Article: Clinical Trial Design Innovations for Precision Medicine in Asthma.
Advances in experimental medicine and biology
2023 Volume 1426, Page(s) 395–412
Abstract: Severe asthma is a spectrum disorder with numerous subsets, many of which are defined by clinical history and a general predisposition for T2 inflammation. Most of the approved therapies for severe asthma have required clinical trial designs with ... ...
Abstract | Severe asthma is a spectrum disorder with numerous subsets, many of which are defined by clinical history and a general predisposition for T2 inflammation. Most of the approved therapies for severe asthma have required clinical trial designs with population enrichment for exacerbation frequency and/or elevation of blood eosinophils. Moving beyond this framework will require trial designs that increase efficiency for studying nondominant subsets and continue to improve upon biomarker signatures. In addition to reviewing the current literature on biomarker-informed trials for severe asthma, this chapter will also review the advantages of master protocols and adaptive design methods for establishing the efficacy of new interventions in prospectively defined subsets of patients. The incorporation of methods that allow for data collection outside of traditional study visits at academic centers, called remote decentralized trial design, is a growing trend that may increase diversity in study participation and allow for enhanced resiliency during the COVID-19 pandemic. Finally, reaching the goals of precision medicine in asthma will require increased emphasis on effectiveness studies. Recent advances in real-world data utilization from electronic health records are also discussed with a view toward pragmatic trial designs that could also incorporate the evaluation of biomarker signatures. |
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MeSH term(s) | Humans ; Asthma/diagnosis ; Asthma/therapy ; Biomarkers ; Clinical Trials as Topic ; COVID-19/therapy ; Pandemics ; Precision Medicine |
Chemical Substances | Biomarkers |
Language | English |
Publishing date | 2023-07-17 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 410187-X |
ISSN | 0065-2598 |
ISSN | 0065-2598 |
DOI | 10.1007/978-3-031-32259-4_17 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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