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Sabanés Bové, Daniel ; Seibold, Heidi ; Boulesteix, Anne-Laure ; Manitz, Juliane ; Gasparini, Alessandro ; Günhan, Burak K. ; Boix, Oliver ; Schüler, Armin ; Fillinger, Sven ; Nahnsen, Sven ; Jacob, Anna E. ; Jaki, Thomas

The statistical software revolution in pharmaceutical development: challenges and opportunities in open source

Sabanés Bové, Daniel, Seibold, Heidi, Boulesteix, Anne-Laure, Manitz, Juliane, Gasparini, Alessandro, Günhan, Burak K., Boix, Oliver, Schüler, Armin, Fillinger, Sven, Nahnsen, Sven, Jacob, Anna E. and Jaki, Thomas (2026) The statistical software revolution in pharmaceutical development: challenges and opportunities in open source. Drug Discovery Today 31 (2), p. 104613.

Date of publication of this fulltext: 25 Feb 2026 08:21
Article
DOI to cite this document: 10.5283/epub.78731


Abstract

Open-source statistical software development is increasingly the preferred solution for leveraging new statistical methods in the pharmaceutical industry. However, with a long history of relying on licensed analysis software, there are philosophical and organizational barriers to overcome. In particular, the sustainability, reliability, usability, and feasibility of maintaining open-source ...

Open-source statistical software development is increasingly the preferred solution for leveraging new statistical methods in the pharmaceutical industry. However, with a long history of relying on licensed analysis software, there are philosophical and organizational barriers to overcome. In particular, the sustainability, reliability, usability, and feasibility of maintaining open-source statistical software long-term must be ensured. Here, we describe the open-source revolution that is emerging in the pharmaceutical industry and how it facilitates greater scaling of innovative analytical methods in statistics. We discuss challenges to open-source software adoption and propose mitigation strategies. Furthermore, we illustrate the potential for open-source software development with examples of successful projects, which highlight the roles of cross-company collaboration, career paths, education, and community building.



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Details

Item typeArticle
Journal or Publication TitleDrug Discovery Today
Publisher:Elsevier
Open Access Type:CC-License
Volume:31
Number of Issue or Book Chapter:2
Page Range:p. 104613
Date21 January 2026
InstitutionsInformatics and Data Science > Department Machine Learning & Data Science
Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Identification Number
ValueType
10.1016/j.drudis.2026.104613DOI
Keywordssoftware, open source, statistics, clinical trials, pharmaceutical industry, academia
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgPartially
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-787318
Item ID78731

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