566269     DOI: 10.1016/j.addr.2014.02.005

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  2 in total

1.  Growing from a few cells: combined effects of initial stochasticity and cell-to-cell variability.

Authors:  A Barizien; M S Suryateja Jammalamadaka; G Amselem; Charles N Baroud
Journal:  J R Soc Interface       Date:  2019-04-26       Impact factor: 4.118

Review 2.  Microfluidic Applications in Drug Development: Fabrication of Drug Carriers and Drug Toxicity Screening.

Authors:  Pei Zhao; Jianchun Wang; Chengmin Chen; Jianmei Wang; Guangxia Liu; Krishnaswamy Nandakumar; Yan Li; Liqiu Wang
Journal:  Micromachines (Basel)       Date:  2022-01-27       Impact factor: 2.891

  2 in total

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