drugdevelopR: Planning of phase II/III drug development programs with optimal sample size allocation and Go/No-go decision rules in R

Sample size determination is crucial in phase II/III drug development programs, impacting the likelihood of meeting program objectives. Within a utility-based framework, methods for optimal designs were developed recently, i.e., optimal go/no-go decision rules (whether to stop or to proceed to phase III) and optimal sample sizes minimizing the cost while maximizing the chances of achieving the program objective. These approaches can accommodate diverse scenarios like multiple phase III trials, arms, or endpoints. To facilitate the usability, the drugdevelopR R package and R Shiny applications were implemented. A sophisticated quality validation concept consisting of measures for archiving, versioning, bug reporting, and code documentation was developed, assuring reliable results.

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Publication Details

Journal
SoftwareX
Published
2025-02-12
DOI
https://doi.org/10.1016/j.softx.2025.102066
Citations
1
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
2.63

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article

drugdevelopR: Planning of phase II/III drug development programs with optimal sample size allocation and Go/No-go decision rules in R

Marietta Kirchner, Stella Erdmann, Meinhard Kieser, Lukas D. Sauer et al.
1 citations
SoftwareX
Statistical Methods in Clinical Trials
2.63
article

drugdevelopR: Planning of phase II/III drug development programs with optimal sample size allocation and Go/No-go decision rules in R

Marietta Kirchner, Stella Erdmann, Meinhard Kieser, Lukas D. Sauer, Johannes Cepicka
article en
1 citations

Abstract

Sample size determination is crucial in phase II/III drug development programs, impacting the likelihood of meeting program objectives. Within a utility-based framework, methods for optimal designs were developed recently, i.e., optimal go/no-go decision rules (whether to stop or to proceed to phase III) and optimal sample sizes minimizing the cost while maximizing the chances of achieving the program objective. These approaches can accommodate diverse scenarios like multiple phase III trials, arms, or endpoints. To facilitate the usability, the drugdevelopR R package and R Shiny applications were implemented. A sophisticated quality validation concept consisting of measures for archiving, versioning, bug reporting, and code documentation was developed, assuring reliable results.

SoftwareXVol. 30
Heidelberg University (DE), Zimmer Biomet (Germany) (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 15%
Statistical Methods in Clinical Trials
2.63
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drugdevelopR: Planning of phase II/III drug development programs with optimal sample size allocation and Go/No-go decision rules in R — Marietta Kirchner, Stella Erdmann, et al. · SoftwareX (2025) | TGRS Research Map | TGRS