Improving quality of science through better animal welfare: the NC3Rs strategy

Prescott, Mark J.; Lidster, Katie

doi:10.1038/laban.1217

Cited by 200 publications

(169 citation statements)

References 33 publications

Supporting

Mentioning

168

Contrasting

Unclassified

Order By: Relevance

“…Similarly to human population imaging, there are several well-founded motivations for animal population imaging: optimization of costs, reduction of experimentation duration, improvement of quality of science and enhancement of research discovery, notably by the use of sufficiently large animal cohorts for ensuring the validity of statistical results (see the special Lab Animal focus on reproducibility in animal research (Prescott and Lidster, 2017)). Although this domain is still in its infancy, we may expect that it will grow in the near future.…”

Section: Discussionmentioning

confidence: 99%

A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps

Deruelle¹,

Kober

Perles-Barbacaru

et al. 2020

Preprint

View full text Add to dashboard Cite

Similarly to human population imaging, there are several well-founded motivations for animal population imaging, the most notable being the improvement of the validity of statistical results by pooling a sufficient number of animal data provided by different imaging centers. In this paper, we demonstrate the feasibility of such a multicenter animal study, sharing raw data from forty rats and processing pipelines between four imaging centers. As specific use case, we considered the estimation of T1 and T2 maps for the healthy rat brain at 7T. We quantitatively report about the variability observed across two data provider centers and evaluate the influence of image processing steps on the final maps, by using three fitting algorithms from three centers.Finally, to derive relaxation time values per brain area, two multi-atlas segmentation pipelines from different centers were executed on two different platforms. In this study, the impact of the acquisition was 2.21% (not significant) and 9.52% on T1 and T2 estimates while the impact of the data processing pipeline was not significant (1.04% and 3.33%, respectively). In addition, the computed normality values can serve as relaxometry reference maps to explore differences to animal models of pathologies.

show abstract

Section: Discussionmentioning

confidence: 99%

A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps

Deruelle¹,

Kober

Perles-Barbacaru

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Similarly, the complexities of human diagnoses are ignored or glossed over at our peril 17,48,49,54,55 . A recurrent theme of this paper, and this special issue, is that the role that good animal wellbeing plays in good science also cannot be ignored 26,[41][42][43][56][57][58] . Furthermore, factors that are controlled or standardized have also been widely shown to affect both the model and scientific outcomes, from the infectious agents we choose to exclude 59 , to the choice of bedding materials [60][61][62] and enrichment [63][64][65] , to cage changing practices 66 , to handling technique 58 , to the identity 31 or sex 67 of the experimenter.…”

Section: Six Questions: What Do We Choose To Ignore?mentioning

confidence: 99%

“…17,18,26-28,39,41) do not represent a voice in the wilderness, but one voice in a chorus and that this emerging literature 1,2,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]42,43 reflects a nascent discipline which can be codified as the study of how knowledge is gained from animal research. We propose the title "Therioepistemology" This focus issue of Lab Animal coincides with a tipping point in biomedical research.…”

mentioning

confidence: 99%

Introducing Therioepistemology: the study of how knowledge is gained from animal research

et al. 2017

View full text Add to dashboard Cite

We are honored to write the opening article of this focus issue of Lab Animal. This focus issue could not occur at a more important time for biomedical research and the use of animals in science in general. The progressive worsening of success rates in human trials (currently 1 in 9 drugs entering human trials will succeed) 1-4 , combined with the explosion of interest in the reproducibility crisis 5-8 and the recognition that most drugs fail in human trials due to insufficient efficacy 1,2,4 , has led to a growing suspicion that the failure of translation from animal work to human outcomes may in some way reflect issues in animal research itself 5-19 -after all, every drug that fails in humans "worked" in an animal model. Indeed pharmaceutical companies continue to disinvest in internal animal R&D, a trend begun in the last decade, passing on the cost and risk to academia and startups 5,20 . Even this approach is not foolproof as pharmaceutical companies often cannot replicate the results of published work from academia 5,8,13 . Accordingly, there is a growing trend to focus on human, not animal, work for basic discovery 17 .Discarding animal research entirely is not the answer. When properly used, animal models have incredible value, not least the ability to follow biomarkers from birth to disease onset in a year or less (in the case of mice), which is impossible in humans 17,18 . There are patterns and principles that can help us identify models and results that are more or less likely to translate, and there are also easily realized, simple changes in the execution of animal work that will inherently improve translation [16][17][18] . This isn't a new concept; looking back over the last 10-15 years we can see many authors have been candid about the merits, strengths, weaknesses, reproducibility, and translatability of various animal models 1,2,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] . Our goal with this article is to unite the common themes in this broader emerging literature and this special issue.Thus, the central point is that we (i.e., refs. 17,18,26-28,39,41) do not represent a voice in the wilderness, but one voice in a chorus and that this emerging literature 1,2,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]42,43 reflects a nascent discipline which can be codified as the study of how knowledge is gained from animal research. We propose the title "Therioepistemology" This focus issue of Lab Animal coincides with a tipping point in biomedical research. For the first time, the scale of the reproducibility and translatability crisis is widely understood beyond the small cadre of researchers who have been studying it and the pharmaceutical and biotech companies who have been living it. Here we argue that an emerging literature, including the papers in this focus issue, has begun to congeal around a set of recurring themes, which themselves represent a paradigm shift. This paradigm shift can be c...

show abstract

“…In addition, other variables of animal model design can influence the magnitude of the treatment response [11] . These findings are highly relevant in the context of the 'reproducibility crisis' [12,13] as well as having ethical implications of the use of animals in research that is not of optimum quality [14] .…”

Section: Introductionmentioning

confidence: 96%

What influences treatment response in animal models of non-alcoholic fatty liver disease? A meta-analysis with meta-regression

Hunter

Duret

et al. 2019

Preprint

View full text Add to dashboard Cite

The classical drug development pipeline necessitates studies using animal models of human disease to gauge future efficacy in humans, however, there is a comparatively low conversion rate from success in animals to in humans. Non-alcoholic fatty liver disease (NAFLD) is a complex chronic disease without any licensed therapies and hence a major field of animal research. We performed a meta-analysis of 414 interventional rodent studies (6,575 animals) in NAFLD to assess the mean difference in hepatic triglyceride content. 20 of 21 studied drug classes had similar efficacy with a mean difference of −30% hepatic triglyceride. However, when publication bias was accounted for, this reduced to −16% difference. Study characteristics were only able to account for a minority of variability on meta-regression, and we replicated previous findings of high risk of bias across 82% of cohorts. These findings build on previous work in preclinical neuroscience and help to explain the challenge of reproducibility and translation within the field of metabolism.

show abstract

Improving quality of science through better animal welfare: the NC3Rs strategy

Cited by 200 publications

References 33 publications

A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps

A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps

Introducing Therioepistemology: the study of how knowledge is gained from animal research

What influences treatment response in animal models of non-alcoholic fatty liver disease? A meta-analysis with meta-regression

Contact Info

Product

Resources

About