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Journal article

Embracing model-based designs for dose-finding trials

Abstract:
Background
Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose-finding, such as the continual reassessment method (CRM).

Methods
We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation.

Results
We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators’ preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome.

Conclusion
There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for does-finding trials in academia.
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1038/bjc.2017.186

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Centre for Statistics in Medicine
Role:
Author


More from this funder
Funding agency for:
Love, S
Grant:
C5529/A16895


Publisher:
Springer Nature
Journal:
British Journal of Cancer More from this journal
Volume:
117
Issue:
3
Pages:
332–339
Publication date:
2017-06-29
Acceptance date:
2017-05-04
DOI:
EISSN:
1532-1827
ISSN:
0007-0920


Keywords:
Pubs id:
pubs:695680
UUID:
uuid:3ec3ed37-67a6-4ed8-8384-41d091d28508
Local pid:
pubs:695680
Deposit date:
2017-05-18

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