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Review
. 2017 Jul 25;117(3):332-339.
doi: 10.1038/bjc.2017.186. Epub 2017 Jun 29.

Embracing model-based designs for dose-finding trials

Sharon B Love  1 , Sarah Brown  2 , Christopher J Weir  3 , Chris Harbron  4 , Christina Yap  5 , Birgit Gaschler-Markefski  6 , James Matcham  7 , Louise Caffrey  8 , Christopher McKevitt  9 , Sally Clive  10 , Charlie Craddock  11 , James Spicer  12 , Victoria Cornelius  13
Affiliations
Review

Embracing model-based designs for dose-finding trials

Sharon B Love et al. Br J Cancer. .

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.

Conclusions: 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 dose-finding trials in academia.

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Conflict of interest statement

BG-M is an employee of Boehringer Ingelheim Pharma GmbH & Co. KG, CH is an employee of Roche Pharmaceuticals and JM is an employee of AstraZeneca. The other authors declare no other conflict of interest.

Figures

Figure 1
Figure 1
Percentage of respondents identifying each item as a barrier to implementing model-based designs. See Supplementary Table C for all items. CI=chief investigator.
Figure 2
Figure 2
Toxicity interval probabilities for all prespecified dose levels after one patient has been treated with 5 mg, showing the probabilities for (top) over-, (middle) target, and (bottom) undertoxicity. With green indicating safe doses and red indicating unsafe doses, this shows the current dose decision can be based solely on overtoxicity since only the overtoxicity graph has red doses. We wish to increase the dose if we can; the current patient took 5 mg, but 10 mg would also be safe; thus, the model proposes 10 mg for the next patient.
See this image and copyright information in PMC

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