From 4ddab7f5c822f4126e271a4ea219e5ecc1a84d0a Mon Sep 17 00:00:00 2001 From: Audrey Yeo Date: Wed, 4 Sep 2024 18:04:25 +0200 Subject: [PATCH] Update README.rmd Co-authored-by: Daniel Sabanes Bove --- README.rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.rmd b/README.rmd index ec6a2d76..3f54e4f0 100644 --- a/README.rmd +++ b/README.rmd @@ -7,7 +7,7 @@ output: github_document hex logo -The phase1b package project is a a Bayesian approach to decision making in early development clinical trials. +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 (Yeo et al, 2024) 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 expanding current 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. ## Installation