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DTAT (version 0.3-7)

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 (2017a) and Norris (2017c) .

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Version

Install

install.packages('DTAT')

Monthly Downloads

310

Version

0.3-7

License

MIT + file LICENSE

Maintainer

David C. Norris

Last Published

May 25th, 2024

Functions in DTAT (0.3-7)

plot,DE,missing-method

Plot a DE object as an interactive htmlwidget

Objects exported from other packages

as_d3_data,DE-method

Convert a DE object to JSON

de.bioRxiv.240846

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

Perform neutrophil-guided dose titration of a chemotherapy drug.

An S4 class for simulating dose-titration study designs

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

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

Extract interval-censored dose tolerance data from a dose titration study

Calculate a dose-survival curve from a dose titration study, adding a confidence band

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

A seq method supporting custom-scaled plot axes.

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

Environment for simulation global variables.

Power-law scaling for doses

Run Shiny apps included in package DTAT

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

A dose titration algorithm (DTA) 'factory' based on the Newton-Raphson heuristic