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Development of an automated appendix generation system (ARGUS) for clinical study reports
Data handling and tabulation are a time-consuming job when writing appendices for clinical study reports. The authors have developed an automated appendix generation system (ARGUS) conforming to the CDISC/SDTM standard using SAS (version 9.3) and R (version 3.3.1: for PK plot generation). It consist...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korean Society for Clinical Pharmacology and Therapeutics
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033538/ https://www.ncbi.nlm.nih.gov/pubmed/32095457 http://dx.doi.org/10.12793/tcp.2017.25.1.34 |
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author | Jang, Dooyeon Han, Seunghoon Yim, Dong-Seok |
author_facet | Jang, Dooyeon Han, Seunghoon Yim, Dong-Seok |
author_sort | Jang, Dooyeon |
collection | PubMed |
description | Data handling and tabulation are a time-consuming job when writing appendices for clinical study reports. The authors have developed an automated appendix generation system (ARGUS) conforming to the CDISC/SDTM standard using SAS (version 9.3) and R (version 3.3.1: for PK plot generation). It consists of the one main program and three subprograms. The program runs to convert a database file into an appendix document with about 100 tables and plots in MS Word format within one min after pressing the submit button under common desktop environments. We found that tasks of constructing appendices for a typical 2×2 crossover design study that have taken our team about 8 days were completed within 6 or 7 hours using the ARGUS system. |
format | Online Article Text |
id | pubmed-7033538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Korean Society for Clinical Pharmacology and Therapeutics |
record_format | MEDLINE/PubMed |
spelling | pubmed-70335382020-02-24 Development of an automated appendix generation system (ARGUS) for clinical study reports Jang, Dooyeon Han, Seunghoon Yim, Dong-Seok Transl Clin Pharmacol Original Article Data handling and tabulation are a time-consuming job when writing appendices for clinical study reports. The authors have developed an automated appendix generation system (ARGUS) conforming to the CDISC/SDTM standard using SAS (version 9.3) and R (version 3.3.1: for PK plot generation). It consists of the one main program and three subprograms. The program runs to convert a database file into an appendix document with about 100 tables and plots in MS Word format within one min after pressing the submit button under common desktop environments. We found that tasks of constructing appendices for a typical 2×2 crossover design study that have taken our team about 8 days were completed within 6 or 7 hours using the ARGUS system. Korean Society for Clinical Pharmacology and Therapeutics 2017-03 2017-03-15 /pmc/articles/PMC7033538/ /pubmed/32095457 http://dx.doi.org/10.12793/tcp.2017.25.1.34 Text en Copyright © 2017 Translational and Clinical Pharmacology http://creativecommons.org/licenses/by-nc/3.0/ It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/). |
spellingShingle | Original Article Jang, Dooyeon Han, Seunghoon Yim, Dong-Seok Development of an automated appendix generation system (ARGUS) for clinical study reports |
title | Development of an automated appendix generation system (ARGUS) for clinical study reports |
title_full | Development of an automated appendix generation system (ARGUS) for clinical study reports |
title_fullStr | Development of an automated appendix generation system (ARGUS) for clinical study reports |
title_full_unstemmed | Development of an automated appendix generation system (ARGUS) for clinical study reports |
title_short | Development of an automated appendix generation system (ARGUS) for clinical study reports |
title_sort | development of an automated appendix generation system (argus) for clinical study reports |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033538/ https://www.ncbi.nlm.nih.gov/pubmed/32095457 http://dx.doi.org/10.12793/tcp.2017.25.1.34 |
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