A review of available software for adaptive clinical trial design
File(s)
Published version
Author(s)
Grayling, Michael John
Wheeler, Graham Mark
Type
Journal Article
Abstract
Background/aims:
The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design.
Methods:
We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest.
Results:
Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs.
Conclusions:
There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.
The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design.
Methods:
We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest.
Results:
Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs.
Conclusions:
There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.
Date Issued
2020-06-01
Date Acceptance
2019-12-26
Citation
Clinical Trials, 2020, 17 (3), pp.323-331
ISSN
1740-7745
Publisher
SAGE Publications
Start Page
323
End Page
331
Journal / Book Title
Clinical Trials
Volume
17
Issue
3
Copyright Statement
© The Author(s) 2020. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
License URL
Identifier
https://journals.sagepub.com/doi/10.1177/1740774520906398
Subjects
Science & Technology
Life Sciences & Biomedicine
Medicine, Research & Experimental
Research & Experimental Medicine
Code
dose escalation
group sequential
multi-stage
sample size re-estimation
phase I
II
phase II
III
Code
dose escalation
group sequential
multi-stage
phase I/II
phase II/III
sample size re-estimation
Adaptive Clinical Trials as Topic
Bayes Theorem
Biomarkers
Computer Simulation
Dose-Response Relationship, Drug
Humans
Research Design
Sample Size
Software
Humans
Bayes Theorem
Sample Size
Dose-Response Relationship, Drug
Research Design
Computer Simulation
Software
Biomarkers
Adaptive Clinical Trials as Topic
0104 Statistics
1103 Clinical Sciences
Statistics & Probability
Publication Status
Published
Date Publish Online
2020-02-17