<strong>A Maturity Model for the Scientific Review of Clinical Trial Designs and Their Informativeness </strong>
Many clinical trials end uninformatively. Informativeness, in the context of clinical trials, defines whether a study&rsquo;s results definitively answer its research questions with meaningful next steps. One subset of these trials are those focused on global health set in low-resource settings. Global health clinical trials benefitting people in low-resource settings are funded primarily by a limited number of large foundations, pharmaceutical firms (&ldquo;industry&rdquo;), and national governments. While clinical trial protocols are required to go through reviews in regulatory and ethical domains, outside of industry-funded trials, funders rarely require focused scientific design reviews. There are no documented standards and processes, or even best practices, for funders to perform scientific reviews after the funding commitment. Considering the investment in and standardization of ethical and regulatory reviews, and the prevalence of studies ending without clarity or never finishing, it may be that scientific reviews of trial designs with a focus on informativeness offer the best chance for improved outcomes and return on investments in clinical trials. A maturity model is a helpful tool for knowledge transfer to help grow capabilities in a new area, or for those looking to perform a self-assessment in an existing area. Such a model is offered for scientific design reviews of clinical trial protocols: a valuable and often-neglected governance step for funders or sponsors, among others. This maturity model includes 11 process areas and 5 maturity levels. Each of the 55 process area levels is populated with descriptions on a continuum toward an optimal state to improve trial protocols in the area of risk of failure. This tool allows for prescriptive guidance on next investments to improve attributes of post-funding reviews of trials, with a focus on informativeness..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Preprints.org - (2023) vom: 11. Apr. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Dolley, Shawn [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.20944/preprints202304.0147.v1 |
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| PPN (Katalog-ID): |
preprintsorg039218295 |
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| 520 | |a Many clinical trials end uninformatively. Informativeness, in the context of clinical trials, defines whether a study&rsquo;s results definitively answer its research questions with meaningful next steps. One subset of these trials are those focused on global health set in low-resource settings. Global health clinical trials benefitting people in low-resource settings are funded primarily by a limited number of large foundations, pharmaceutical firms (&ldquo;industry&rdquo;), and national governments. While clinical trial protocols are required to go through reviews in regulatory and ethical domains, outside of industry-funded trials, funders rarely require focused scientific design reviews. There are no documented standards and processes, or even best practices, for funders to perform scientific reviews after the funding commitment. Considering the investment in and standardization of ethical and regulatory reviews, and the prevalence of studies ending without clarity or never finishing, it may be that scientific reviews of trial designs with a focus on informativeness offer the best chance for improved outcomes and return on investments in clinical trials. A maturity model is a helpful tool for knowledge transfer to help grow capabilities in a new area, or for those looking to perform a self-assessment in an existing area. Such a model is offered for scientific design reviews of clinical trial protocols: a valuable and often-neglected governance step for funders or sponsors, among others. This maturity model includes 11 process areas and 5 maturity levels. Each of the 55 process area levels is populated with descriptions on a continuum toward an optimal state to improve trial protocols in the area of risk of failure. This tool allows for prescriptive guidance on next investments to improve attributes of post-funding reviews of trials, with a focus on informativeness. | ||
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