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Incorporating digitally derived endpoints within clinical development programs by leveraging prior work
Digital health technologies (DHTs) enable remote data collection, support a patient-centric approach to drug development, and provide real-time data in real-world settings. With increasing use of DHTs in clinical care and development, we expect a growing body of evidence supporting use of DHTs to ca...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415378/ https://www.ncbi.nlm.nih.gov/pubmed/37563201 http://dx.doi.org/10.1038/s41746-023-00886-9 |
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author | Bertha, Amy Alaj, Rinol Bousnina, Imein Doyle, Megan K. Friend, Danielle Kalamegham, Rasika Oliva, Lauren Knezevic, Igor Kramer, Frank Podhaisky, Hans-Peter Reimann, Sven |
author_facet | Bertha, Amy Alaj, Rinol Bousnina, Imein Doyle, Megan K. Friend, Danielle Kalamegham, Rasika Oliva, Lauren Knezevic, Igor Kramer, Frank Podhaisky, Hans-Peter Reimann, Sven |
author_sort | Bertha, Amy |
collection | PubMed |
description | Digital health technologies (DHTs) enable remote data collection, support a patient-centric approach to drug development, and provide real-time data in real-world settings. With increasing use of DHTs in clinical care and development, we expect a growing body of evidence supporting use of DHTs to capture endpoint data in clinical trials. As the body of evidence grows, it will be critical to ensure that available prior work can be leveraged. We propose a framework to reuse analytical and clinical validation, as well as verification data, generated for existing DHTs. We apply real life case studies to illustrate our proposal aimed at leveraging prior work, while applying the V3 framework (verification, analytical validation, clinical validation) and avoiding duplication. Utilizing our framework will enable stakeholders to share best practices and consistent approaches to employing these tools in clinical studies, build on each other’s work, and ultimately accelerate evidence generation demonstrating the reproducibility and value add of these new tools. |
format | Online Article Text |
id | pubmed-10415378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104153782023-08-12 Incorporating digitally derived endpoints within clinical development programs by leveraging prior work Bertha, Amy Alaj, Rinol Bousnina, Imein Doyle, Megan K. Friend, Danielle Kalamegham, Rasika Oliva, Lauren Knezevic, Igor Kramer, Frank Podhaisky, Hans-Peter Reimann, Sven NPJ Digit Med Comment Digital health technologies (DHTs) enable remote data collection, support a patient-centric approach to drug development, and provide real-time data in real-world settings. With increasing use of DHTs in clinical care and development, we expect a growing body of evidence supporting use of DHTs to capture endpoint data in clinical trials. As the body of evidence grows, it will be critical to ensure that available prior work can be leveraged. We propose a framework to reuse analytical and clinical validation, as well as verification data, generated for existing DHTs. We apply real life case studies to illustrate our proposal aimed at leveraging prior work, while applying the V3 framework (verification, analytical validation, clinical validation) and avoiding duplication. Utilizing our framework will enable stakeholders to share best practices and consistent approaches to employing these tools in clinical studies, build on each other’s work, and ultimately accelerate evidence generation demonstrating the reproducibility and value add of these new tools. Nature Publishing Group UK 2023-08-10 /pmc/articles/PMC10415378/ /pubmed/37563201 http://dx.doi.org/10.1038/s41746-023-00886-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Comment Bertha, Amy Alaj, Rinol Bousnina, Imein Doyle, Megan K. Friend, Danielle Kalamegham, Rasika Oliva, Lauren Knezevic, Igor Kramer, Frank Podhaisky, Hans-Peter Reimann, Sven Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title | Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title_full | Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title_fullStr | Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title_full_unstemmed | Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title_short | Incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
title_sort | incorporating digitally derived endpoints within clinical development programs by leveraging prior work |
topic | Comment |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415378/ https://www.ncbi.nlm.nih.gov/pubmed/37563201 http://dx.doi.org/10.1038/s41746-023-00886-9 |
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