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Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness
Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3698101/ https://www.ncbi.nlm.nih.gov/pubmed/23351881 http://dx.doi.org/10.1186/2041-1480-4-5 |
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author | Boyce, Richard D Horn, John R Hassanzadeh, Oktie Waard, Anita de Schneider, Jodi Luciano, Joanne S Rastegar-Mojarad, Majid Liakata, Maria |
author_facet | Boyce, Richard D Horn, John R Hassanzadeh, Oktie Waard, Anita de Schneider, Jodi Luciano, Joanne S Rastegar-Mojarad, Majid Liakata, Maria |
author_sort | Boyce, Richard D |
collection | PubMed |
description | Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market. |
format | Online Article Text |
id | pubmed-3698101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36981012013-07-02 Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness Boyce, Richard D Horn, John R Hassanzadeh, Oktie Waard, Anita de Schneider, Jodi Luciano, Joanne S Rastegar-Mojarad, Majid Liakata, Maria J Biomed Semantics Research Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market. BioMed Central 2013-01-26 /pmc/articles/PMC3698101/ /pubmed/23351881 http://dx.doi.org/10.1186/2041-1480-4-5 Text en Copyright © 2013 Boyce et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Boyce, Richard D Horn, John R Hassanzadeh, Oktie Waard, Anita de Schneider, Jodi Luciano, Joanne S Rastegar-Mojarad, Majid Liakata, Maria Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title | Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title_full | Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title_fullStr | Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title_full_unstemmed | Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title_short | Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
title_sort | dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3698101/ https://www.ncbi.nlm.nih.gov/pubmed/23351881 http://dx.doi.org/10.1186/2041-1480-4-5 |
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