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A Guide to Reproducibility in Preclinical Research

Many have raised concerns about the reproducibility of biomedical research. In this Perspective, the authors address this “reproducibility crisis” by distilling discussions around reproducibility into a simple guide to facilitate understanding of the topic. Reproducibility applies both within and ac...

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Detalles Bibliográficos
Autores principales: Samsa, Greg, Samsa, Leigh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published for the Association of American Medical Colleges by Lippincott Williams & Wilkins 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314499/
https://www.ncbi.nlm.nih.gov/pubmed/29995667
http://dx.doi.org/10.1097/ACM.0000000000002351
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author Samsa, Greg
Samsa, Leigh
author_facet Samsa, Greg
Samsa, Leigh
author_sort Samsa, Greg
collection PubMed
description Many have raised concerns about the reproducibility of biomedical research. In this Perspective, the authors address this “reproducibility crisis” by distilling discussions around reproducibility into a simple guide to facilitate understanding of the topic. Reproducibility applies both within and across studies. The following questions address reproducibility within studies: “Within a study, if the investigator repeats the data management and analysis, will she get an identical answer?” and “Within a study, if someone else starts with the same raw data, will she draw a similar conclusion?” Contrastingly, the following questions address reproducibility across studies: “If someone else tries to repeat an experiment as exactly as possible, will she draw a similar conclusion?” and “If someone else tries to perform a similar study, will she draw a similar conclusion?” Many elements of reproducibility from clinical trials can be applied to preclinical research (e.g., changing the culture of preclinical research to focus more on transparency and rigor). For investigators, steps toward improving reproducibility include specifying data analysis plans ahead of time to decrease selective reporting; more explicit data management and analysis protocols; and increasingly detailed experimental protocols, which allow others to repeat experiments. Additionally, senior investigators should take greater ownership of the details of their research (e.g., implementing active laboratory management practices, such as random audits of raw data [or at least reduced reliance on data summaries], more hands-on time overseeing experiments, and encouraging a healthy skepticism from all contributors). These actions will support a culture where rigor + transparency = reproducibility.
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spelling pubmed-63144992019-01-18 A Guide to Reproducibility in Preclinical Research Samsa, Greg Samsa, Leigh Acad Med Perspectives Many have raised concerns about the reproducibility of biomedical research. In this Perspective, the authors address this “reproducibility crisis” by distilling discussions around reproducibility into a simple guide to facilitate understanding of the topic. Reproducibility applies both within and across studies. The following questions address reproducibility within studies: “Within a study, if the investigator repeats the data management and analysis, will she get an identical answer?” and “Within a study, if someone else starts with the same raw data, will she draw a similar conclusion?” Contrastingly, the following questions address reproducibility across studies: “If someone else tries to repeat an experiment as exactly as possible, will she draw a similar conclusion?” and “If someone else tries to perform a similar study, will she draw a similar conclusion?” Many elements of reproducibility from clinical trials can be applied to preclinical research (e.g., changing the culture of preclinical research to focus more on transparency and rigor). For investigators, steps toward improving reproducibility include specifying data analysis plans ahead of time to decrease selective reporting; more explicit data management and analysis protocols; and increasingly detailed experimental protocols, which allow others to repeat experiments. Additionally, senior investigators should take greater ownership of the details of their research (e.g., implementing active laboratory management practices, such as random audits of raw data [or at least reduced reliance on data summaries], more hands-on time overseeing experiments, and encouraging a healthy skepticism from all contributors). These actions will support a culture where rigor + transparency = reproducibility. Published for the Association of American Medical Colleges by Lippincott Williams & Wilkins 2019-01 2018-07-10 /pmc/articles/PMC6314499/ /pubmed/29995667 http://dx.doi.org/10.1097/ACM.0000000000002351 Text en Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Association of American Medical Colleges. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Perspectives
Samsa, Greg
Samsa, Leigh
A Guide to Reproducibility in Preclinical Research
title A Guide to Reproducibility in Preclinical Research
title_full A Guide to Reproducibility in Preclinical Research
title_fullStr A Guide to Reproducibility in Preclinical Research
title_full_unstemmed A Guide to Reproducibility in Preclinical Research
title_short A Guide to Reproducibility in Preclinical Research
title_sort guide to reproducibility in preclinical research
topic Perspectives
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314499/
https://www.ncbi.nlm.nih.gov/pubmed/29995667
http://dx.doi.org/10.1097/ACM.0000000000002351
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