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Quantitative Benefit–Risk Assessment: State of the Practice Within Industry
BACKGROUND: Benefit–risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit–risk assessment (qBRA) methods. METHODS: Semi-struc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864811/ https://www.ncbi.nlm.nih.gov/pubmed/33111177 http://dx.doi.org/10.1007/s43441-020-00230-3 |
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author | Smith, Meredith Y. van Til, Janine DiSantostefano, Rachael L. Hauber, A. Brett Marsh, Kevin |
author_facet | Smith, Meredith Y. van Til, Janine DiSantostefano, Rachael L. Hauber, A. Brett Marsh, Kevin |
author_sort | Smith, Meredith Y. |
collection | PubMed |
description | BACKGROUND: Benefit–risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit–risk assessment (qBRA) methods. METHODS: Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit–risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis. RESULTS: While most surveyed companies had applied qBRA, application was limited to a small number of assets—primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances. CONCLUSION: qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s43441-020-00230-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7864811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78648112021-02-16 Quantitative Benefit–Risk Assessment: State of the Practice Within Industry Smith, Meredith Y. van Til, Janine DiSantostefano, Rachael L. Hauber, A. Brett Marsh, Kevin Ther Innov Regul Sci Original Research BACKGROUND: Benefit–risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit–risk assessment (qBRA) methods. METHODS: Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit–risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis. RESULTS: While most surveyed companies had applied qBRA, application was limited to a small number of assets—primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances. CONCLUSION: qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s43441-020-00230-3) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-10-27 2021 /pmc/articles/PMC7864811/ /pubmed/33111177 http://dx.doi.org/10.1007/s43441-020-00230-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Smith, Meredith Y. van Til, Janine DiSantostefano, Rachael L. Hauber, A. Brett Marsh, Kevin Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title | Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title_full | Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title_fullStr | Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title_full_unstemmed | Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title_short | Quantitative Benefit–Risk Assessment: State of the Practice Within Industry |
title_sort | quantitative benefit–risk assessment: state of the practice within industry |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864811/ https://www.ncbi.nlm.nih.gov/pubmed/33111177 http://dx.doi.org/10.1007/s43441-020-00230-3 |
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