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DTAT (version 0.3-4)

Dose Titration Algorithm Tuning

Description

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) and Norris (2017) .

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Version

Install

install.packages('DTAT')

Monthly Downloads

310

Version

0.3-4

License

MIT + file LICENSE

Maintainer

David C. Norris

Last Published

June 14th, 2020

Functions in DTAT (0.3-4)

DTAT-package

Dose Titration Algorithm Tuning: a Framework for Dose Individualization in Drug Development
DE-class

An S4 class for simulating dose-titration study designs
titrate

Perform neutrophil-guided dose titration of a chemotherapy drug.
dtat1000

Precomputed neutrophil-guided chemotherapy dose titration for 1000 simulated subjects.
titration

Simulate a ‘3+3/PC’ dose-titration trial
newton.raphson

A dose titration algorithm (DTA) 'factory' based on the Newton-Raphson heuristic
plot,DE,missing-method

Plot a DE object as an interactive htmlwidget
reexports

Objects exported from other packages
Onoue.Friberg

POMP PK/PD model for docetaxel, combining Onoue et al (2016) with Friberg et al (2002)
dose.survfit

Calculate a dose-survival curve from a dose titration study, adding a confidence band
de.bioRxiv.240846

Simulated ‘3+3/PC’ dose-titration study from bioRxiv paper no. 240846
as_d3_data,DE-method

Convert a DE object to JSON
scaled

Power-law scaling for doses
seq.function

A seq method supporting custom-scaled plot axes.
runDTATapp

Run Shiny apps included in package DTAT
sim

Environment for simulation global variables.
dose.survival

Extract interval-censored dose tolerance data from a dose titration study
ds.curve

Extract the dose-survival curve, with its upper and lower confidence band limits