The phase1b package implements a Bayesian approach to decision making
in early development clinical trials. As a background, the main purpose
of early trials is to determine whether a novel treatment demonstrates
sufficient safety and efficacy signals to warrant further investment
(Lee & Liu, 2008).
The new R package phase1b is a flexible toolkit that calculates many
properties to this end, especially in the oncology therapeutic area. The
primary focus of this package is on binary endpoints. The benefit of a
Bayesian approach is the possibility to account for prior data (Thall &
Simon, 1994) in that a new drug may have shown some signals of efficacy
owing to its proposed mode of action, or similar activity based on prior
data. The concept of the phase1b package is to evaluate the posterior
probability that the response rate with a novel drug is better than with
the current standard of care treatment in early phase trials such as
Phase I.
The phase1b package provides a facility for early development study
teams to decide on further development of a drug either through
designing for phase 2 or 3, or expansion cohorts. The prior distribution
can incorporate any previous data via mixtures of beta distributions.
Furthermore, based on an assumed true response rate if the novel drug
was administered in the wider population, the package calculates the
frequentist probability that a current clinical trial would be stopped
for efficacy or futility conditional on true values of the response,
otherwise known as operating characteristics.
The intended user is the early clinical trial statistician in the design and interim stage of their study and offers a flexible approach to setting priors and weighting.
You can install the development version of phase1b from
GitHub with:
devtools::install_github("https://github.com/Genentech/phase1b/", force = TRUE)
library(phase1b)An introductory vignette is currently being prepared. Use the help function in your console to access the documentation.
To cite phase1b please see
here.