Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Animal Models Reflecting Chronic Obstructive Pulmonary Disease and Related Respiratory Disorders : Translating Pre-Clinical Data into Clinical Relevance

Tanner, Lloyd LU and Single, Andrew Bruce LU (2020) In Journal of Innate Immunity 12(3). p.203-225
Abstract

Chronic obstructive pulmonary disease (COPD) affects the lives of an ever-growing number of people worldwide. The lack of understanding surrounding the pathophysiology of the disease and its progression has led to COPD becoming the third leading cause of death worldwide. COPD is incurable, with current treatments only addressing associated symptoms and sometimes slowing its progression, thus highlighting the need to develop novel treatments. However, this has been limited by the lack of experimental standardization within the respiratory disease research area. A lack of coherent animal models that accurately represent all aspects of COPD clinical presentation makes the translation of promising in vitrodata to human clinical trials... (More)

Chronic obstructive pulmonary disease (COPD) affects the lives of an ever-growing number of people worldwide. The lack of understanding surrounding the pathophysiology of the disease and its progression has led to COPD becoming the third leading cause of death worldwide. COPD is incurable, with current treatments only addressing associated symptoms and sometimes slowing its progression, thus highlighting the need to develop novel treatments. However, this has been limited by the lack of experimental standardization within the respiratory disease research area. A lack of coherent animal models that accurately represent all aspects of COPD clinical presentation makes the translation of promising in vitrodata to human clinical trials exceptionally challenging. Here, we review current knowledge within the COPD research field, with a focus on current COPD animal models. Moreover, we include a set of advantages and disadvantages for the selection of pre-clinical models for the identification of novel COPD treatments.

(Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Innate Immunity
volume
12
issue
3
pages
23 pages
publisher
Karger
external identifiers
  • scopus:85072643988
  • pmid:31527372
ISSN
1662-811X
DOI
10.1159/000502489
language
English
LU publication?
yes
id
bd4ced51-a546-4a5a-b246-f9e26922eadc
date added to LUP
2019-10-07 13:14:37
date last changed
2024-12-12 21:37:23
@article{bd4ced51-a546-4a5a-b246-f9e26922eadc,
  abstract     = {{<p>Chronic obstructive pulmonary disease (COPD) affects the lives of an ever-growing number of people worldwide. The lack of understanding surrounding the pathophysiology of the disease and its progression has led to COPD becoming the third leading cause of death worldwide. COPD is incurable, with current treatments only addressing associated symptoms and sometimes slowing its progression, thus highlighting the need to develop novel treatments. However, this has been limited by the lack of experimental standardization within the respiratory disease research area. A lack of coherent animal models that accurately represent all aspects of COPD clinical presentation makes the translation of promising in vitrodata to human clinical trials exceptionally challenging. Here, we review current knowledge within the COPD research field, with a focus on current COPD animal models. Moreover, we include a set of advantages and disadvantages for the selection of pre-clinical models for the identification of novel COPD treatments.</p>}},
  author       = {{Tanner, Lloyd and Single, Andrew Bruce}},
  issn         = {{1662-811X}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{203--225}},
  publisher    = {{Karger}},
  series       = {{Journal of Innate Immunity}},
  title        = {{Animal Models Reflecting Chronic Obstructive Pulmonary Disease and Related Respiratory Disorders : Translating Pre-Clinical Data into Clinical Relevance}},
  url          = {{http://dx.doi.org/10.1159/000502489}},
  doi          = {{10.1159/000502489}},
  volume       = {{12}},
  year         = {{2020}},
}