DTAT: Dose Titration Algorithm Tuning

DTAT is a methodologic framework allowing dose individualization to be conceived as a continuous learning process that begins in early-phase clinical trials and continues throughout drug development, on into clinical practice. This package includes code that researchers may use to reproduce or extend key results of the DTAT research programme, plus tools for trialists to design and simulate a '3+3/PC' dose-finding study. Please see Norris (2017) <doi:10.12688/f1000research.10624.3> and Norris (2017) <doi:10.1101/240846>.

Package details

AuthorDavid C. Norris [aut, cre]
MaintainerDavid C. Norris <[email protected]>
LicenseMIT + file LICENSE
URL https://osf.io/5479p/
Package repositoryView on CRAN
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DTAT documentation built on Feb. 21, 2019, 4:34 p.m.