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Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research

BACKGROUND: The public and healthcare workers have a high expectation of animal research which they perceive as necessary to predict the safety and efficacy of drugs before testing in clinical trials. However, the expectation is not always realised and there is evidence that the research often fails...

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Autor principal: Green, Susan Bridgwood
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517563/
https://www.ncbi.nlm.nih.gov/pubmed/26215508
http://dx.doi.org/10.1186/s12910-015-0043-7
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author Green, Susan Bridgwood
author_facet Green, Susan Bridgwood
author_sort Green, Susan Bridgwood
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description BACKGROUND: The public and healthcare workers have a high expectation of animal research which they perceive as necessary to predict the safety and efficacy of drugs before testing in clinical trials. However, the expectation is not always realised and there is evidence that the research often fails to stand up to scientific scrutiny and its 'predictive value' is either weak or absent. DISCUSSION: Problems with the use of animals as models of humans arise from a variety of biases and systemic failures including: 1) bias and poor practice in research methodology and data analysis; 2) lack of transparency in scientific assessment and regulation of the research; 3) long-term denial of weaknesses in cross-species translation; 4) profit-driven motives overriding patient interests; 5) lack of accountability of expenditure on animal research; 6) reductionist-materialism in science which tends to dictate scientific inquiry and control the direction of funding in biomedical research. SUMMARY: Bias in animal research needs to be addressed before medical research and healthcare decision-making can be more evidence-based. Research funding may be misdirected on studying 'disease mechanisms' in animals that cannot be replicated outside tightly controlled laboratory conditions, and without sufficient critical evaluation animal research may divert attention away from avenues of research that hold promise for human health. The potential for harm to patients and trial volunteers from reliance on biased animal data(1) requires measures to improve its conduct, regulation and analysis. This article draws attention to a few of the many forms of bias in animal research that have come to light in the last decade and offers a strategy incorporating ten recommendations stated at the end of each section on bias. The proposals need development through open debate and subsequent rigorous implementation so that reviewers may determine the value of animal research to human health. The 10Rs + are protected by a Creative Commons Attribution 3.0 Unported License and therefore may be 'shared, remixed or built on, even commercially, so long as attributed by giving appropriate credit with a link to the license, and indicate if changes were made.’ ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12910-015-0043-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-45175632015-07-29 Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research Green, Susan Bridgwood BMC Med Ethics Debate BACKGROUND: The public and healthcare workers have a high expectation of animal research which they perceive as necessary to predict the safety and efficacy of drugs before testing in clinical trials. However, the expectation is not always realised and there is evidence that the research often fails to stand up to scientific scrutiny and its 'predictive value' is either weak or absent. DISCUSSION: Problems with the use of animals as models of humans arise from a variety of biases and systemic failures including: 1) bias and poor practice in research methodology and data analysis; 2) lack of transparency in scientific assessment and regulation of the research; 3) long-term denial of weaknesses in cross-species translation; 4) profit-driven motives overriding patient interests; 5) lack of accountability of expenditure on animal research; 6) reductionist-materialism in science which tends to dictate scientific inquiry and control the direction of funding in biomedical research. SUMMARY: Bias in animal research needs to be addressed before medical research and healthcare decision-making can be more evidence-based. Research funding may be misdirected on studying 'disease mechanisms' in animals that cannot be replicated outside tightly controlled laboratory conditions, and without sufficient critical evaluation animal research may divert attention away from avenues of research that hold promise for human health. The potential for harm to patients and trial volunteers from reliance on biased animal data(1) requires measures to improve its conduct, regulation and analysis. This article draws attention to a few of the many forms of bias in animal research that have come to light in the last decade and offers a strategy incorporating ten recommendations stated at the end of each section on bias. The proposals need development through open debate and subsequent rigorous implementation so that reviewers may determine the value of animal research to human health. The 10Rs + are protected by a Creative Commons Attribution 3.0 Unported License and therefore may be 'shared, remixed or built on, even commercially, so long as attributed by giving appropriate credit with a link to the license, and indicate if changes were made.’ ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12910-015-0043-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-28 /pmc/articles/PMC4517563/ /pubmed/26215508 http://dx.doi.org/10.1186/s12910-015-0043-7 Text en © Green. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Debate
Green, Susan Bridgwood
Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title_full Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title_fullStr Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title_full_unstemmed Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title_short Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research
title_sort can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? bias in preclinical animal research
topic Debate
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517563/
https://www.ncbi.nlm.nih.gov/pubmed/26215508
http://dx.doi.org/10.1186/s12910-015-0043-7
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