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Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review

Clinical trials are time consuming, expensive, and often burdensome on patients. Clinical trials can fail for many reasons. This survey reviews many of these reasons and offers insights on opportunities for improving the likelihood of creating and executing successful clinical trials. Literature fro...

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Detalles Bibliográficos
Autor principal: Fogel, David B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092479/
https://www.ncbi.nlm.nih.gov/pubmed/30112460
http://dx.doi.org/10.1016/j.conctc.2018.08.001
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author Fogel, David B.
author_facet Fogel, David B.
author_sort Fogel, David B.
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description Clinical trials are time consuming, expensive, and often burdensome on patients. Clinical trials can fail for many reasons. This survey reviews many of these reasons and offers insights on opportunities for improving the likelihood of creating and executing successful clinical trials. Literature from the past 30 years was reviewed for relevant data. Common patterns in reported successful trials are identified, including factors regarding the study site, study coordinator/investigator, and the effects on participating patients. Specific instances where artificial intelligence can help improve clinical trials are identified.
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spelling pubmed-60924792018-08-15 Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review Fogel, David B. Contemp Clin Trials Commun Article Clinical trials are time consuming, expensive, and often burdensome on patients. Clinical trials can fail for many reasons. This survey reviews many of these reasons and offers insights on opportunities for improving the likelihood of creating and executing successful clinical trials. Literature from the past 30 years was reviewed for relevant data. Common patterns in reported successful trials are identified, including factors regarding the study site, study coordinator/investigator, and the effects on participating patients. Specific instances where artificial intelligence can help improve clinical trials are identified. Elsevier 2018-08-07 /pmc/articles/PMC6092479/ /pubmed/30112460 http://dx.doi.org/10.1016/j.conctc.2018.08.001 Text en © 2018 The Author http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Fogel, David B.
Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title_full Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title_fullStr Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title_full_unstemmed Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title_short Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
title_sort factors associated with clinical trials that fail and opportunities for improving the likelihood of success: a review
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092479/
https://www.ncbi.nlm.nih.gov/pubmed/30112460
http://dx.doi.org/10.1016/j.conctc.2018.08.001
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