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Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing
Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6590385/ https://www.ncbi.nlm.nih.gov/pubmed/30303528 http://dx.doi.org/10.1002/cpt.1255 |
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author | Schmider, Juergen Kumar, Krishan LaForest, Chantal Swankoski, Brian Naim, Karen Caubel, Patrick M. |
author_facet | Schmider, Juergen Kumar, Krishan LaForest, Chantal Swankoski, Brian Naim, Karen Caubel, Patrick M. |
author_sort | Schmider, Juergen |
collection | PubMed |
description | Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of three commercial vendors. The result confirmed the feasibility of using artificial intelligence–based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time‐consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method used in the pilot was able to differentiate vendor capabilities and identify the best candidate to move into the discovery phase. |
format | Online Article Text |
id | pubmed-6590385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65903852019-07-08 Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing Schmider, Juergen Kumar, Krishan LaForest, Chantal Swankoski, Brian Naim, Karen Caubel, Patrick M. Clin Pharmacol Ther Research Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of three commercial vendors. The result confirmed the feasibility of using artificial intelligence–based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time‐consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method used in the pilot was able to differentiate vendor capabilities and identify the best candidate to move into the discovery phase. John Wiley and Sons Inc. 2018-12-11 2019-04 /pmc/articles/PMC6590385/ /pubmed/30303528 http://dx.doi.org/10.1002/cpt.1255 Text en © 2018 Pfizer Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Schmider, Juergen Kumar, Krishan LaForest, Chantal Swankoski, Brian Naim, Karen Caubel, Patrick M. Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title | Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title_full | Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title_fullStr | Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title_full_unstemmed | Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title_short | Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing |
title_sort | innovation in pharmacovigilance: use of artificial intelligence in adverse event case processing |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6590385/ https://www.ncbi.nlm.nih.gov/pubmed/30303528 http://dx.doi.org/10.1002/cpt.1255 |
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